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case e_a
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ₁ : Perm m
σ₂ : Perm n
⊢ ↑↑(sign σ₁) * ↑↑(sign σ₂) = ↑↑(sign (Equiv.sumCongr σ₁ σ₂)) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
| rw [sign_sumCongr, Units.val_mul, Int.cast_mul] | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
⊢ ∀ (a₁ a₂ : Perm m × Perm n) (ha₁ : a₁ ∈ univ) (ha₂ : a₂ ∈ univ),
(fun σ x => Equiv.sumCongr σ.1 σ.2) a₁ ha₁ = (fun σ x => Equiv.sumCongr σ.1 σ.2) a₂ ha₂ → a₁ = a₂ | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· | intro σ₁ σ₂ h₁ h₂ | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· | Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ₁ σ₂ : Perm m × Perm n
h₁ : σ₁ ∈ univ
h₂ : σ₂ ∈ univ
⊢ (fun σ x => Equiv.sumCongr σ.1 σ.2) σ₁ h₁ = (fun σ x => Equiv.sumCongr σ.1 σ.2) σ₂ h₂ → σ₁ = σ₂ | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
| dsimp only | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ₁ σ₂ : Perm m × Perm n
h₁ : σ₁ ∈ univ
h₂ : σ₂ ∈ univ
⊢ Equiv.sumCongr σ₁.1 σ₁.2 = Equiv.sumCongr σ₂.1 σ₂.2 → σ₁ = σ₂ | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
| intro h | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ₁ σ₂ : Perm m × Perm n
h₁ : σ₁ ∈ univ
h₂ : σ₂ ∈ univ
h : Equiv.sumCongr σ₁.1 σ₁.2 = Equiv.sumCongr σ₂.1 σ₂.2
⊢ σ₁ = σ₂ | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
| have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ₁ σ₂ : Perm m × Perm n
h₁ : σ₁ ∈ univ
h₂ : σ₂ ∈ univ
h : Equiv.sumCongr σ₁.1 σ₁.2 = Equiv.sumCongr σ₂.1 σ₂.2
h2 : ∀ (x : m ⊕ n), (Perm.sumCongr σ₁.1 σ₁.2) x = (Perm.sumCongr σ₂.1 σ₂.2) x
⊢ σ₁ = σ₂ | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
| simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ₁ σ₂ : Perm m × Perm n
h₁ : σ₁ ∈ univ
h₂ : σ₂ ∈ univ
h : Equiv.sumCongr σ₁.1 σ₁.2 = Equiv.sumCongr σ₂.1 σ₂.2
h2 : (∀ (a : m), σ₁.1 a = σ₂.1 a) ∧ ∀ (b : n), σ₁.2 b = σ₂.2 b
⊢ σ₁ = σ₂ | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
| ext x | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case a.H
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ₁ σ₂ : Perm m × Perm n
h₁ : σ₁ ∈ univ
h₂ : σ₂ ∈ univ
h : Equiv.sumCongr σ₁.1 σ₁.2 = Equiv.sumCongr σ₂.1 σ₂.2
h2 : (∀ (a : m), σ₁.1 a = σ₂.1 a) ∧ ∀ (b : n), σ₁.2 b = σ₂.2 b
x : m
⊢ σ₁.1 x = σ₂.1 x | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· | exact h2.left x | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· | Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case a.H
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ₁ σ₂ : Perm m × Perm n
h₁ : σ₁ ∈ univ
h₂ : σ₂ ∈ univ
h : Equiv.sumCongr σ₁.1 σ₁.2 = Equiv.sumCongr σ₂.1 σ₂.2
h2 : (∀ (a : m), σ₁.1 a = σ₂.1 a) ∧ ∀ (b : n), σ₁.2 b = σ₂.2 b
x : n
⊢ σ₁.2 x = σ₂.2 x | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· | exact h2.right x | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· | Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
⊢ ∀ b ∈ Set.toFinset ↑(MonoidHom.range (sumCongrHom m n)),
∃ a, ∃ (ha : a ∈ univ), b = (fun σ x => Equiv.sumCongr σ.1 σ.2) a ha | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· | intro σ hσ | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· | Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ : m ⊕ n ≃ m ⊕ n
hσ : σ ∈ Set.toFinset ↑(MonoidHom.range (sumCongrHom m n))
⊢ ∃ a, ∃ (ha : a ∈ univ), σ = (fun σ x => Equiv.sumCongr σ.1 σ.2) a ha | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
| erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ : m ⊕ n ≃ m ⊕ n
hσ : ∃ x, (sumCongrHom m n) x = σ
⊢ ∃ a, ∃ (ha : a ∈ univ), σ = (fun σ x => Equiv.sumCongr σ.1 σ.2) a ha | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
| obtain ⟨σ₁₂, hσ₁₂⟩ := hσ | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case intro
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ : m ⊕ n ≃ m ⊕ n
σ₁₂ : Perm m × Perm n
hσ₁₂ : (sumCongrHom m n) σ₁₂ = σ
⊢ ∃ a, ∃ (ha : a ∈ univ), σ = (fun σ x => Equiv.sumCongr σ.1 σ.2) a ha | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
| use σ₁₂ | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case h
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ : m ⊕ n ≃ m ⊕ n
σ₁₂ : Perm m × Perm n
hσ₁₂ : (sumCongrHom m n) σ₁₂ = σ
⊢ ∃ (ha : σ₁₂ ∈ univ), σ = (fun σ x => Equiv.sumCongr σ.1 σ.2) σ₁₂ ha | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
| rw [← hσ₁₂] | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case h
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ : m ⊕ n ≃ m ⊕ n
σ₁₂ : Perm m × Perm n
hσ₁₂ : (sumCongrHom m n) σ₁₂ = σ
⊢ ∃ (ha : σ₁₂ ∈ univ), (sumCongrHom m n) σ₁₂ = (fun σ x => Equiv.sumCongr σ.1 σ.2) σ₁₂ ha | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
| simp | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case convert_2
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
⊢ ∀ x ∈ univ,
x ∉ Set.toFinset ↑(MonoidHom.range (sumCongrHom m n)) → ↑↑(sign x) * ∏ i : m ⊕ n, fromBlocks A B 0 D (x i) i = 0 | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· | rintro σ - hσn | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· | Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case convert_2
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ : Perm (m ⊕ n)
hσn : σ ∉ Set.toFinset ↑(MonoidHom.range (sumCongrHom m n))
⊢ ↑↑(sign σ) * ∏ i : m ⊕ n, fromBlocks A B 0 D (σ i) i = 0 | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
| have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ : Perm (m ⊕ n)
hσn : σ ∉ Set.toFinset ↑(MonoidHom.range (sumCongrHom m n))
⊢ ¬∀ (x : m), ∃ y, Sum.inl y = σ (Sum.inl x) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
| rw [Set.mem_toFinset] at hσn | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ : Perm (m ⊕ n)
hσn : σ ∉ ↑(MonoidHom.range (sumCongrHom m n))
⊢ ¬∀ (x : m), ∃ y, Sum.inl y = σ (Sum.inl x) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
| simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case convert_2
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ : Perm (m ⊕ n)
hσn : σ ∉ Set.toFinset ↑(MonoidHom.range (sumCongrHom m n))
h1 : ¬∀ (x : m), ∃ y, Sum.inl y = σ (Sum.inl x)
⊢ ↑↑(sign σ) * ∏ i : m ⊕ n, fromBlocks A B 0 D (σ i) i = 0 | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
| obtain ⟨a, ha⟩ := not_forall.mp h1 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case convert_2.intro
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ : Perm (m ⊕ n)
hσn : σ ∉ Set.toFinset ↑(MonoidHom.range (sumCongrHom m n))
h1 : ¬∀ (x : m), ∃ y, Sum.inl y = σ (Sum.inl x)
a : m
ha : ¬∃ y, Sum.inl y = σ (Sum.inl a)
⊢ ↑↑(sign σ) * ∏ i : m ⊕ n, fromBlocks A B 0 D (σ i) i = 0 | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
| cases' hx : σ (Sum.inl a) with a2 b | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case convert_2.intro.inl
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ : Perm (m ⊕ n)
hσn : σ ∉ Set.toFinset ↑(MonoidHom.range (sumCongrHom m n))
h1 : ¬∀ (x : m), ∃ y, Sum.inl y = σ (Sum.inl x)
a : m
ha : ¬∃ y, Sum.inl y = σ (Sum.inl a)
a2 : m
hx : σ (Sum.inl a) = Sum.inl a2
⊢ ↑↑(sign σ) * ∏ i : m ⊕ n, fromBlocks A B 0 D (σ i) i = 0 | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· | have hn := (not_exists.mp ha) a2 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· | Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case convert_2.intro.inl
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ : Perm (m ⊕ n)
hσn : σ ∉ Set.toFinset ↑(MonoidHom.range (sumCongrHom m n))
h1 : ¬∀ (x : m), ∃ y, Sum.inl y = σ (Sum.inl x)
a : m
ha : ¬∃ y, Sum.inl y = σ (Sum.inl a)
a2 : m
hx : σ (Sum.inl a) = Sum.inl a2
hn : ¬Sum.inl a2 = σ (Sum.inl a)
⊢ ↑↑(sign σ) * ∏ i : m ⊕ n, fromBlocks A B 0 D (σ i) i = 0 | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
| exact absurd hx.symm hn | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case convert_2.intro.inr
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ : Perm (m ⊕ n)
hσn : σ ∉ Set.toFinset ↑(MonoidHom.range (sumCongrHom m n))
h1 : ¬∀ (x : m), ∃ y, Sum.inl y = σ (Sum.inl x)
a : m
ha : ¬∃ y, Sum.inl y = σ (Sum.inl a)
b : n
hx : σ (Sum.inl a) = Sum.inr b
⊢ ↑↑(sign σ) * ∏ i : m ⊕ n, fromBlocks A B 0 D (σ i) i = 0 | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· | rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero] | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· | Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case convert_2.intro.inr
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
B : Matrix m n R
D : Matrix n n R
σ : Perm (m ⊕ n)
hσn : σ ∉ Set.toFinset ↑(MonoidHom.range (sumCongrHom m n))
h1 : ¬∀ (x : m), ∃ y, Sum.inl y = σ (Sum.inl x)
a : m
ha : ¬∃ y, Sum.inl y = σ (Sum.inl a)
b : n
hx : σ (Sum.inl a) = Sum.inr b
⊢ fromBlocks A B 0 D (σ (Sum.inl a)) (Sum.inl a) = 0 | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
| rw [hx, fromBlocks_apply₂₁, zero_apply] | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
| Mathlib.LinearAlgebra.Matrix.Determinant.643_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix m m R
C : Matrix n m R
D : Matrix n n R
⊢ det (fromBlocks A 0 C D) = det A * det D | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
| rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose] | /-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
| Mathlib.LinearAlgebra.Matrix.Determinant.699_0.U1f6HO8zRbnvZ95 | /-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
⊢ det A = ∑ i : Fin (Nat.succ n), (-1) ^ ↑i * A i 0 * det (submatrix A (Fin.succAbove i) Fin.succ) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
| rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
| Mathlib.LinearAlgebra.Matrix.Determinant.709_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
⊢ ∑ σ in Finset.map (Equiv.toEmbedding decomposeFin.symm) (univ ×ˢ univ), sign σ • ∏ i : Fin (Nat.succ n), A (σ i) i =
∑ i : Fin (Nat.succ n), (-1) ^ ↑i * A i 0 * det (submatrix A (Fin.succAbove i) Fin.succ) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
| simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
| Mathlib.LinearAlgebra.Matrix.Determinant.709_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
⊢ ∑ x : Fin (Nat.succ n),
∑ y : Perm (Fin n),
sign (decomposeFin.symm (x, y)) • ∏ x_1 : Fin (Nat.succ n), A ((decomposeFin.symm (x, y)) x_1) x_1 =
∑ x : Fin (Nat.succ n), (-1) ^ ↑x * A x 0 * det (of fun i j => A (Fin.succAbove x i) (Fin.succ j)) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
| refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
| Mathlib.LinearAlgebra.Matrix.Determinant.709_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) | Mathlib_LinearAlgebra_Matrix_Determinant |
case refine'_1
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
x✝ : i ∈ univ
⊢ ∑ y : Perm (Fin n), sign (decomposeFin.symm (0, y)) • ∏ x : Fin (Nat.succ n), A ((decomposeFin.symm (0, y)) x) x =
(-1) ^ ↑0 * A 0 0 * det (of fun i j => A (Fin.succAbove 0 i) (Fin.succ j)) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· | simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· | Mathlib.LinearAlgebra.Matrix.Determinant.709_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) | Mathlib_LinearAlgebra_Matrix_Determinant |
case refine'_2
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i✝ : Fin (Nat.succ n)
x✝ : i✝ ∈ univ
i : Fin n
⊢ ∑ y : Perm (Fin n),
sign (decomposeFin.symm (Fin.succ i, y)) • ∏ x : Fin (Nat.succ n), A ((decomposeFin.symm (Fin.succ i, y)) x) x =
(-1) ^ ↑(Fin.succ i) * A (Fin.succ i) 0 * det (of fun i_1 j => A (Fin.succAbove (Fin.succ i) i_1) (Fin.succ j)) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
| have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
| Mathlib.LinearAlgebra.Matrix.Determinant.709_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i✝ : Fin (Nat.succ n)
x✝ : i✝ ∈ univ
i : Fin n
⊢ (-1) ^ ↑i = ↑↑(sign (Fin.cycleRange i)) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by | simp [Fin.sign_cycleRange] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by | Mathlib.LinearAlgebra.Matrix.Determinant.709_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) | Mathlib_LinearAlgebra_Matrix_Determinant |
case refine'_2
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i✝ : Fin (Nat.succ n)
x✝ : i✝ ∈ univ
i : Fin n
this : (-1) ^ ↑i = ↑↑(sign (Fin.cycleRange i))
⊢ ∑ y : Perm (Fin n),
sign (decomposeFin.symm (Fin.succ i, y)) • ∏ x : Fin (Nat.succ n), A ((decomposeFin.symm (Fin.succ i, y)) x) x =
(-1) ^ ↑(Fin.succ i) * A (Fin.succ i) 0 * det (of fun i_1 j => A (Fin.succAbove (Fin.succ i) i_1) (Fin.succ j)) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
| rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
| Mathlib.LinearAlgebra.Matrix.Determinant.709_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) | Mathlib_LinearAlgebra_Matrix_Determinant |
case refine'_2
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i✝ : Fin (Nat.succ n)
x✝ : i✝ ∈ univ
i : Fin n
this : (-1) ^ ↑i = ↑↑(sign (Fin.cycleRange i))
⊢ ∑ y : Perm (Fin n),
sign (decomposeFin.symm (Fin.succ i, y)) • ∏ x : Fin (Nat.succ n), A ((decomposeFin.symm (Fin.succ i, y)) x) x =
∑ x : Perm (Fin n),
-1 *
(A (Fin.succ i) 0 *
sign x •
∏ i_1 : Fin n,
of (fun i_2 j => A (Fin.succAbove (Fin.succ i) i_2) (Fin.succ j)) ((Fin.cycleRange i) (x i_1)) i_1) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
| refine' Finset.sum_congr rfl fun σ _ => _ | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
| Mathlib.LinearAlgebra.Matrix.Determinant.709_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) | Mathlib_LinearAlgebra_Matrix_Determinant |
case refine'_2
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i✝ : Fin (Nat.succ n)
x✝¹ : i✝ ∈ univ
i : Fin n
this : (-1) ^ ↑i = ↑↑(sign (Fin.cycleRange i))
σ : Perm (Fin n)
x✝ : σ ∈ univ
⊢ sign (decomposeFin.symm (Fin.succ i, σ)) • ∏ x : Fin (Nat.succ n), A ((decomposeFin.symm (Fin.succ i, σ)) x) x =
-1 *
(A (Fin.succ i) 0 *
sign σ •
∏ i_1 : Fin n,
of (fun i_2 j => A (Fin.succAbove (Fin.succ i) i_2) (Fin.succ j)) ((Fin.cycleRange i) (σ i_1)) i_1) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
| rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
| Mathlib.LinearAlgebra.Matrix.Determinant.709_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) | Mathlib_LinearAlgebra_Matrix_Determinant |
case refine'_2
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i✝ : Fin (Nat.succ n)
x✝¹ : i✝ ∈ univ
i : Fin n
this : (-1) ^ ↑i = ↑↑(sign (Fin.cycleRange i))
σ : Perm (Fin n)
x✝ : σ ∈ univ
⊢ (-1 * sign σ) • ∏ x : Fin (Nat.succ n), A ((decomposeFin.symm (Fin.succ i, σ)) x) x =
-1 *
(A (Fin.succ i) 0 *
sign σ •
∏ i_1 : Fin n,
of (fun i_2 j => A (Fin.succAbove (Fin.succ i) i_2) (Fin.succ j)) ((Fin.cycleRange i) (σ i_1)) i_1) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
| calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
| Mathlib.LinearAlgebra.Matrix.Determinant.709_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i✝ : Fin (Nat.succ n)
x✝¹ : i✝ ∈ univ
i : Fin n
this : (-1) ^ ↑i = ↑↑(sign (Fin.cycleRange i))
σ : Perm (Fin n)
x✝ : σ ∈ univ
⊢ (-1 * ↑(sign σ)) • ∏ i' : Fin (Nat.succ n), A ((decomposeFin.symm (Fin.succ i, σ)) i') i' =
(-1 * ↑(sign σ)) •
(A (Fin.succ i) 0 * ∏ i' : Fin n, A (Fin.succAbove (Fin.succ i) ((Fin.cycleRange i) (σ i'))) (Fin.succ i')) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
| simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
| Mathlib.LinearAlgebra.Matrix.Determinant.709_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i✝ : Fin (Nat.succ n)
x✝¹ : i✝ ∈ univ
i : Fin n
this : (-1) ^ ↑i = ↑↑(sign (Fin.cycleRange i))
σ : Perm (Fin n)
x✝ : σ ∈ univ
⊢ (-1 * ↑(sign σ)) •
(A (Fin.succ i) 0 * ∏ i' : Fin n, A (Fin.succAbove (Fin.succ i) ((Fin.cycleRange i) (σ i'))) (Fin.succ i')) =
-1 *
(A (Fin.succ i) 0 *
↑(sign σ) • ∏ i' : Fin n, A (Fin.succAbove (Fin.succ i) ((Fin.cycleRange i) (σ i'))) (Fin.succ i')) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
| simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
| Mathlib.LinearAlgebra.Matrix.Determinant.709_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
⊢ det A = ∑ j : Fin (Nat.succ n), (-1) ^ ↑j * A 0 j * det (submatrix A Fin.succ (Fin.succAbove j)) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
| rw [← det_transpose A, det_succ_column_zero] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
| Mathlib.LinearAlgebra.Matrix.Determinant.741_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
⊢ ∑ i : Fin (Nat.succ n), (-1) ^ ↑i * Aᵀ i 0 * det (submatrix Aᵀ (Fin.succAbove i) Fin.succ) =
∑ j : Fin (Nat.succ n), (-1) ^ ↑j * A 0 j * det (submatrix A Fin.succ (Fin.succAbove j)) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
| refine' Finset.sum_congr rfl fun i _ => _ | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
| Mathlib.LinearAlgebra.Matrix.Determinant.741_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
x✝ : i ∈ univ
⊢ (-1) ^ ↑i * Aᵀ i 0 * det (submatrix Aᵀ (Fin.succAbove i) Fin.succ) =
(-1) ^ ↑i * A 0 i * det (submatrix A Fin.succ (Fin.succAbove i)) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
| rw [← det_transpose] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
| Mathlib.LinearAlgebra.Matrix.Determinant.741_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
x✝ : i ∈ univ
⊢ (-1) ^ ↑i * Aᵀ i 0 * det (submatrix Aᵀ (Fin.succAbove i) Fin.succ)ᵀ =
(-1) ^ ↑i * A 0 i * det (submatrix A Fin.succ (Fin.succAbove i)) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
| simp only [transpose_apply, transpose_submatrix, transpose_transpose] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
| Mathlib.LinearAlgebra.Matrix.Determinant.741_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
⊢ det A = ∑ j : Fin (Nat.succ n), (-1) ^ (↑i + ↑j) * A i j * det (submatrix A (Fin.succAbove i) (Fin.succAbove j)) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
| simp_rw [pow_add, mul_assoc, ← mul_sum] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
| Mathlib.LinearAlgebra.Matrix.Determinant.750_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
⊢ det A =
(-1) ^ ↑i * ∑ x : Fin (Nat.succ n), (-1) ^ ↑x * (A i x * det (submatrix A (Fin.succAbove i) (Fin.succAbove x))) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
| have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
| Mathlib.LinearAlgebra.Matrix.Determinant.750_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
⊢ det A = (-1) ^ ↑i * ↑↑(sign (Fin.cycleRange i)⁻¹) * det A | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
| calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
| Mathlib.LinearAlgebra.Matrix.Determinant.750_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
⊢ det A = ↑↑((-1) ^ ↑i * (-1) ^ ↑i) * det A | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by | simp | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by | Mathlib.LinearAlgebra.Matrix.Determinant.750_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
⊢ ↑↑((-1) ^ ↑i * (-1) ^ ↑i) * det A = (-1) ^ ↑i * ↑↑(sign (Fin.cycleRange i)⁻¹) * det A | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by | simp [-Int.units_mul_self] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by | Mathlib.LinearAlgebra.Matrix.Determinant.750_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
this : det A = (-1) ^ ↑i * ↑↑(sign (Fin.cycleRange i)⁻¹) * det A
⊢ det A =
(-1) ^ ↑i * ∑ x : Fin (Nat.succ n), (-1) ^ ↑x * (A i x * det (submatrix A (Fin.succAbove i) (Fin.succAbove x))) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
| rw [this, mul_assoc] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
| Mathlib.LinearAlgebra.Matrix.Determinant.750_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
this : det A = (-1) ^ ↑i * ↑↑(sign (Fin.cycleRange i)⁻¹) * det A
⊢ (-1) ^ ↑i * (↑↑(sign (Fin.cycleRange i)⁻¹) * det A) =
(-1) ^ ↑i * ∑ x : Fin (Nat.succ n), (-1) ^ ↑x * (A i x * det (submatrix A (Fin.succAbove i) (Fin.succAbove x))) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
| congr | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
| Mathlib.LinearAlgebra.Matrix.Determinant.750_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
case e_a
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
this : det A = (-1) ^ ↑i * ↑↑(sign (Fin.cycleRange i)⁻¹) * det A
⊢ ↑↑(sign (Fin.cycleRange i)⁻¹) * det A =
∑ x : Fin (Nat.succ n), (-1) ^ ↑x * (A i x * det (submatrix A (Fin.succAbove i) (Fin.succAbove x))) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
| rw [← det_permute, det_succ_row_zero] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
| Mathlib.LinearAlgebra.Matrix.Determinant.750_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
case e_a
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
this : det A = (-1) ^ ↑i * ↑↑(sign (Fin.cycleRange i)⁻¹) * det A
⊢ ∑ j : Fin (Nat.succ n),
(-1) ^ ↑j * A ((Fin.cycleRange i)⁻¹ 0) j *
det (submatrix (fun i_1 => A ((Fin.cycleRange i)⁻¹ i_1)) Fin.succ (Fin.succAbove j)) =
∑ x : Fin (Nat.succ n), (-1) ^ ↑x * (A i x * det (submatrix A (Fin.succAbove i) (Fin.succAbove x))) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
| refine' Finset.sum_congr rfl fun j _ => _ | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
| Mathlib.LinearAlgebra.Matrix.Determinant.750_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
case e_a
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
this : det A = (-1) ^ ↑i * ↑↑(sign (Fin.cycleRange i)⁻¹) * det A
j : Fin (Nat.succ n)
x✝ : j ∈ univ
⊢ (-1) ^ ↑j * A ((Fin.cycleRange i)⁻¹ 0) j *
det (submatrix (fun i_1 => A ((Fin.cycleRange i)⁻¹ i_1)) Fin.succ (Fin.succAbove j)) =
(-1) ^ ↑j * (A i j * det (submatrix A (Fin.succAbove i) (Fin.succAbove j))) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
| rw [mul_assoc, Matrix.submatrix, Matrix.submatrix] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
| Mathlib.LinearAlgebra.Matrix.Determinant.750_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
case e_a
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
this : det A = (-1) ^ ↑i * ↑↑(sign (Fin.cycleRange i)⁻¹) * det A
j : Fin (Nat.succ n)
x✝ : j ∈ univ
⊢ (-1) ^ ↑j *
(A ((Fin.cycleRange i)⁻¹ 0) j *
det (of fun i_1 j_1 => A ((Fin.cycleRange i)⁻¹ (Fin.succ i_1)) (Fin.succAbove j j_1))) =
(-1) ^ ↑j * (A i j * det (of fun i_1 j_1 => A (Fin.succAbove i i_1) (Fin.succAbove j j_1))) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
| congr | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
| Mathlib.LinearAlgebra.Matrix.Determinant.750_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
case e_a.e_a.e_a.e_a
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
this : det A = (-1) ^ ↑i * ↑↑(sign (Fin.cycleRange i)⁻¹) * det A
j : Fin (Nat.succ n)
x✝ : j ∈ univ
⊢ (Fin.cycleRange i)⁻¹ 0 = i | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
congr
· | rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_zero] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
congr
· | Mathlib.LinearAlgebra.Matrix.Determinant.750_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
case e_a.e_a.e_a.e_M.h.e_6.h
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
this : det A = (-1) ^ ↑i * ↑↑(sign (Fin.cycleRange i)⁻¹) * det A
j : Fin (Nat.succ n)
x✝ : j ∈ univ
⊢ (fun i_1 j_1 => A ((Fin.cycleRange i)⁻¹ (Fin.succ i_1)) (Fin.succAbove j j_1)) = fun i_1 j_1 =>
A (Fin.succAbove i i_1) (Fin.succAbove j j_1) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
congr
· rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_zero]
· | ext i' j' | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
congr
· rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_zero]
· | Mathlib.LinearAlgebra.Matrix.Determinant.750_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
case e_a.e_a.e_a.e_M.h.e_6.h.h.h
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
i : Fin (Nat.succ n)
this : det A = (-1) ^ ↑i * ↑↑(sign (Fin.cycleRange i)⁻¹) * det A
j : Fin (Nat.succ n)
x✝ : j ∈ univ
i' j' : Fin n
⊢ A ((Fin.cycleRange i)⁻¹ (Fin.succ i')) (Fin.succAbove j j') = A (Fin.succAbove i i') (Fin.succAbove j j') | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
congr
· rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_zero]
· ext i' j'
| rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_succ] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
congr
· rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_zero]
· ext i' j'
| Mathlib.LinearAlgebra.Matrix.Determinant.750_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
j : Fin (Nat.succ n)
⊢ det A = ∑ i : Fin (Nat.succ n), (-1) ^ (↑i + ↑j) * A i j * det (submatrix A (Fin.succAbove i) (Fin.succAbove j)) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
congr
· rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_zero]
· ext i' j'
rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_succ]
#align matrix.det_succ_row Matrix.det_succ_row
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column `j`. -/
theorem det_succ_column {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (j : Fin n.succ) :
det A =
∑ i : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
| rw [← det_transpose, det_succ_row _ j] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column `j`. -/
theorem det_succ_column {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (j : Fin n.succ) :
det A =
∑ i : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
| Mathlib.LinearAlgebra.Matrix.Determinant.770_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column `j`. -/
theorem det_succ_column {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (j : Fin n.succ) :
det A =
∑ i : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
j : Fin (Nat.succ n)
⊢ ∑ j_1 : Fin (Nat.succ n), (-1) ^ (↑j + ↑j_1) * Aᵀ j j_1 * det (submatrix Aᵀ (Fin.succAbove j) (Fin.succAbove j_1)) =
∑ i : Fin (Nat.succ n), (-1) ^ (↑i + ↑j) * A i j * det (submatrix A (Fin.succAbove i) (Fin.succAbove j)) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
congr
· rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_zero]
· ext i' j'
rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_succ]
#align matrix.det_succ_row Matrix.det_succ_row
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column `j`. -/
theorem det_succ_column {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (j : Fin n.succ) :
det A =
∑ i : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
rw [← det_transpose, det_succ_row _ j]
| refine' Finset.sum_congr rfl fun i _ => _ | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column `j`. -/
theorem det_succ_column {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (j : Fin n.succ) :
det A =
∑ i : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
rw [← det_transpose, det_succ_row _ j]
| Mathlib.LinearAlgebra.Matrix.Determinant.770_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column `j`. -/
theorem det_succ_column {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (j : Fin n.succ) :
det A =
∑ i : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n✝ : Type u_2
inst✝⁴ : DecidableEq n✝
inst✝³ : Fintype n✝
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
n : ℕ
A : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
j i : Fin (Nat.succ n)
x✝ : i ∈ univ
⊢ (-1) ^ (↑j + ↑i) * Aᵀ j i * det (submatrix Aᵀ (Fin.succAbove j) (Fin.succAbove i)) =
(-1) ^ (↑i + ↑j) * A i j * det (submatrix A (Fin.succAbove i) (Fin.succAbove j)) | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
congr
· rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_zero]
· ext i' j'
rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_succ]
#align matrix.det_succ_row Matrix.det_succ_row
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column `j`. -/
theorem det_succ_column {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (j : Fin n.succ) :
det A =
∑ i : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
rw [← det_transpose, det_succ_row _ j]
refine' Finset.sum_congr rfl fun i _ => _
| rw [add_comm, ← det_transpose, transpose_apply, transpose_submatrix, transpose_transpose] | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column `j`. -/
theorem det_succ_column {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (j : Fin n.succ) :
det A =
∑ i : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
rw [← det_transpose, det_succ_row _ j]
refine' Finset.sum_congr rfl fun i _ => _
| Mathlib.LinearAlgebra.Matrix.Determinant.770_0.U1f6HO8zRbnvZ95 | /-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column `j`. -/
theorem det_succ_column {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (j : Fin n.succ) :
det A =
∑ i : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix (Fin 2) (Fin 2) R
⊢ det A = A 0 0 * A 1 1 - A 0 1 * A 1 0 | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
congr
· rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_zero]
· ext i' j'
rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_succ]
#align matrix.det_succ_row Matrix.det_succ_row
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column `j`. -/
theorem det_succ_column {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (j : Fin n.succ) :
det A =
∑ i : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
rw [← det_transpose, det_succ_row _ j]
refine' Finset.sum_congr rfl fun i _ => _
rw [add_comm, ← det_transpose, transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_column Matrix.det_succ_column
/-- Determinant of 0x0 matrix -/
@[simp]
theorem det_fin_zero {A : Matrix (Fin 0) (Fin 0) R} : det A = 1 :=
det_isEmpty
#align matrix.det_fin_zero Matrix.det_fin_zero
/-- Determinant of 1x1 matrix -/
theorem det_fin_one (A : Matrix (Fin 1) (Fin 1) R) : det A = A 0 0 :=
det_unique A
#align matrix.det_fin_one Matrix.det_fin_one
theorem det_fin_one_of (a : R) : det !![a] = a :=
det_fin_one _
#align matrix.det_fin_one_of Matrix.det_fin_one_of
/-- Determinant of 2x2 matrix -/
theorem det_fin_two (A : Matrix (Fin 2) (Fin 2) R) : det A = A 0 0 * A 1 1 - A 0 1 * A 1 0 := by
| simp only [det_succ_row_zero, det_unique, Fin.default_eq_zero, submatrix_apply,
Fin.succ_zero_eq_one, Fin.sum_univ_succ, Fin.val_zero, Fin.zero_succAbove, univ_unique,
Fin.val_succ, Fin.coe_fin_one, Fin.succ_succAbove_zero, sum_singleton] | /-- Determinant of 2x2 matrix -/
theorem det_fin_two (A : Matrix (Fin 2) (Fin 2) R) : det A = A 0 0 * A 1 1 - A 0 1 * A 1 0 := by
| Mathlib.LinearAlgebra.Matrix.Determinant.794_0.U1f6HO8zRbnvZ95 | /-- Determinant of 2x2 matrix -/
theorem det_fin_two (A : Matrix (Fin 2) (Fin 2) R) : det A = A 0 0 * A 1 1 - A 0 1 * A 1 0 | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix (Fin 2) (Fin 2) R
⊢ (-1) ^ 0 * A 0 0 * A 1 1 + (-1) ^ (0 + 1) * A 0 1 * A 1 0 = A 0 0 * A 1 1 - A 0 1 * A 1 0 | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
congr
· rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_zero]
· ext i' j'
rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_succ]
#align matrix.det_succ_row Matrix.det_succ_row
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column `j`. -/
theorem det_succ_column {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (j : Fin n.succ) :
det A =
∑ i : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
rw [← det_transpose, det_succ_row _ j]
refine' Finset.sum_congr rfl fun i _ => _
rw [add_comm, ← det_transpose, transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_column Matrix.det_succ_column
/-- Determinant of 0x0 matrix -/
@[simp]
theorem det_fin_zero {A : Matrix (Fin 0) (Fin 0) R} : det A = 1 :=
det_isEmpty
#align matrix.det_fin_zero Matrix.det_fin_zero
/-- Determinant of 1x1 matrix -/
theorem det_fin_one (A : Matrix (Fin 1) (Fin 1) R) : det A = A 0 0 :=
det_unique A
#align matrix.det_fin_one Matrix.det_fin_one
theorem det_fin_one_of (a : R) : det !![a] = a :=
det_fin_one _
#align matrix.det_fin_one_of Matrix.det_fin_one_of
/-- Determinant of 2x2 matrix -/
theorem det_fin_two (A : Matrix (Fin 2) (Fin 2) R) : det A = A 0 0 * A 1 1 - A 0 1 * A 1 0 := by
simp only [det_succ_row_zero, det_unique, Fin.default_eq_zero, submatrix_apply,
Fin.succ_zero_eq_one, Fin.sum_univ_succ, Fin.val_zero, Fin.zero_succAbove, univ_unique,
Fin.val_succ, Fin.coe_fin_one, Fin.succ_succAbove_zero, sum_singleton]
| ring | /-- Determinant of 2x2 matrix -/
theorem det_fin_two (A : Matrix (Fin 2) (Fin 2) R) : det A = A 0 0 * A 1 1 - A 0 1 * A 1 0 := by
simp only [det_succ_row_zero, det_unique, Fin.default_eq_zero, submatrix_apply,
Fin.succ_zero_eq_one, Fin.sum_univ_succ, Fin.val_zero, Fin.zero_succAbove, univ_unique,
Fin.val_succ, Fin.coe_fin_one, Fin.succ_succAbove_zero, sum_singleton]
| Mathlib.LinearAlgebra.Matrix.Determinant.794_0.U1f6HO8zRbnvZ95 | /-- Determinant of 2x2 matrix -/
theorem det_fin_two (A : Matrix (Fin 2) (Fin 2) R) : det A = A 0 0 * A 1 1 - A 0 1 * A 1 0 | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix (Fin 3) (Fin 3) R
⊢ det A =
A 0 0 * A 1 1 * A 2 2 - A 0 0 * A 1 2 * A 2 1 - A 0 1 * A 1 0 * A 2 2 + A 0 1 * A 1 2 * A 2 0 +
A 0 2 * A 1 0 * A 2 1 -
A 0 2 * A 1 1 * A 2 0 | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
congr
· rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_zero]
· ext i' j'
rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_succ]
#align matrix.det_succ_row Matrix.det_succ_row
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column `j`. -/
theorem det_succ_column {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (j : Fin n.succ) :
det A =
∑ i : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
rw [← det_transpose, det_succ_row _ j]
refine' Finset.sum_congr rfl fun i _ => _
rw [add_comm, ← det_transpose, transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_column Matrix.det_succ_column
/-- Determinant of 0x0 matrix -/
@[simp]
theorem det_fin_zero {A : Matrix (Fin 0) (Fin 0) R} : det A = 1 :=
det_isEmpty
#align matrix.det_fin_zero Matrix.det_fin_zero
/-- Determinant of 1x1 matrix -/
theorem det_fin_one (A : Matrix (Fin 1) (Fin 1) R) : det A = A 0 0 :=
det_unique A
#align matrix.det_fin_one Matrix.det_fin_one
theorem det_fin_one_of (a : R) : det !![a] = a :=
det_fin_one _
#align matrix.det_fin_one_of Matrix.det_fin_one_of
/-- Determinant of 2x2 matrix -/
theorem det_fin_two (A : Matrix (Fin 2) (Fin 2) R) : det A = A 0 0 * A 1 1 - A 0 1 * A 1 0 := by
simp only [det_succ_row_zero, det_unique, Fin.default_eq_zero, submatrix_apply,
Fin.succ_zero_eq_one, Fin.sum_univ_succ, Fin.val_zero, Fin.zero_succAbove, univ_unique,
Fin.val_succ, Fin.coe_fin_one, Fin.succ_succAbove_zero, sum_singleton]
ring
#align matrix.det_fin_two Matrix.det_fin_two
@[simp]
theorem det_fin_two_of (a b c d : R) : Matrix.det !![a, b; c, d] = a * d - b * c :=
det_fin_two _
#align matrix.det_fin_two_of Matrix.det_fin_two_of
/-- Determinant of 3x3 matrix -/
theorem det_fin_three (A : Matrix (Fin 3) (Fin 3) R) :
det A =
A 0 0 * A 1 1 * A 2 2 - A 0 0 * A 1 2 * A 2 1
- A 0 1 * A 1 0 * A 2 2 + A 0 1 * A 1 2 * A 2 0
+ A 0 2 * A 1 0 * A 2 1 - A 0 2 * A 1 1 * A 2 0 := by
| simp only [det_succ_row_zero, Nat.odd_iff_not_even, submatrix_apply, Fin.succ_zero_eq_one,
submatrix_submatrix, det_unique, Fin.default_eq_zero, comp_apply, Fin.succ_one_eq_two,
Fin.sum_univ_succ, Fin.val_zero, Fin.zero_succAbove, univ_unique, Fin.val_succ,
Fin.coe_fin_one, Fin.succ_succAbove_zero, sum_singleton, Fin.succ_succAbove_one, even_add_self] | /-- Determinant of 3x3 matrix -/
theorem det_fin_three (A : Matrix (Fin 3) (Fin 3) R) :
det A =
A 0 0 * A 1 1 * A 2 2 - A 0 0 * A 1 2 * A 2 1
- A 0 1 * A 1 0 * A 2 2 + A 0 1 * A 1 2 * A 2 0
+ A 0 2 * A 1 0 * A 2 1 - A 0 2 * A 1 1 * A 2 0 := by
| Mathlib.LinearAlgebra.Matrix.Determinant.807_0.U1f6HO8zRbnvZ95 | /-- Determinant of 3x3 matrix -/
theorem det_fin_three (A : Matrix (Fin 3) (Fin 3) R) :
det A =
A 0 0 * A 1 1 * A 2 2 - A 0 0 * A 1 2 * A 2 1
- A 0 1 * A 1 0 * A 2 2 + A 0 1 * A 1 2 * A 2 0
+ A 0 2 * A 1 0 * A 2 1 - A 0 2 * A 1 1 * A 2 0 | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁴ : DecidableEq n
inst✝³ : Fintype n
inst✝² : DecidableEq m
inst✝¹ : Fintype m
R : Type v
inst✝ : CommRing R
A : Matrix (Fin 3) (Fin 3) R
⊢ (-1) ^ 0 * A 0 0 * ((-1) ^ 0 * A 1 1 * A 2 2 + (-1) ^ (0 + 1) * A 1 2 * A 2 1) +
((-1) ^ (0 + 1) * A 0 1 * ((-1) ^ 0 * A 1 0 * A 2 2 + (-1) ^ (0 + 1) * A 1 2 * A 2 0) +
(-1) ^ (0 + 1 + 1) * A 0 2 * ((-1) ^ 0 * A 1 0 * A 2 1 + (-1) ^ (0 + 1) * A 1 1 * A 2 0)) =
A 0 0 * A 1 1 * A 2 2 - A 0 0 * A 1 2 * A 2 1 - A 0 1 * A 1 0 * A 2 2 + A 0 1 * A 1 2 * A 2 0 +
A 0 2 * A 1 0 * A 2 1 -
A 0 2 * A 1 1 * A 2 0 | /-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.PEquiv
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.GroupTheory.Perm.Sign
import Mathlib.Algebra.Algebra.Basic
import Mathlib.Tactic.Ring
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Pi
#align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395"
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`test/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
open Matrix BigOperators
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
-- mathport name: «exprε »
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [Λ^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
#align matrix.det_row_alternating Matrix.detRowAlternating
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
#align matrix.det Matrix.det
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
#align matrix.det_apply Matrix.det_apply
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
#align matrix.det_apply' Matrix.det_apply'
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine' (Finset.sum_eq_single 1 _ _).trans _
· rintro σ - h2
cases' not_forall.1 (mt Equiv.ext h2) with x h3
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
#align matrix.det_diagonal Matrix.det_diagonal
-- @[simp] -- Porting note: simp can prove this
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_zero
#align matrix.det_zero Matrix.det_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
#align matrix.det_one Matrix.det_one
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
#align matrix.det_is_empty Matrix.det_isEmpty
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
#align matrix.coe_det_is_empty Matrix.coe_det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
#align matrix.det_eq_one_of_card_eq_zero Matrix.det_eq_one_of_card_eq_zero
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
#align matrix.det_unique Matrix.det_unique
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
#align matrix.det_eq_elem_of_subsingleton Matrix.det_eq_elem_of_subsingleton
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
#align matrix.det_eq_elem_of_card_eq_one Matrix.det_eq_elem_of_card_eq_one
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
#align matrix.det_mul_aux Matrix.det_mul_aux
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ =
∑ p in (@univ (n → n) _).filter Bijective,
∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i :=
(Eq.symm <|
sum_subset (filter_subset _ _) fun f _ hbij =>
det_mul_aux <| by simpa only [true_and_iff, mem_filter, mem_univ] using hbij)
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
(sum_bij (fun p h => Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ => mem_univ _)
(fun _ _ => rfl) (fun _ _ _ _ h => by injection h) fun b _ =>
⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩)
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
#align matrix.det_mul Matrix.det_mul
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
#align matrix.det_monoid_hom Matrix.detMonoidHom
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
#align matrix.coe_det_monoid_hom Matrix.coe_detMonoidHom
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
#align matrix.det_mul_comm Matrix.det_mul_comm
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
#align matrix.det_mul_left_comm Matrix.det_mul_left_comm
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
#align matrix.det_mul_right_comm Matrix.det_mul_right_comm
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
#align matrix.det_units_conj Matrix.det_units_conj
-- TODO(mathlib4#6607): fix elaboration so that the ascription isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((↑M⁻¹ : Matrix _ _ _) * N * (↑M : Matrix _ _ _)) = det N :=
det_units_conj M⁻¹ N
#align matrix.det_units_conj' Matrix.det_units_conj'
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine' Fintype.sum_bijective _ inv_involutive.bijective _ _ _
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
intros
simp
#align matrix.det_transpose Matrix.det_transpose
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(Matrix.det fun i => M (σ i)) = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
#align matrix.det_permute Matrix.det_permute
/-- Permuting rows and columns with the same equivalence has no effect. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
#align matrix.det_submatrix_equiv_self Matrix.det_submatrix_equiv_self
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
#align matrix.det_reindex_self Matrix.det_reindex_self
/-- The determinant of a permutation matrix equals its sign. -/
@[simp]
theorem det_permutation (σ : Perm n) :
Matrix.det (σ.toPEquiv.toMatrix : Matrix n n R) = Perm.sign σ := by
rw [← Matrix.mul_one (σ.toPEquiv.toMatrix : Matrix n n R), PEquiv.toPEquiv_mul_matrix,
det_permute, det_one, mul_one]
#align matrix.det_permutation Matrix.det_permutation
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := (det_mul _ _)
_ = c ^ Fintype.card n * det A := by simp [card_univ]
#align matrix.det_smul Matrix.det_smul
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [DistribMulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) : det (c • A) = c ^ Fintype.card n • det A :=
by rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
#align matrix.det_smul_of_tower Matrix.det_smul_of_tower
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
#align matrix.det_neg Matrix.det_neg
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) : det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A :=
by rw [← det_smul_of_tower, Units.neg_smul, one_smul]
#align matrix.det_neg_eq_smul Matrix.det_neg_eq_smul
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
#align matrix.det_mul_row Matrix.det_mul_row
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
#align matrix.det_mul_column Matrix.det_mul_column
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
#align matrix.det_pow Matrix.det_pow
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by simp [Matrix.det_apply', f.map_sum, f.map_prod]
#align ring_hom.map_det RingHom.map_det
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align ring_equiv.map_det RingEquiv.map_det
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
#align alg_hom.map_det AlgHom.map_det
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
#align alg_equiv.map_det AlgEquiv.map_det
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
#align matrix.det_conj_transpose Matrix.det_conjTranspose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_coord_zero i (funext h)
#align matrix.det_eq_zero_of_row_eq_zero Matrix.det_eq_zero_of_row_eq_zero
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
#align matrix.det_eq_zero_of_column_eq_zero Matrix.det_eq_zero_of_column_eq_zero
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
#align matrix.det_zero_of_row_eq Matrix.det_zero_of_row_eq
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
#align matrix.det_zero_of_column_eq Matrix.det_zero_of_column_eq
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_add M j u v
#align matrix.det_update_row_add Matrix.det_updateRow_add
theorem det_updateColumn_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateColumn M j <| u + v) = det (updateColumn M j u) + det (updateColumn M j v) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_add]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_add Matrix.det_updateColumn_add
theorem det_updateRow_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow M j <| s • u) = s * det (updateRow M j u) :=
(detRowAlternating : (n → R) [Λ^n]→ₗ[R] R).map_smul M j s u
#align matrix.det_update_row_smul Matrix.det_updateRow_smul
theorem det_updateColumn_smul (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn M j <| s • u) = s * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, det_updateRow_smul]
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul Matrix.det_updateColumn_smul
theorem det_updateRow_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateRow (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateRow M j u) :=
MultilinearMap.map_update_smul _ M j s u
#align matrix.det_update_row_smul' Matrix.det_updateRow_smul'
theorem det_updateColumn_smul' (M : Matrix n n R) (j : n) (s : R) (u : n → R) :
det (updateColumn (s • M) j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) := by
rw [← det_transpose, ← updateRow_transpose, transpose_smul, det_updateRow_smul']
simp [updateRow_transpose, det_transpose]
#align matrix.det_update_column_smul' Matrix.det_updateColumn_smul'
section DetEq
/-! ### `det_eq` section
Lemmas showing the determinant is invariant under a variety of operations.
-/
theorem det_eq_of_eq_mul_det_one {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = B * C) : det A = det B :=
calc
det A = det (B * C) := congr_arg _ hA
_ = det B * det C := (det_mul _ _)
_ = det B := by rw [hC, mul_one]
#align matrix.det_eq_of_eq_mul_det_one Matrix.det_eq_of_eq_mul_det_one
theorem det_eq_of_eq_det_one_mul {A B : Matrix n n R} (C : Matrix n n R) (hC : det C = 1)
(hA : A = C * B) : det A = det B :=
calc
det A = det (C * B) := congr_arg _ hA
_ = det C * det B := (det_mul _ _)
_ = det B := by rw [hC, one_mul]
#align matrix.det_eq_of_eq_det_one_mul Matrix.det_eq_of_eq_det_one_mul
theorem det_updateRow_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateRow A i (A i + A j)) = det A := by
simp [det_updateRow_add,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_self Matrix.det_updateRow_add_self
theorem det_updateColumn_add_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) :
det (updateColumn A i fun k => A k i + A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_self Aᵀ hij
#align matrix.det_update_column_add_self Matrix.det_updateColumn_add_self
theorem det_updateRow_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateRow A i (A i + c • A j)) = det A := by
simp [det_updateRow_add, det_updateRow_smul,
det_zero_of_row_eq hij (updateRow_self.trans (updateRow_ne hij.symm).symm)]
#align matrix.det_update_row_add_smul_self Matrix.det_updateRow_add_smul_self
theorem det_updateColumn_add_smul_self (A : Matrix n n R) {i j : n} (hij : i ≠ j) (c : R) :
det (updateColumn A i fun k => A k i + c • A k j) = det A := by
rw [← det_transpose, ← updateRow_transpose, ← det_transpose A]
exact det_updateRow_add_smul_self Aᵀ hij c
#align matrix.det_update_column_add_smul_self Matrix.det_updateColumn_add_smul_self
theorem det_eq_of_forall_row_eq_smul_add_const_aux {A B : Matrix n n R} {s : Finset n} :
∀ (c : n → R) (_ : ∀ i, i ∉ s → c i = 0) (k : n) (_ : k ∉ s)
(_: ∀ i j, A i j = B i j + c i * B k j), det A = det B := by
induction s using Finset.induction_on generalizing B with
| empty =>
rintro c hs k - A_eq
have : ∀ i, c i = 0 := by
intro i
specialize hs i
contrapose! hs
simp [hs]
congr
ext i j
rw [A_eq, this, zero_mul, add_zero]
| @insert i s _hi ih =>
intro c hs k hk A_eq
have hAi : A i = B i + c i • B k := funext (A_eq i)
rw [@ih (updateRow B i (A i)) (Function.update c i 0), hAi, det_updateRow_add_smul_self]
· exact mt (fun h => show k ∈ insert i s from h ▸ Finset.mem_insert_self _ _) hk
· intro i' hi'
rw [Function.update_apply]
split_ifs with hi'i
· rfl
· exact hs i' fun h => hi' ((Finset.mem_insert.mp h).resolve_left hi'i)
· exact k
· exact fun h => hk (Finset.mem_insert_of_mem h)
· intro i' j'
rw [updateRow_apply, Function.update_apply]
split_ifs with hi'i
· simp [hi'i]
rw [A_eq, updateRow_ne fun h : k = i => hk <| h ▸ Finset.mem_insert_self k s]
#align matrix.det_eq_of_forall_row_eq_smul_add_const_aux Matrix.det_eq_of_forall_row_eq_smul_add_const_aux
/-- If you add multiples of row `B k` to other rows, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_const {A B : Matrix n n R} (c : n → R) (k : n)
(hk : c k = 0) (A_eq : ∀ i j, A i j = B i j + c i * B k j) : det A = det B :=
det_eq_of_forall_row_eq_smul_add_const_aux c
(fun i =>
not_imp_comm.mp fun hi =>
Finset.mem_erase.mpr
⟨mt (fun h : i = k => show c i = 0 from h.symm ▸ hk) hi, Finset.mem_univ i⟩)
k (Finset.not_mem_erase k Finset.univ) A_eq
#align matrix.det_eq_of_forall_row_eq_smul_add_const Matrix.det_eq_of_forall_row_eq_smul_add_const
theorem det_eq_of_forall_row_eq_smul_add_pred_aux {n : ℕ} (k : Fin (n + 1)) :
∀ (c : Fin n → R) (_hc : ∀ i : Fin n, k < i.succ → c i = 0)
{M N : Matrix (Fin n.succ) (Fin n.succ) R} (_h0 : ∀ j, M 0 j = N 0 j)
(_hsucc : ∀ (i : Fin n) (j), M i.succ j = N i.succ j + c i * M (Fin.castSucc i) j),
det M = det N := by
refine' Fin.induction _ (fun k ih => _) k <;> intro c hc M N h0 hsucc
· congr
ext i j
refine' Fin.cases (h0 j) (fun i => _) i
rw [hsucc, hc i (Fin.succ_pos _), zero_mul, add_zero]
set M' := updateRow M k.succ (N k.succ) with hM'
have hM : M = updateRow M' k.succ (M' k.succ + c k • M (Fin.castSucc k)) := by
ext i j
by_cases hi : i = k.succ
· simp [hi, hM', hsucc, updateRow_self]
rw [updateRow_ne hi, hM', updateRow_ne hi]
have k_ne_succ : (Fin.castSucc k) ≠ k.succ := (Fin.castSucc_lt_succ k).ne
have M_k : M (Fin.castSucc k) = M' (Fin.castSucc k) := (updateRow_ne k_ne_succ).symm
rw [hM, M_k, det_updateRow_add_smul_self M' k_ne_succ.symm, ih (Function.update c k 0)]
· intro i hi
rw [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff] at hi
rw [Function.update_apply]
split_ifs with hik
· rfl
exact hc _ (Fin.succ_lt_succ_iff.mpr (lt_of_le_of_ne hi (Ne.symm hik)))
· rwa [hM', updateRow_ne (Fin.succ_ne_zero _).symm]
intro i j
rw [Function.update_apply]
split_ifs with hik
· rw [zero_mul, add_zero, hM', hik, updateRow_self]
rw [hM', updateRow_ne ((Fin.succ_injective _).ne hik), hsucc]
by_cases hik2 : k < i
· simp [hc i (Fin.succ_lt_succ_iff.mpr hik2)]
rw [updateRow_ne]
apply ne_of_lt
rwa [Fin.lt_iff_val_lt_val, Fin.coe_castSucc, Fin.val_succ, Nat.lt_succ_iff, ← not_lt]
#align matrix.det_eq_of_forall_row_eq_smul_add_pred_aux Matrix.det_eq_of_forall_row_eq_smul_add_pred_aux
/-- If you add multiples of previous rows to the next row, the determinant doesn't change. -/
theorem det_eq_of_forall_row_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ j, A 0 j = B 0 j)
(A_succ : ∀ (i : Fin n) (j), A i.succ j = B i.succ j + c i * A (Fin.castSucc i) j) :
det A = det B :=
det_eq_of_forall_row_eq_smul_add_pred_aux (Fin.last _) c
(fun _ hi => absurd hi (not_lt_of_ge (Fin.le_last _))) A_zero A_succ
#align matrix.det_eq_of_forall_row_eq_smul_add_pred Matrix.det_eq_of_forall_row_eq_smul_add_pred
/-- If you add multiples of previous columns to the next columns, the determinant doesn't change. -/
theorem det_eq_of_forall_col_eq_smul_add_pred {n : ℕ} {A B : Matrix (Fin (n + 1)) (Fin (n + 1)) R}
(c : Fin n → R) (A_zero : ∀ i, A i 0 = B i 0)
(A_succ : ∀ (i) (j : Fin n), A i j.succ = B i j.succ + c j * A i (Fin.castSucc j)) :
det A = det B := by
rw [← det_transpose A, ← det_transpose B]
exact det_eq_of_forall_row_eq_smul_add_pred c A_zero fun i j => A_succ j i
#align matrix.det_eq_of_forall_col_eq_smul_add_pred Matrix.det_eq_of_forall_col_eq_smul_add_pred
end DetEq
@[simp]
theorem det_blockDiagonal {o : Type*} [Fintype o] [DecidableEq o] (M : o → Matrix n n R) :
(blockDiagonal M).det = ∏ k, (M k).det := by
-- Rewrite the determinants as a sum over permutations.
simp_rw [det_apply']
-- The right hand side is a product of sums, rewrite it as a sum of products.
rw [Finset.prod_sum]
simp_rw [Finset.prod_attach_univ, Finset.univ_pi_univ]
-- We claim that the only permutations contributing to the sum are those that
-- preserve their second component.
let preserving_snd : Finset (Equiv.Perm (n × o)) :=
Finset.univ.filter fun σ => ∀ x, (σ x).snd = x.snd
have mem_preserving_snd :
∀ {σ : Equiv.Perm (n × o)}, σ ∈ preserving_snd ↔ ∀ x, (σ x).snd = x.snd := fun {σ} =>
Finset.mem_filter.trans ⟨fun h => h.2, fun h => ⟨Finset.mem_univ _, h⟩⟩
rw [← Finset.sum_subset (Finset.subset_univ preserving_snd) _]
-- And that these are in bijection with `o → Equiv.Perm m`.
rw [(Finset.sum_bij
(fun (σ : ∀ k : o, k ∈ Finset.univ → Equiv.Perm n) _ =>
prodCongrLeft fun k => σ k (Finset.mem_univ k))
_ _ _ _).symm]
· intro σ _
rw [mem_preserving_snd]
rintro ⟨-, x⟩
simp only [prodCongrLeft_apply]
· intro σ _
rw [Finset.prod_mul_distrib, ← Finset.univ_product_univ, Finset.prod_product_right]
simp only [sign_prodCongrLeft, Units.coe_prod, Int.cast_prod, blockDiagonal_apply_eq,
prodCongrLeft_apply]
· intro σ σ' _ _ eq
ext x hx k
simp only at eq
have :
∀ k x,
prodCongrLeft (fun k => σ k (Finset.mem_univ _)) (k, x) =
prodCongrLeft (fun k => σ' k (Finset.mem_univ _)) (k, x) :=
fun k x => by rw [eq]
simp only [prodCongrLeft_apply, Prod.mk.inj_iff] at this
exact (this k x).1
· intro σ hσ
rw [mem_preserving_snd] at hσ
have hσ' : ∀ x, (σ⁻¹ x).snd = x.snd := by
intro x
conv_rhs => rw [← Perm.apply_inv_self σ x, hσ]
have mk_apply_eq : ∀ k x, ((σ (x, k)).fst, k) = σ (x, k) := by
intro k x
ext
· simp only
· simp only [hσ]
have mk_inv_apply_eq : ∀ k x, ((σ⁻¹ (x, k)).fst, k) = σ⁻¹ (x, k) := by
intro k x
conv_lhs => rw [← Perm.apply_inv_self σ (x, k)]
ext
· simp only [apply_inv_self]
· simp only [hσ']
refine' ⟨fun k _ => ⟨fun x => (σ (x, k)).fst, fun x => (σ⁻¹ (x, k)).fst, _, _⟩, _, _⟩
· intro x
simp only [mk_apply_eq, inv_apply_self]
· intro x
simp only [mk_inv_apply_eq, apply_inv_self]
· apply Finset.mem_univ
· ext ⟨k, x⟩
· simp only [coe_fn_mk, prodCongrLeft_apply]
· simp only [prodCongrLeft_apply, hσ]
· intro σ _ hσ
rw [mem_preserving_snd] at hσ
obtain ⟨⟨k, x⟩, hkx⟩ := not_forall.mp hσ
rw [Finset.prod_eq_zero (Finset.mem_univ (k, x)), mul_zero]
rw [blockDiagonal_apply_ne]
exact hkx
#align matrix.det_block_diagonal Matrix.det_blockDiagonal
/-- The determinant of a 2×2 block matrix with the lower-left block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_upper_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₂₁ (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) :
(Matrix.fromBlocks A B 0 D).det = A.det * D.det := by
classical
simp_rw [det_apply']
convert Eq.symm <|
sum_subset (β := R) (subset_univ ((sumCongrHom m n).range : Set (Perm (Sum m n))).toFinset) ?_
rw [sum_mul_sum]
simp_rw [univ_product_univ]
rw [(sum_bij (fun (σ : Perm m × Perm n) _ => Equiv.sumCongr σ.fst σ.snd) _ _ _ _).symm]
· intro σ₁₂ h
simp only
erw [Set.mem_toFinset, MonoidHom.mem_range]
use σ₁₂
simp only [sumCongrHom_apply]
· simp only [forall_prop_of_true, Prod.forall, mem_univ]
intro σ₁ σ₂
rw [Fintype.prod_sum_type]
simp_rw [Equiv.sumCongr_apply, Sum.map_inr, Sum.map_inl, fromBlocks_apply₁₁,
fromBlocks_apply₂₂]
rw [mul_mul_mul_comm]
congr
rw [sign_sumCongr, Units.val_mul, Int.cast_mul]
· intro σ₁ σ₂ h₁ h₂
dsimp only
intro h
have h2 : ∀ x, Perm.sumCongr σ₁.fst σ₁.snd x = Perm.sumCongr σ₂.fst σ₂.snd x :=
FunLike.congr_fun h
simp only [Sum.map_inr, Sum.map_inl, Perm.sumCongr_apply, Sum.forall, Sum.inl.injEq,
Sum.inr.injEq] at h2
ext x
· exact h2.left x
· exact h2.right x
· intro σ hσ
erw [Set.mem_toFinset, MonoidHom.mem_range] at hσ
obtain ⟨σ₁₂, hσ₁₂⟩ := hσ
use σ₁₂
rw [← hσ₁₂]
simp
· rintro σ - hσn
have h1 : ¬∀ x, ∃ y, Sum.inl y = σ (Sum.inl x) := by
rw [Set.mem_toFinset] at hσn
-- Porting note: golfed
simpa only [Set.MapsTo, Set.mem_range, forall_exists_index, forall_apply_eq_imp_iff] using
mt mem_sumCongrHom_range_of_perm_mapsTo_inl hσn
obtain ⟨a, ha⟩ := not_forall.mp h1
cases' hx : σ (Sum.inl a) with a2 b
· have hn := (not_exists.mp ha) a2
exact absurd hx.symm hn
· rw [Finset.prod_eq_zero (Finset.mem_univ (Sum.inl a)), mul_zero]
rw [hx, fromBlocks_apply₂₁, zero_apply]
#align matrix.det_from_blocks_zero₂₁ Matrix.det_fromBlocks_zero₂₁
/-- The determinant of a 2×2 block matrix with the upper-right block equal to zero is the product of
the determinants of the diagonal blocks. For the generalization to any number of blocks, see
`Matrix.det_of_lower_triangular`. -/
@[simp]
theorem det_fromBlocks_zero₁₂ (A : Matrix m m R) (C : Matrix n m R) (D : Matrix n n R) :
(Matrix.fromBlocks A 0 C D).det = A.det * D.det := by
rw [← det_transpose, fromBlocks_transpose, transpose_zero, det_fromBlocks_zero₂₁, det_transpose,
det_transpose]
#align matrix.det_from_blocks_zero₁₂ Matrix.det_fromBlocks_zero₁₂
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column 0. -/
theorem det_succ_column_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ i : Fin n.succ, (-1) ^ (i : ℕ) * A i 0 * det (A.submatrix i.succAbove Fin.succ) := by
rw [Matrix.det_apply, Finset.univ_perm_fin_succ, ← Finset.univ_product_univ]
simp only [Finset.sum_map, Equiv.toEmbedding_apply, Finset.sum_product, Matrix.submatrix]
refine' Finset.sum_congr rfl fun i _ => Fin.cases _ (fun i => _) i
· simp only [Fin.prod_univ_succ, Matrix.det_apply, Finset.mul_sum,
Equiv.Perm.decomposeFin_symm_apply_zero, Fin.val_zero, one_mul,
Equiv.Perm.decomposeFin.symm_sign, Equiv.swap_self, if_true, id.def, eq_self_iff_true,
Equiv.Perm.decomposeFin_symm_apply_succ, Fin.succAbove_zero, Equiv.coe_refl, pow_zero,
mul_smul_comm, of_apply]
-- `univ_perm_fin_succ` gives a different embedding of `Perm (Fin n)` into
-- `Perm (Fin n.succ)` than the determinant of the submatrix we want,
-- permute `A` so that we get the correct one.
have : (-1 : R) ^ (i : ℕ) = (Perm.sign i.cycleRange) := by simp [Fin.sign_cycleRange]
rw [Fin.val_succ, pow_succ, this, mul_assoc, mul_assoc, mul_left_comm (ε _), ←
det_permute, Matrix.det_apply, Finset.mul_sum, Finset.mul_sum]
-- now we just need to move the corresponding parts to the same place
refine' Finset.sum_congr rfl fun σ _ => _
rw [Equiv.Perm.decomposeFin.symm_sign, if_neg (Fin.succ_ne_zero i)]
calc
((-1 * Perm.sign σ : ℤ) • ∏ i', A (Perm.decomposeFin.symm (Fin.succ i, σ) i') i') =
(-1 * Perm.sign σ : ℤ) • (A (Fin.succ i) 0 *
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp only [Fin.prod_univ_succ, Fin.succAbove_cycleRange,
Equiv.Perm.decomposeFin_symm_apply_zero, Equiv.Perm.decomposeFin_symm_apply_succ]
_ = -1 * (A (Fin.succ i) 0 * (Perm.sign σ : ℤ) •
∏ i', A ((Fin.succ i).succAbove (Fin.cycleRange i (σ i'))) i'.succ) := by
simp [mul_assoc, mul_comm, _root_.neg_mul, one_mul, zsmul_eq_mul, neg_inj, neg_smul,
Fin.succAbove_cycleRange, mul_left_comm]
#align matrix.det_succ_column_zero Matrix.det_succ_column_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row 0. -/
theorem det_succ_row_zero {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) :
det A = ∑ j : Fin n.succ, (-1) ^ (j : ℕ) * A 0 j * det (A.submatrix Fin.succ j.succAbove) := by
rw [← det_transpose A, det_succ_column_zero]
refine' Finset.sum_congr rfl fun i _ => _
rw [← det_transpose]
simp only [transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_row_zero Matrix.det_succ_row_zero
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along row `i`. -/
theorem det_succ_row {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (i : Fin n.succ) :
det A =
∑ j : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
simp_rw [pow_add, mul_assoc, ← mul_sum]
have : det A = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by
calc
det A = ↑((-1 : ℤˣ) ^ (i : ℕ) * (-1 : ℤˣ) ^ (i : ℕ) : ℤˣ) * det A := by simp
_ = (-1 : R) ^ (i : ℕ) * (Perm.sign i.cycleRange⁻¹) * det A := by simp [-Int.units_mul_self]
rw [this, mul_assoc]
congr
rw [← det_permute, det_succ_row_zero]
refine' Finset.sum_congr rfl fun j _ => _
rw [mul_assoc, Matrix.submatrix, Matrix.submatrix]
congr
· rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_zero]
· ext i' j'
rw [Equiv.Perm.inv_def, Fin.cycleRange_symm_succ]
#align matrix.det_succ_row Matrix.det_succ_row
/-- Laplacian expansion of the determinant of an `n+1 × n+1` matrix along column `j`. -/
theorem det_succ_column {n : ℕ} (A : Matrix (Fin n.succ) (Fin n.succ) R) (j : Fin n.succ) :
det A =
∑ i : Fin n.succ, (-1) ^ (i + j : ℕ) * A i j * det (A.submatrix i.succAbove j.succAbove) := by
rw [← det_transpose, det_succ_row _ j]
refine' Finset.sum_congr rfl fun i _ => _
rw [add_comm, ← det_transpose, transpose_apply, transpose_submatrix, transpose_transpose]
#align matrix.det_succ_column Matrix.det_succ_column
/-- Determinant of 0x0 matrix -/
@[simp]
theorem det_fin_zero {A : Matrix (Fin 0) (Fin 0) R} : det A = 1 :=
det_isEmpty
#align matrix.det_fin_zero Matrix.det_fin_zero
/-- Determinant of 1x1 matrix -/
theorem det_fin_one (A : Matrix (Fin 1) (Fin 1) R) : det A = A 0 0 :=
det_unique A
#align matrix.det_fin_one Matrix.det_fin_one
theorem det_fin_one_of (a : R) : det !![a] = a :=
det_fin_one _
#align matrix.det_fin_one_of Matrix.det_fin_one_of
/-- Determinant of 2x2 matrix -/
theorem det_fin_two (A : Matrix (Fin 2) (Fin 2) R) : det A = A 0 0 * A 1 1 - A 0 1 * A 1 0 := by
simp only [det_succ_row_zero, det_unique, Fin.default_eq_zero, submatrix_apply,
Fin.succ_zero_eq_one, Fin.sum_univ_succ, Fin.val_zero, Fin.zero_succAbove, univ_unique,
Fin.val_succ, Fin.coe_fin_one, Fin.succ_succAbove_zero, sum_singleton]
ring
#align matrix.det_fin_two Matrix.det_fin_two
@[simp]
theorem det_fin_two_of (a b c d : R) : Matrix.det !![a, b; c, d] = a * d - b * c :=
det_fin_two _
#align matrix.det_fin_two_of Matrix.det_fin_two_of
/-- Determinant of 3x3 matrix -/
theorem det_fin_three (A : Matrix (Fin 3) (Fin 3) R) :
det A =
A 0 0 * A 1 1 * A 2 2 - A 0 0 * A 1 2 * A 2 1
- A 0 1 * A 1 0 * A 2 2 + A 0 1 * A 1 2 * A 2 0
+ A 0 2 * A 1 0 * A 2 1 - A 0 2 * A 1 1 * A 2 0 := by
simp only [det_succ_row_zero, Nat.odd_iff_not_even, submatrix_apply, Fin.succ_zero_eq_one,
submatrix_submatrix, det_unique, Fin.default_eq_zero, comp_apply, Fin.succ_one_eq_two,
Fin.sum_univ_succ, Fin.val_zero, Fin.zero_succAbove, univ_unique, Fin.val_succ,
Fin.coe_fin_one, Fin.succ_succAbove_zero, sum_singleton, Fin.succ_succAbove_one, even_add_self]
| ring | /-- Determinant of 3x3 matrix -/
theorem det_fin_three (A : Matrix (Fin 3) (Fin 3) R) :
det A =
A 0 0 * A 1 1 * A 2 2 - A 0 0 * A 1 2 * A 2 1
- A 0 1 * A 1 0 * A 2 2 + A 0 1 * A 1 2 * A 2 0
+ A 0 2 * A 1 0 * A 2 1 - A 0 2 * A 1 1 * A 2 0 := by
simp only [det_succ_row_zero, Nat.odd_iff_not_even, submatrix_apply, Fin.succ_zero_eq_one,
submatrix_submatrix, det_unique, Fin.default_eq_zero, comp_apply, Fin.succ_one_eq_two,
Fin.sum_univ_succ, Fin.val_zero, Fin.zero_succAbove, univ_unique, Fin.val_succ,
Fin.coe_fin_one, Fin.succ_succAbove_zero, sum_singleton, Fin.succ_succAbove_one, even_add_self]
| Mathlib.LinearAlgebra.Matrix.Determinant.807_0.U1f6HO8zRbnvZ95 | /-- Determinant of 3x3 matrix -/
theorem det_fin_three (A : Matrix (Fin 3) (Fin 3) R) :
det A =
A 0 0 * A 1 1 * A 2 2 - A 0 0 * A 1 2 * A 2 1
- A 0 1 * A 1 0 * A 2 2 + A 0 1 * A 1 2 * A 2 0
+ A 0 2 * A 1 0 * A 2 1 - A 0 2 * A 1 1 * A 2 0 | Mathlib_LinearAlgebra_Matrix_Determinant |
A : Type v
inst✝ : Ring A
x✝² x✝¹ x✝ : A
⊢ ⁅x✝² + x✝¹, x✝⁆ = ⁅x✝², x✝⁆ + ⁅x✝¹, x✝⁆ | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by | simp only [Ring.lie_def, right_distrib, left_distrib] | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by | Mathlib.Algebra.Lie.OfAssociative.67_0.ll51mLev4p7Z1wP | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority | Mathlib_Algebra_Lie_OfAssociative |
A : Type v
inst✝ : Ring A
x✝² x✝¹ x✝ : A
⊢ x✝² * x✝ + x✝¹ * x✝ - (x✝ * x✝² + x✝ * x✝¹) = x✝² * x✝ - x✝ * x✝² + (x✝¹ * x✝ - x✝ * x✝¹) | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; | abel | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; | Mathlib.Algebra.Lie.OfAssociative.67_0.ll51mLev4p7Z1wP | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority | Mathlib_Algebra_Lie_OfAssociative |
A : Type v
inst✝ : Ring A
x✝² x✝¹ x✝ : A
⊢ x✝² * x✝ + x✝¹ * x✝ - (x✝ * x✝² + x✝ * x✝¹) = x✝² * x✝ - x✝ * x✝² + (x✝¹ * x✝ - x✝ * x✝¹) | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; | abel | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; | Mathlib.Algebra.Lie.OfAssociative.67_0.ll51mLev4p7Z1wP | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority | Mathlib_Algebra_Lie_OfAssociative |
A : Type v
inst✝ : Ring A
x✝² x✝¹ x✝ : A
⊢ ⁅x✝², x✝¹ + x✝⁆ = ⁅x✝², x✝¹⁆ + ⁅x✝², x✝⁆ | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by | simp only [Ring.lie_def, right_distrib, left_distrib] | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by | Mathlib.Algebra.Lie.OfAssociative.67_0.ll51mLev4p7Z1wP | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority | Mathlib_Algebra_Lie_OfAssociative |
A : Type v
inst✝ : Ring A
x✝² x✝¹ x✝ : A
⊢ x✝² * x✝¹ + x✝² * x✝ - (x✝¹ * x✝² + x✝ * x✝²) = x✝² * x✝¹ - x✝¹ * x✝² + (x✝² * x✝ - x✝ * x✝²) | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; | abel | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; | Mathlib.Algebra.Lie.OfAssociative.67_0.ll51mLev4p7Z1wP | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority | Mathlib_Algebra_Lie_OfAssociative |
A : Type v
inst✝ : Ring A
x✝² x✝¹ x✝ : A
⊢ x✝² * x✝¹ + x✝² * x✝ - (x✝¹ * x✝² + x✝ * x✝²) = x✝² * x✝¹ - x✝¹ * x✝² + (x✝² * x✝ - x✝ * x✝²) | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; | abel | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; | Mathlib.Algebra.Lie.OfAssociative.67_0.ll51mLev4p7Z1wP | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority | Mathlib_Algebra_Lie_OfAssociative |
A : Type v
inst✝ : Ring A
⊢ ∀ (x : A), ⁅x, x⁆ = 0 | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by | simp only [Ring.lie_def, forall_const, sub_self] | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by | Mathlib.Algebra.Lie.OfAssociative.67_0.ll51mLev4p7Z1wP | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority | Mathlib_Algebra_Lie_OfAssociative |
A : Type v
inst✝ : Ring A
x✝² x✝¹ x✝ : A
⊢ ⁅x✝², ⁅x✝¹, x✝⁆⁆ = ⁅⁅x✝², x✝¹⁆, x✝⁆ + ⁅x✝¹, ⁅x✝², x✝⁆⁆ | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
| simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc] | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
| Mathlib.Algebra.Lie.OfAssociative.67_0.ll51mLev4p7Z1wP | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority | Mathlib_Algebra_Lie_OfAssociative |
A : Type v
inst✝ : Ring A
x✝² x✝¹ x✝ : A
⊢ x✝² * (x✝¹ * x✝) - x✝² * (x✝ * x✝¹) - (x✝¹ * (x✝ * x✝²) - x✝ * (x✝¹ * x✝²)) =
x✝² * (x✝¹ * x✝) - x✝¹ * (x✝² * x✝) - (x✝ * (x✝² * x✝¹) - x✝ * (x✝¹ * x✝²)) +
(x✝¹ * (x✝² * x✝) - x✝¹ * (x✝ * x✝²) - (x✝² * (x✝ * x✝¹) - x✝ * (x✝² * x✝¹))) | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; | abel | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; | Mathlib.Algebra.Lie.OfAssociative.67_0.ll51mLev4p7Z1wP | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority | Mathlib_Algebra_Lie_OfAssociative |
A : Type v
inst✝ : Ring A
x✝² x✝¹ x✝ : A
⊢ x✝² * (x✝¹ * x✝) - x✝² * (x✝ * x✝¹) - (x✝¹ * (x✝ * x✝²) - x✝ * (x✝¹ * x✝²)) =
x✝² * (x✝¹ * x✝) - x✝¹ * (x✝² * x✝) - (x✝ * (x✝² * x✝¹) - x✝ * (x✝¹ * x✝²)) +
(x✝¹ * (x✝² * x✝) - x✝¹ * (x✝ * x✝²) - (x✝² * (x✝ * x✝¹) - x✝ * (x✝² * x✝¹))) | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; | abel | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; | Mathlib.Algebra.Lie.OfAssociative.67_0.ll51mLev4p7Z1wP | /-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority | Mathlib_Algebra_Lie_OfAssociative |
A : Type v
inst✝² : Ring A
M : Type w
inst✝¹ : AddCommGroup M
inst✝ : Module A M
⊢ ∀ (x y : A) (m : M), ⁅x, ⁅y, m⁆⁆ = ⁅⁅x, y⁆, m⁆ + ⁅y, ⁅x, m⁆⁆ | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by | simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel] | /-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by | Mathlib.Algebra.Lie.OfAssociative.91_0.ll51mLev4p7Z1wP | /-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket | Mathlib_Algebra_Lie_OfAssociative |
A : Type v
inst✝² : Ring A
R : Type u
inst✝¹ : CommRing R
inst✝ : Algebra R A
t : R
x y : A
⊢ ⁅x, t • y⁆ = t • ⁅x, y⁆ | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
| rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub] | /-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
| Mathlib.Algebra.Lie.OfAssociative.121_0.ll51mLev4p7Z1wP | /-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority | Mathlib_Algebra_Lie_OfAssociative |
A : Type v
inst✝⁶ : Ring A
R : Type u
inst✝⁵ : CommRing R
inst✝⁴ : Algebra R A
B : Type w
C : Type w₁
inst✝³ : Ring B
inst✝² : Ring C
inst✝¹ : Algebra R B
inst✝ : Algebra R C
f : A →ₐ[R] B
g : B →ₐ[R] C
src✝ : A →ₗ[R] B := toLinearMap f
x✝¹ x✝ : A
⊢ AddHom.toFun
{ toAddHom := src✝.toAddHom,
map_smul' :=
(_ :
∀ (r : R) (x : A),
AddHom.toFun src✝.toAddHom (r • x) = (RingHom.id R) r • AddHom.toFun src✝.toAddHom x) }.toAddHom
⁅x✝¹, x✝⁆ =
⁅AddHom.toFun
{ toAddHom := src✝.toAddHom,
map_smul' :=
(_ :
∀ (r : R) (x : A),
AddHom.toFun src✝.toAddHom (r • x) = (RingHom.id R) r • AddHom.toFun src✝.toAddHom x) }.toAddHom
x✝¹,
AddHom.toFun
{ toAddHom := src✝.toAddHom,
map_smul' :=
(_ :
∀ (r : R) (x : A),
AddHom.toFun src✝.toAddHom (r • x) = (RingHom.id R) r • AddHom.toFun src✝.toAddHom x) }.toAddHom
x✝⁆ | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by | simp [LieRing.of_associative_ring_bracket] | /-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by | Mathlib.Algebra.Lie.OfAssociative.161_0.ll51mLev4p7Z1wP | /-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B | Mathlib_Algebra_Lie_OfAssociative |
A : Type v
inst✝⁶ : Ring A
R : Type u
inst✝⁵ : CommRing R
inst✝⁴ : Algebra R A
B : Type w
C : Type w₁
inst✝³ : Ring B
inst✝² : Ring C
inst✝¹ : Algebra R B
inst✝ : Algebra R C
f✝ : A →ₐ[R] B
g✝ : B →ₐ[R] C
f g : A →ₐ[R] B
h : toLieHom f = toLieHom g
⊢ f = g | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
| ext a | theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
| Mathlib.Algebra.Lie.OfAssociative.197_0.ll51mLev4p7Z1wP | theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g | Mathlib_Algebra_Lie_OfAssociative |
case H
A : Type v
inst✝⁶ : Ring A
R : Type u
inst✝⁵ : CommRing R
inst✝⁴ : Algebra R A
B : Type w
C : Type w₁
inst✝³ : Ring B
inst✝² : Ring C
inst✝¹ : Algebra R B
inst✝ : Algebra R C
f✝ : A →ₐ[R] B
g✝ : B →ₐ[R] C
f g : A →ₐ[R] B
h : toLieHom f = toLieHom g
a : A
⊢ f a = g a | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; | exact LieHom.congr_fun h a | theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; | Mathlib.Algebra.Lie.OfAssociative.197_0.ll51mLev4p7Z1wP | theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g | Mathlib_Algebra_Lie_OfAssociative |
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
x y : L
⊢ (fun x =>
{ toAddHom := { toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{ toAddHom := { toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{ toAddHom := { toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by | ext m | /-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by | Mathlib.Algebra.Lie.OfAssociative.215_0.ll51mLev4p7Z1wP | /-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x | Mathlib_Algebra_Lie_OfAssociative |
case h
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
x y : L
m : M
⊢ ((fun x =>
{ toAddHom := { toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y))
m =
((fun x =>
{ toAddHom := { toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{ toAddHom := { toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y)
m | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; | apply add_lie | /-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; | Mathlib.Algebra.Lie.OfAssociative.215_0.ll51mLev4p7Z1wP | /-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x | Mathlib_Algebra_Lie_OfAssociative |
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
t : R
x : L
⊢ AddHom.toFun
{
toFun := fun x =>
{ toAddHom := { toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
(t • x) =
(RingHom.id R) t •
AddHom.toFun
{
toFun := fun x =>
{ toAddHom := { toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
x | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by | ext m | /-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by | Mathlib.Algebra.Lie.OfAssociative.215_0.ll51mLev4p7Z1wP | /-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x | Mathlib_Algebra_Lie_OfAssociative |
case h
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
t : R
x : L
m : M
⊢ (AddHom.toFun
{
toFun := fun x =>
{ toAddHom := { toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
(t • x))
m =
((RingHom.id R) t •
AddHom.toFun
{
toFun := fun x =>
{ toAddHom := { toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
x)
m | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; | apply smul_lie | /-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; | Mathlib.Algebra.Lie.OfAssociative.215_0.ll51mLev4p7Z1wP | /-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x | Mathlib_Algebra_Lie_OfAssociative |
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
x y : L
⊢ AddHom.toFun
{
toAddHom :=
{
toFun := fun x =>
{ toAddHom := { toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) },
map_smul' :=
(_ :
∀ (t : R) (x : L),
AddHom.toFun
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
(t • x) =
(RingHom.id R) t •
AddHom.toFun
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
x) }.toAddHom
⁅x, y⁆ =
⁅AddHom.toFun
{
toAddHom :=
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) },
map_smul' :=
(_ :
∀ (t : R) (x : L),
AddHom.toFun
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
(t • x) =
(RingHom.id R) t •
AddHom.toFun
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
x) }.toAddHom
x,
AddHom.toFun
{
toAddHom :=
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) },
map_smul' :=
(_ :
∀ (t : R) (x : L),
AddHom.toFun
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
(t • x) =
(RingHom.id R) t •
AddHom.toFun
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
x) }.toAddHom
y⁆ | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by | ext m | /-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by | Mathlib.Algebra.Lie.OfAssociative.215_0.ll51mLev4p7Z1wP | /-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x | Mathlib_Algebra_Lie_OfAssociative |
case h
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
x y : L
m : M
⊢ (AddHom.toFun
{
toAddHom :=
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) },
map_smul' :=
(_ :
∀ (t : R) (x : L),
AddHom.toFun
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
(t • x) =
(RingHom.id R) t •
AddHom.toFun
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
x) }.toAddHom
⁅x, y⁆)
m =
⁅AddHom.toFun
{
toAddHom :=
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) },
map_smul' :=
(_ :
∀ (t : R) (x : L),
AddHom.toFun
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
(t • x) =
(RingHom.id R) t •
AddHom.toFun
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
x) }.toAddHom
x,
AddHom.toFun
{
toAddHom :=
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆, map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) },
map_smul' :=
(_ :
∀ (t : R) (x : L),
AddHom.toFun
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
(t • x) =
(RingHom.id R) t •
AddHom.toFun
{
toFun := fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) },
map_add' :=
(_ :
∀ (x y : L),
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
(x + y) =
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
x +
(fun x =>
{
toAddHom :=
{ toFun := fun m => ⁅x, m⁆,
map_add' := (_ : ∀ (m n : M), ⁅x, m + n⁆ = ⁅x, m⁆ + ⁅x, n⁆) },
map_smul' := (_ : ∀ (t : R) (m : M), ⁅x, t • m⁆ = t • ⁅x, m⁆) })
y) }
x) }.toAddHom
y⁆
m | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; | apply lie_lie | /-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; | Mathlib.Algebra.Lie.OfAssociative.215_0.ll51mLev4p7Z1wP | /-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x | Mathlib_Algebra_Lie_OfAssociative |
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
⊢ toEndomorphism R (Module.End R M) M = LieHom.id | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by | ext g m | @[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by | Mathlib.Algebra.Lie.OfAssociative.239_0.ll51mLev4p7Z1wP | @[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id | Mathlib_Algebra_Lie_OfAssociative |
case h.h
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
g : Module.End R M
m : M
⊢ ((toEndomorphism R (Module.End R M) M) g) m = (LieHom.id g) m | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; | simp [lie_eq_smul] | @[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; | Mathlib.Algebra.Lie.OfAssociative.239_0.ll51mLev4p7Z1wP | @[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id | Mathlib_Algebra_Lie_OfAssociative |
R : Type u
L : Type v
M : Type w
inst✝¹⁰ : CommRing R
inst✝⁹ : LieRing L
inst✝⁸ : LieAlgebra R L
inst✝⁷ : AddCommGroup M
inst✝⁶ : Module R M
inst✝⁵ : LieRingModule L M
inst✝⁴ : LieModule R L M
M₂ : Type w₁
inst✝³ : AddCommGroup M₂
inst✝² : Module R M₂
inst✝¹ : LieRingModule L M₂
inst✝ : LieModule R L M₂
f : M →ₗ⁅R,L⁆ M₂
k : ℕ
x : L
⊢ ((toEndomorphism R L M₂) x ^ k) ∘ₗ ↑f = ↑f ∘ₗ (toEndomorphism R L M) x ^ k | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEndomorphism_module_end
theorem LieSubalgebra.toEndomorphism_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEndomorphism R K M x = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEndomorphism_eq
@[simp]
theorem LieSubalgebra.toEndomorphism_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEndomorphism R K M ⟨x, hx⟩ = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEndomorphism_mk
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
| apply LinearMap.commute_pow_left_of_commute | lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
| Mathlib.Algebra.Lie.OfAssociative.262_0.ll51mLev4p7Z1wP | lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k | Mathlib_Algebra_Lie_OfAssociative |
case h
R : Type u
L : Type v
M : Type w
inst✝¹⁰ : CommRing R
inst✝⁹ : LieRing L
inst✝⁸ : LieAlgebra R L
inst✝⁷ : AddCommGroup M
inst✝⁶ : Module R M
inst✝⁵ : LieRingModule L M
inst✝⁴ : LieModule R L M
M₂ : Type w₁
inst✝³ : AddCommGroup M₂
inst✝² : Module R M₂
inst✝¹ : LieRingModule L M₂
inst✝ : LieModule R L M₂
f : M →ₗ⁅R,L⁆ M₂
k : ℕ
x : L
⊢ LinearMap.comp ((toEndomorphism R L M₂) x) ↑f = ↑f ∘ₗ (toEndomorphism R L M) x | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEndomorphism_module_end
theorem LieSubalgebra.toEndomorphism_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEndomorphism R K M x = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEndomorphism_eq
@[simp]
theorem LieSubalgebra.toEndomorphism_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEndomorphism R K M ⟨x, hx⟩ = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEndomorphism_mk
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
| ext | lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
| Mathlib.Algebra.Lie.OfAssociative.262_0.ll51mLev4p7Z1wP | lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k | Mathlib_Algebra_Lie_OfAssociative |
case h.h
R : Type u
L : Type v
M : Type w
inst✝¹⁰ : CommRing R
inst✝⁹ : LieRing L
inst✝⁸ : LieAlgebra R L
inst✝⁷ : AddCommGroup M
inst✝⁶ : Module R M
inst✝⁵ : LieRingModule L M
inst✝⁴ : LieModule R L M
M₂ : Type w₁
inst✝³ : AddCommGroup M₂
inst✝² : Module R M₂
inst✝¹ : LieRingModule L M₂
inst✝ : LieModule R L M₂
f : M →ₗ⁅R,L⁆ M₂
k : ℕ
x : L
x✝ : M
⊢ (LinearMap.comp ((toEndomorphism R L M₂) x) ↑f) x✝ = (↑f ∘ₗ (toEndomorphism R L M) x) x✝ | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEndomorphism_module_end
theorem LieSubalgebra.toEndomorphism_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEndomorphism R K M x = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEndomorphism_eq
@[simp]
theorem LieSubalgebra.toEndomorphism_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEndomorphism R K M ⟨x, hx⟩ = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEndomorphism_mk
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
ext
| simp | lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
ext
| Mathlib.Algebra.Lie.OfAssociative.262_0.ll51mLev4p7Z1wP | lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k | Mathlib_Algebra_Lie_OfAssociative |
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
N : LieSubmodule R L M
x : L
⊢ Submodule.map ((toEndomorphism R L M) x) ↑N ≤ ↑N | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEndomorphism_module_end
theorem LieSubalgebra.toEndomorphism_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEndomorphism R K M x = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEndomorphism_eq
@[simp]
theorem LieSubalgebra.toEndomorphism_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEndomorphism R K M ⟨x, hx⟩ = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEndomorphism_mk
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
ext
simp
lemma toEndomorphism_pow_apply_map (m : M) :
(toEndomorphism R L M₂ x ^ k) (f m) = f ((toEndomorphism R L M x ^ k) m) :=
LinearMap.congr_fun (toEndomorphism_pow_comp_lieHom f k x) m
end LieModule
namespace LieSubmodule
open LieModule Set
variable {N : LieSubmodule R L M} {x : L}
theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N := by
| rintro n ⟨m, hm, rfl⟩ | theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N := by
| Mathlib.Algebra.Lie.OfAssociative.280_0.ll51mLev4p7Z1wP | theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N | Mathlib_Algebra_Lie_OfAssociative |
case intro.intro
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
N : LieSubmodule R L M
x : L
m : M
hm : m ∈ ↑↑N
⊢ ((toEndomorphism R L M) x) m ∈ ↑N | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEndomorphism_module_end
theorem LieSubalgebra.toEndomorphism_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEndomorphism R K M x = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEndomorphism_eq
@[simp]
theorem LieSubalgebra.toEndomorphism_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEndomorphism R K M ⟨x, hx⟩ = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEndomorphism_mk
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
ext
simp
lemma toEndomorphism_pow_apply_map (m : M) :
(toEndomorphism R L M₂ x ^ k) (f m) = f ((toEndomorphism R L M x ^ k) m) :=
LinearMap.congr_fun (toEndomorphism_pow_comp_lieHom f k x) m
end LieModule
namespace LieSubmodule
open LieModule Set
variable {N : LieSubmodule R L M} {x : L}
theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N := by
rintro n ⟨m, hm, rfl⟩
| exact N.lie_mem hm | theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N := by
rintro n ⟨m, hm, rfl⟩
| Mathlib.Algebra.Lie.OfAssociative.280_0.ll51mLev4p7Z1wP | theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N | Mathlib_Algebra_Lie_OfAssociative |
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
N : LieSubmodule R L M
x : L
m : M
hm : m ∈ ↑N
⊢ ((toEndomorphism R L M) x ∘ₗ Submodule.subtype ↑N) { val := m, property := hm } ∈ ↑N | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEndomorphism_module_end
theorem LieSubalgebra.toEndomorphism_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEndomorphism R K M x = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEndomorphism_eq
@[simp]
theorem LieSubalgebra.toEndomorphism_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEndomorphism R K M ⟨x, hx⟩ = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEndomorphism_mk
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
ext
simp
lemma toEndomorphism_pow_apply_map (m : M) :
(toEndomorphism R L M₂ x ^ k) (f m) = f ((toEndomorphism R L M x ^ k) m) :=
LinearMap.congr_fun (toEndomorphism_pow_comp_lieHom f k x) m
end LieModule
namespace LieSubmodule
open LieModule Set
variable {N : LieSubmodule R L M} {x : L}
theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N := by
rintro n ⟨m, hm, rfl⟩
exact N.lie_mem hm
#align lie_submodule.coe_map_to_endomorphism_le LieSubmodule.coe_map_toEndomorphism_le
variable (N x)
theorem toEndomorphism_comp_subtype_mem (m : M) (hm : m ∈ (N : Submodule R M)) :
(toEndomorphism R L M x).comp (N : Submodule R M).subtype ⟨m, hm⟩ ∈ (N : Submodule R M) := by
| simpa using N.lie_mem hm | theorem toEndomorphism_comp_subtype_mem (m : M) (hm : m ∈ (N : Submodule R M)) :
(toEndomorphism R L M x).comp (N : Submodule R M).subtype ⟨m, hm⟩ ∈ (N : Submodule R M) := by
| Mathlib.Algebra.Lie.OfAssociative.288_0.ll51mLev4p7Z1wP | theorem toEndomorphism_comp_subtype_mem (m : M) (hm : m ∈ (N : Submodule R M)) :
(toEndomorphism R L M x).comp (N : Submodule R M).subtype ⟨m, hm⟩ ∈ (N : Submodule R M) | Mathlib_Algebra_Lie_OfAssociative |
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
N : LieSubmodule R L M
x : L
h :
optParam
(∀ (m : M) (hm : m ∈ ↑N), ((toEndomorphism R L M) x ∘ₗ Submodule.subtype ↑N) { val := m, property := hm } ∈ ↑N)
(_ : ∀ (m : M) (hm : m ∈ ↑N), ((toEndomorphism R L M) x ∘ₗ Submodule.subtype ↑N) { val := m, property := hm } ∈ ↑N)
⊢ LinearMap.restrict ((toEndomorphism R L M) x) h = (toEndomorphism R L ↥↑N) x | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEndomorphism_module_end
theorem LieSubalgebra.toEndomorphism_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEndomorphism R K M x = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEndomorphism_eq
@[simp]
theorem LieSubalgebra.toEndomorphism_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEndomorphism R K M ⟨x, hx⟩ = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEndomorphism_mk
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
ext
simp
lemma toEndomorphism_pow_apply_map (m : M) :
(toEndomorphism R L M₂ x ^ k) (f m) = f ((toEndomorphism R L M x ^ k) m) :=
LinearMap.congr_fun (toEndomorphism_pow_comp_lieHom f k x) m
end LieModule
namespace LieSubmodule
open LieModule Set
variable {N : LieSubmodule R L M} {x : L}
theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N := by
rintro n ⟨m, hm, rfl⟩
exact N.lie_mem hm
#align lie_submodule.coe_map_to_endomorphism_le LieSubmodule.coe_map_toEndomorphism_le
variable (N x)
theorem toEndomorphism_comp_subtype_mem (m : M) (hm : m ∈ (N : Submodule R M)) :
(toEndomorphism R L M x).comp (N : Submodule R M).subtype ⟨m, hm⟩ ∈ (N : Submodule R M) := by
simpa using N.lie_mem hm
#align lie_submodule.to_endomorphism_comp_subtype_mem LieSubmodule.toEndomorphism_comp_subtype_mem
@[simp]
theorem toEndomorphism_restrict_eq_toEndomorphism (h := N.toEndomorphism_comp_subtype_mem x) :
(toEndomorphism R L M x).restrict h = toEndomorphism R L N x := by
| ext | @[simp]
theorem toEndomorphism_restrict_eq_toEndomorphism (h := N.toEndomorphism_comp_subtype_mem x) :
(toEndomorphism R L M x).restrict h = toEndomorphism R L N x := by
| Mathlib.Algebra.Lie.OfAssociative.293_0.ll51mLev4p7Z1wP | @[simp]
theorem toEndomorphism_restrict_eq_toEndomorphism (h | Mathlib_Algebra_Lie_OfAssociative |
case h.a
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
N : LieSubmodule R L M
x : L
h :
optParam
(∀ (m : M) (hm : m ∈ ↑N), ((toEndomorphism R L M) x ∘ₗ Submodule.subtype ↑N) { val := m, property := hm } ∈ ↑N)
(_ : ∀ (m : M) (hm : m ∈ ↑N), ((toEndomorphism R L M) x ∘ₗ Submodule.subtype ↑N) { val := m, property := hm } ∈ ↑N)
x✝ : ↥↑N
⊢ ↑((LinearMap.restrict ((toEndomorphism R L M) x) h) x✝) = ↑(((toEndomorphism R L ↥↑N) x) x✝) | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEndomorphism_module_end
theorem LieSubalgebra.toEndomorphism_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEndomorphism R K M x = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEndomorphism_eq
@[simp]
theorem LieSubalgebra.toEndomorphism_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEndomorphism R K M ⟨x, hx⟩ = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEndomorphism_mk
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
ext
simp
lemma toEndomorphism_pow_apply_map (m : M) :
(toEndomorphism R L M₂ x ^ k) (f m) = f ((toEndomorphism R L M x ^ k) m) :=
LinearMap.congr_fun (toEndomorphism_pow_comp_lieHom f k x) m
end LieModule
namespace LieSubmodule
open LieModule Set
variable {N : LieSubmodule R L M} {x : L}
theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N := by
rintro n ⟨m, hm, rfl⟩
exact N.lie_mem hm
#align lie_submodule.coe_map_to_endomorphism_le LieSubmodule.coe_map_toEndomorphism_le
variable (N x)
theorem toEndomorphism_comp_subtype_mem (m : M) (hm : m ∈ (N : Submodule R M)) :
(toEndomorphism R L M x).comp (N : Submodule R M).subtype ⟨m, hm⟩ ∈ (N : Submodule R M) := by
simpa using N.lie_mem hm
#align lie_submodule.to_endomorphism_comp_subtype_mem LieSubmodule.toEndomorphism_comp_subtype_mem
@[simp]
theorem toEndomorphism_restrict_eq_toEndomorphism (h := N.toEndomorphism_comp_subtype_mem x) :
(toEndomorphism R L M x).restrict h = toEndomorphism R L N x := by
ext; | simp [LinearMap.restrict_apply] | @[simp]
theorem toEndomorphism_restrict_eq_toEndomorphism (h := N.toEndomorphism_comp_subtype_mem x) :
(toEndomorphism R L M x).restrict h = toEndomorphism R L N x := by
ext; | Mathlib.Algebra.Lie.OfAssociative.293_0.ll51mLev4p7Z1wP | @[simp]
theorem toEndomorphism_restrict_eq_toEndomorphism (h | Mathlib_Algebra_Lie_OfAssociative |
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
N : LieSubmodule R L M
x✝ : L
φ : R
k : ℕ
x : L
⊢ MapsTo ⇑(((toEndomorphism R L M) x - (algebraMap R (Module.End R M)) φ) ^ k) ↑N ↑N | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEndomorphism_module_end
theorem LieSubalgebra.toEndomorphism_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEndomorphism R K M x = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEndomorphism_eq
@[simp]
theorem LieSubalgebra.toEndomorphism_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEndomorphism R K M ⟨x, hx⟩ = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEndomorphism_mk
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
ext
simp
lemma toEndomorphism_pow_apply_map (m : M) :
(toEndomorphism R L M₂ x ^ k) (f m) = f ((toEndomorphism R L M x ^ k) m) :=
LinearMap.congr_fun (toEndomorphism_pow_comp_lieHom f k x) m
end LieModule
namespace LieSubmodule
open LieModule Set
variable {N : LieSubmodule R L M} {x : L}
theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N := by
rintro n ⟨m, hm, rfl⟩
exact N.lie_mem hm
#align lie_submodule.coe_map_to_endomorphism_le LieSubmodule.coe_map_toEndomorphism_le
variable (N x)
theorem toEndomorphism_comp_subtype_mem (m : M) (hm : m ∈ (N : Submodule R M)) :
(toEndomorphism R L M x).comp (N : Submodule R M).subtype ⟨m, hm⟩ ∈ (N : Submodule R M) := by
simpa using N.lie_mem hm
#align lie_submodule.to_endomorphism_comp_subtype_mem LieSubmodule.toEndomorphism_comp_subtype_mem
@[simp]
theorem toEndomorphism_restrict_eq_toEndomorphism (h := N.toEndomorphism_comp_subtype_mem x) :
(toEndomorphism R L M x).restrict h = toEndomorphism R L N x := by
ext; simp [LinearMap.restrict_apply]
#align lie_submodule.to_endomorphism_restrict_eq_to_endomorphism LieSubmodule.toEndomorphism_restrict_eq_toEndomorphism
lemma mapsTo_pow_toEndomorphism_sub_algebraMap {φ : R} {k : ℕ} {x : L} :
MapsTo ((toEndomorphism R L M x - algebraMap R (Module.End R M) φ) ^ k) N N := by
| rw [LinearMap.coe_pow] | lemma mapsTo_pow_toEndomorphism_sub_algebraMap {φ : R} {k : ℕ} {x : L} :
MapsTo ((toEndomorphism R L M x - algebraMap R (Module.End R M) φ) ^ k) N N := by
| Mathlib.Algebra.Lie.OfAssociative.299_0.ll51mLev4p7Z1wP | lemma mapsTo_pow_toEndomorphism_sub_algebraMap {φ : R} {k : ℕ} {x : L} :
MapsTo ((toEndomorphism R L M x - algebraMap R (Module.End R M) φ) ^ k) N N | Mathlib_Algebra_Lie_OfAssociative |
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
N : LieSubmodule R L M
x✝ : L
φ : R
k : ℕ
x : L
⊢ MapsTo (⇑((toEndomorphism R L M) x - (algebraMap R (Module.End R M)) φ))^[k] ↑N ↑N | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEndomorphism_module_end
theorem LieSubalgebra.toEndomorphism_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEndomorphism R K M x = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEndomorphism_eq
@[simp]
theorem LieSubalgebra.toEndomorphism_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEndomorphism R K M ⟨x, hx⟩ = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEndomorphism_mk
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
ext
simp
lemma toEndomorphism_pow_apply_map (m : M) :
(toEndomorphism R L M₂ x ^ k) (f m) = f ((toEndomorphism R L M x ^ k) m) :=
LinearMap.congr_fun (toEndomorphism_pow_comp_lieHom f k x) m
end LieModule
namespace LieSubmodule
open LieModule Set
variable {N : LieSubmodule R L M} {x : L}
theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N := by
rintro n ⟨m, hm, rfl⟩
exact N.lie_mem hm
#align lie_submodule.coe_map_to_endomorphism_le LieSubmodule.coe_map_toEndomorphism_le
variable (N x)
theorem toEndomorphism_comp_subtype_mem (m : M) (hm : m ∈ (N : Submodule R M)) :
(toEndomorphism R L M x).comp (N : Submodule R M).subtype ⟨m, hm⟩ ∈ (N : Submodule R M) := by
simpa using N.lie_mem hm
#align lie_submodule.to_endomorphism_comp_subtype_mem LieSubmodule.toEndomorphism_comp_subtype_mem
@[simp]
theorem toEndomorphism_restrict_eq_toEndomorphism (h := N.toEndomorphism_comp_subtype_mem x) :
(toEndomorphism R L M x).restrict h = toEndomorphism R L N x := by
ext; simp [LinearMap.restrict_apply]
#align lie_submodule.to_endomorphism_restrict_eq_to_endomorphism LieSubmodule.toEndomorphism_restrict_eq_toEndomorphism
lemma mapsTo_pow_toEndomorphism_sub_algebraMap {φ : R} {k : ℕ} {x : L} :
MapsTo ((toEndomorphism R L M x - algebraMap R (Module.End R M) φ) ^ k) N N := by
rw [LinearMap.coe_pow]
| exact MapsTo.iterate (fun m hm ↦ N.sub_mem (N.lie_mem hm) (N.smul_mem _ hm)) k | lemma mapsTo_pow_toEndomorphism_sub_algebraMap {φ : R} {k : ℕ} {x : L} :
MapsTo ((toEndomorphism R L M x - algebraMap R (Module.End R M) φ) ^ k) N N := by
rw [LinearMap.coe_pow]
| Mathlib.Algebra.Lie.OfAssociative.299_0.ll51mLev4p7Z1wP | lemma mapsTo_pow_toEndomorphism_sub_algebraMap {φ : R} {k : ℕ} {x : L} :
MapsTo ((toEndomorphism R L M x - algebraMap R (Module.End R M) φ) ^ k) N N | Mathlib_Algebra_Lie_OfAssociative |
R : Type u
L : Type v
M : Type w
inst✝⁸ : CommRing R
inst✝⁷ : LieRing L
inst✝⁶ : LieAlgebra R L
inst✝⁵ : AddCommGroup M
inst✝⁴ : Module R M
inst✝³ : LieRingModule L M
inst✝² : LieModule R L M
A : Type v
inst✝¹ : Ring A
inst✝ : Algebra R A
⊢ ⇑(ad R A) = LinearMap.mulLeft R - LinearMap.mulRight R | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEndomorphism_module_end
theorem LieSubalgebra.toEndomorphism_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEndomorphism R K M x = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEndomorphism_eq
@[simp]
theorem LieSubalgebra.toEndomorphism_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEndomorphism R K M ⟨x, hx⟩ = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEndomorphism_mk
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
ext
simp
lemma toEndomorphism_pow_apply_map (m : M) :
(toEndomorphism R L M₂ x ^ k) (f m) = f ((toEndomorphism R L M x ^ k) m) :=
LinearMap.congr_fun (toEndomorphism_pow_comp_lieHom f k x) m
end LieModule
namespace LieSubmodule
open LieModule Set
variable {N : LieSubmodule R L M} {x : L}
theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N := by
rintro n ⟨m, hm, rfl⟩
exact N.lie_mem hm
#align lie_submodule.coe_map_to_endomorphism_le LieSubmodule.coe_map_toEndomorphism_le
variable (N x)
theorem toEndomorphism_comp_subtype_mem (m : M) (hm : m ∈ (N : Submodule R M)) :
(toEndomorphism R L M x).comp (N : Submodule R M).subtype ⟨m, hm⟩ ∈ (N : Submodule R M) := by
simpa using N.lie_mem hm
#align lie_submodule.to_endomorphism_comp_subtype_mem LieSubmodule.toEndomorphism_comp_subtype_mem
@[simp]
theorem toEndomorphism_restrict_eq_toEndomorphism (h := N.toEndomorphism_comp_subtype_mem x) :
(toEndomorphism R L M x).restrict h = toEndomorphism R L N x := by
ext; simp [LinearMap.restrict_apply]
#align lie_submodule.to_endomorphism_restrict_eq_to_endomorphism LieSubmodule.toEndomorphism_restrict_eq_toEndomorphism
lemma mapsTo_pow_toEndomorphism_sub_algebraMap {φ : R} {k : ℕ} {x : L} :
MapsTo ((toEndomorphism R L M x - algebraMap R (Module.End R M) φ) ^ k) N N := by
rw [LinearMap.coe_pow]
exact MapsTo.iterate (fun m hm ↦ N.sub_mem (N.lie_mem hm) (N.smul_mem _ hm)) k
end LieSubmodule
open LieAlgebra
theorem LieAlgebra.ad_eq_lmul_left_sub_lmul_right (A : Type v) [Ring A] [Algebra R A] :
(ad R A : A → Module.End R A) = LinearMap.mulLeft R - LinearMap.mulRight R := by
| ext a b | theorem LieAlgebra.ad_eq_lmul_left_sub_lmul_right (A : Type v) [Ring A] [Algebra R A] :
(ad R A : A → Module.End R A) = LinearMap.mulLeft R - LinearMap.mulRight R := by
| Mathlib.Algebra.Lie.OfAssociative.308_0.ll51mLev4p7Z1wP | theorem LieAlgebra.ad_eq_lmul_left_sub_lmul_right (A : Type v) [Ring A] [Algebra R A] :
(ad R A : A → Module.End R A) = LinearMap.mulLeft R - LinearMap.mulRight R | Mathlib_Algebra_Lie_OfAssociative |
case h.h
R : Type u
L : Type v
M : Type w
inst✝⁸ : CommRing R
inst✝⁷ : LieRing L
inst✝⁶ : LieAlgebra R L
inst✝⁵ : AddCommGroup M
inst✝⁴ : Module R M
inst✝³ : LieRingModule L M
inst✝² : LieModule R L M
A : Type v
inst✝¹ : Ring A
inst✝ : Algebra R A
a b : A
⊢ ((ad R A) a) b = ((LinearMap.mulLeft R - LinearMap.mulRight R) a) b | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEndomorphism_module_end
theorem LieSubalgebra.toEndomorphism_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEndomorphism R K M x = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEndomorphism_eq
@[simp]
theorem LieSubalgebra.toEndomorphism_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEndomorphism R K M ⟨x, hx⟩ = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEndomorphism_mk
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
ext
simp
lemma toEndomorphism_pow_apply_map (m : M) :
(toEndomorphism R L M₂ x ^ k) (f m) = f ((toEndomorphism R L M x ^ k) m) :=
LinearMap.congr_fun (toEndomorphism_pow_comp_lieHom f k x) m
end LieModule
namespace LieSubmodule
open LieModule Set
variable {N : LieSubmodule R L M} {x : L}
theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N := by
rintro n ⟨m, hm, rfl⟩
exact N.lie_mem hm
#align lie_submodule.coe_map_to_endomorphism_le LieSubmodule.coe_map_toEndomorphism_le
variable (N x)
theorem toEndomorphism_comp_subtype_mem (m : M) (hm : m ∈ (N : Submodule R M)) :
(toEndomorphism R L M x).comp (N : Submodule R M).subtype ⟨m, hm⟩ ∈ (N : Submodule R M) := by
simpa using N.lie_mem hm
#align lie_submodule.to_endomorphism_comp_subtype_mem LieSubmodule.toEndomorphism_comp_subtype_mem
@[simp]
theorem toEndomorphism_restrict_eq_toEndomorphism (h := N.toEndomorphism_comp_subtype_mem x) :
(toEndomorphism R L M x).restrict h = toEndomorphism R L N x := by
ext; simp [LinearMap.restrict_apply]
#align lie_submodule.to_endomorphism_restrict_eq_to_endomorphism LieSubmodule.toEndomorphism_restrict_eq_toEndomorphism
lemma mapsTo_pow_toEndomorphism_sub_algebraMap {φ : R} {k : ℕ} {x : L} :
MapsTo ((toEndomorphism R L M x - algebraMap R (Module.End R M) φ) ^ k) N N := by
rw [LinearMap.coe_pow]
exact MapsTo.iterate (fun m hm ↦ N.sub_mem (N.lie_mem hm) (N.smul_mem _ hm)) k
end LieSubmodule
open LieAlgebra
theorem LieAlgebra.ad_eq_lmul_left_sub_lmul_right (A : Type v) [Ring A] [Algebra R A] :
(ad R A : A → Module.End R A) = LinearMap.mulLeft R - LinearMap.mulRight R := by
ext a b; | simp [LieRing.of_associative_ring_bracket] | theorem LieAlgebra.ad_eq_lmul_left_sub_lmul_right (A : Type v) [Ring A] [Algebra R A] :
(ad R A : A → Module.End R A) = LinearMap.mulLeft R - LinearMap.mulRight R := by
ext a b; | Mathlib.Algebra.Lie.OfAssociative.308_0.ll51mLev4p7Z1wP | theorem LieAlgebra.ad_eq_lmul_left_sub_lmul_right (A : Type v) [Ring A] [Algebra R A] :
(ad R A : A → Module.End R A) = LinearMap.mulLeft R - LinearMap.mulRight R | Mathlib_Algebra_Lie_OfAssociative |
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
K : LieSubalgebra R L
x : ↥K
⊢ (ad R L) ↑x ∘ₗ ↑(incl K) = ↑(incl K) ∘ₗ (ad R ↥K) x | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEndomorphism_module_end
theorem LieSubalgebra.toEndomorphism_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEndomorphism R K M x = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEndomorphism_eq
@[simp]
theorem LieSubalgebra.toEndomorphism_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEndomorphism R K M ⟨x, hx⟩ = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEndomorphism_mk
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
ext
simp
lemma toEndomorphism_pow_apply_map (m : M) :
(toEndomorphism R L M₂ x ^ k) (f m) = f ((toEndomorphism R L M x ^ k) m) :=
LinearMap.congr_fun (toEndomorphism_pow_comp_lieHom f k x) m
end LieModule
namespace LieSubmodule
open LieModule Set
variable {N : LieSubmodule R L M} {x : L}
theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N := by
rintro n ⟨m, hm, rfl⟩
exact N.lie_mem hm
#align lie_submodule.coe_map_to_endomorphism_le LieSubmodule.coe_map_toEndomorphism_le
variable (N x)
theorem toEndomorphism_comp_subtype_mem (m : M) (hm : m ∈ (N : Submodule R M)) :
(toEndomorphism R L M x).comp (N : Submodule R M).subtype ⟨m, hm⟩ ∈ (N : Submodule R M) := by
simpa using N.lie_mem hm
#align lie_submodule.to_endomorphism_comp_subtype_mem LieSubmodule.toEndomorphism_comp_subtype_mem
@[simp]
theorem toEndomorphism_restrict_eq_toEndomorphism (h := N.toEndomorphism_comp_subtype_mem x) :
(toEndomorphism R L M x).restrict h = toEndomorphism R L N x := by
ext; simp [LinearMap.restrict_apply]
#align lie_submodule.to_endomorphism_restrict_eq_to_endomorphism LieSubmodule.toEndomorphism_restrict_eq_toEndomorphism
lemma mapsTo_pow_toEndomorphism_sub_algebraMap {φ : R} {k : ℕ} {x : L} :
MapsTo ((toEndomorphism R L M x - algebraMap R (Module.End R M) φ) ^ k) N N := by
rw [LinearMap.coe_pow]
exact MapsTo.iterate (fun m hm ↦ N.sub_mem (N.lie_mem hm) (N.smul_mem _ hm)) k
end LieSubmodule
open LieAlgebra
theorem LieAlgebra.ad_eq_lmul_left_sub_lmul_right (A : Type v) [Ring A] [Algebra R A] :
(ad R A : A → Module.End R A) = LinearMap.mulLeft R - LinearMap.mulRight R := by
ext a b; simp [LieRing.of_associative_ring_bracket]
#align lie_algebra.ad_eq_lmul_left_sub_lmul_right LieAlgebra.ad_eq_lmul_left_sub_lmul_right
theorem LieSubalgebra.ad_comp_incl_eq (K : LieSubalgebra R L) (x : K) :
(ad R L ↑x).comp (K.incl : K →ₗ[R] L) = (K.incl : K →ₗ[R] L).comp (ad R K x) := by
| ext y | theorem LieSubalgebra.ad_comp_incl_eq (K : LieSubalgebra R L) (x : K) :
(ad R L ↑x).comp (K.incl : K →ₗ[R] L) = (K.incl : K →ₗ[R] L).comp (ad R K x) := by
| Mathlib.Algebra.Lie.OfAssociative.313_0.ll51mLev4p7Z1wP | theorem LieSubalgebra.ad_comp_incl_eq (K : LieSubalgebra R L) (x : K) :
(ad R L ↑x).comp (K.incl : K →ₗ[R] L) = (K.incl : K →ₗ[R] L).comp (ad R K x) | Mathlib_Algebra_Lie_OfAssociative |
case h
R : Type u
L : Type v
M : Type w
inst✝⁶ : CommRing R
inst✝⁵ : LieRing L
inst✝⁴ : LieAlgebra R L
inst✝³ : AddCommGroup M
inst✝² : Module R M
inst✝¹ : LieRingModule L M
inst✝ : LieModule R L M
K : LieSubalgebra R L
x y : ↥K
⊢ ((ad R L) ↑x ∘ₗ ↑(incl K)) y = (↑(incl K) ∘ₗ (ad R ↥K) x) y | /-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Algebra.Lie.Submodule
import Mathlib.Algebra.Algebra.Subalgebra.Basic
#align_import algebra.lie.of_associative from "leanprover-community/mathlib"@"f0f3d964763ecd0090c9eb3ae0d15871d08781c4"
/-!
# Lie algebras of associative algebras
This file defines the Lie algebra structure that arises on an associative algebra via the ring
commutator.
Since the linear endomorphisms of a Lie algebra form an associative algebra, one can define the
adjoint action as a morphism of Lie algebras from a Lie algebra to its linear endomorphisms. We
make such a definition in this file.
## Main definitions
* `LieAlgebra.ofAssociativeAlgebra`
* `LieAlgebra.ofAssociativeAlgebraHom`
* `LieModule.toEndomorphism`
* `LieAlgebra.ad`
* `LinearEquiv.lieConj`
* `AlgEquiv.toLieEquiv`
## Tags
lie algebra, ring commutator, adjoint action
-/
universe u v w w₁ w₂
section OfAssociative
variable {A : Type v} [Ring A]
namespace Ring
/-- The bracket operation for rings is the ring commutator, which captures the extent to which a
ring is commutative. It is identically zero exactly when the ring is commutative. -/
instance (priority := 100) instBracket : Bracket A A :=
⟨fun x y => x * y - y * x⟩
theorem lie_def (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align ring.lie_def Ring.lie_def
end Ring
theorem commute_iff_lie_eq {x y : A} : Commute x y ↔ ⁅x, y⁆ = 0 :=
sub_eq_zero.symm
#align commute_iff_lie_eq commute_iff_lie_eq
theorem Commute.lie_eq {x y : A} (h : Commute x y) : ⁅x, y⁆ = 0 :=
sub_eq_zero_of_eq h
#align commute.lie_eq Commute.lie_eq
namespace LieRing
/-- An associative ring gives rise to a Lie ring by taking the bracket to be the ring commutator. -/
instance (priority := 100) ofAssociativeRing : LieRing A where
add_lie _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_add _ _ _ := by simp only [Ring.lie_def, right_distrib, left_distrib]; abel
lie_self := by simp only [Ring.lie_def, forall_const, sub_self]
leibniz_lie _ _ _ := by
simp only [Ring.lie_def, mul_sub_left_distrib, mul_sub_right_distrib, mul_assoc]; abel
#align lie_ring.of_associative_ring LieRing.ofAssociativeRing
theorem of_associative_ring_bracket (x y : A) : ⁅x, y⁆ = x * y - y * x :=
rfl
#align lie_ring.of_associative_ring_bracket LieRing.of_associative_ring_bracket
@[simp]
theorem lie_apply {α : Type*} (f g : α → A) (a : α) : ⁅f, g⁆ a = ⁅f a, g a⁆ :=
rfl
#align lie_ring.lie_apply LieRing.lie_apply
end LieRing
section AssociativeModule
variable {M : Type w} [AddCommGroup M] [Module A M]
/-- We can regard a module over an associative ring `A` as a Lie ring module over `A` with Lie
bracket equal to its ring commutator.
Note that this cannot be a global instance because it would create a diamond when `M = A`,
specifically we can build two mathematically-different `bracket A A`s:
1. `@Ring.bracket A _` which says `⁅a, b⁆ = a * b - b * a`
2. `(@LieRingModule.ofAssociativeModule A _ A _ _).toBracket` which says `⁅a, b⁆ = a • b`
(and thus `⁅a, b⁆ = a * b`)
See note [reducible non-instances] -/
@[reducible]
def LieRingModule.ofAssociativeModule : LieRingModule A M where
bracket := (· • ·)
add_lie := add_smul
lie_add := smul_add
leibniz_lie := by simp [LieRing.of_associative_ring_bracket, sub_smul, mul_smul, sub_add_cancel]
#align lie_ring_module.of_associative_module LieRingModule.ofAssociativeModule
attribute [local instance] LieRingModule.ofAssociativeModule
theorem lie_eq_smul (a : A) (m : M) : ⁅a, m⁆ = a • m :=
rfl
#align lie_eq_smul lie_eq_smul
end AssociativeModule
section LieAlgebra
variable {R : Type u} [CommRing R] [Algebra R A]
/-- An associative algebra gives rise to a Lie algebra by taking the bracket to be the ring
commutator. -/
instance (priority := 100) LieAlgebra.ofAssociativeAlgebra : LieAlgebra R A where
lie_smul t x y := by
rw [LieRing.of_associative_ring_bracket, LieRing.of_associative_ring_bracket,
Algebra.mul_smul_comm, Algebra.smul_mul_assoc, smul_sub]
#align lie_algebra.of_associative_algebra LieAlgebra.ofAssociativeAlgebra
attribute [local instance] LieRingModule.ofAssociativeModule
section AssociativeRepresentation
variable {M : Type w} [AddCommGroup M] [Module R M] [Module A M] [IsScalarTower R A M]
/-- A representation of an associative algebra `A` is also a representation of `A`, regarded as a
Lie algebra via the ring commutator.
See the comment at `LieRingModule.ofAssociativeModule` for why the possibility `M = A` means
this cannot be a global instance. -/
theorem LieModule.ofAssociativeModule : LieModule R A M where
smul_lie := smul_assoc
lie_smul := smul_algebra_smul_comm
#align lie_module.of_associative_module LieModule.ofAssociativeModule
instance Module.End.lieRingModule : LieRingModule (Module.End R M) M :=
LieRingModule.ofAssociativeModule
#align module.End.lie_ring_module Module.End.lieRingModule
instance Module.End.lieModule : LieModule R (Module.End R M) M :=
LieModule.ofAssociativeModule
#align module.End.lie_module Module.End.lieModule
end AssociativeRepresentation
namespace AlgHom
variable {B : Type w} {C : Type w₁} [Ring B] [Ring C] [Algebra R B] [Algebra R C]
variable (f : A →ₐ[R] B) (g : B →ₐ[R] C)
/-- The map `ofAssociativeAlgebra` associating a Lie algebra to an associative algebra is
functorial. -/
def toLieHom : A →ₗ⁅R⁆ B :=
{ f.toLinearMap with
map_lie' := fun {_ _} => by simp [LieRing.of_associative_ring_bracket] }
#align alg_hom.to_lie_hom AlgHom.toLieHom
instance : Coe (A →ₐ[R] B) (A →ₗ⁅R⁆ B) :=
⟨toLieHom⟩
/- Porting note: is a syntactic tautology
@[simp]
theorem toLieHom_coe : f.toLieHom = ↑f :=
rfl
-/
#noalign alg_hom.to_lie_hom_coe
@[simp]
theorem coe_toLieHom : ((f : A →ₗ⁅R⁆ B) : A → B) = f :=
rfl
#align alg_hom.coe_to_lie_hom AlgHom.coe_toLieHom
theorem toLieHom_apply (x : A) : f.toLieHom x = f x :=
rfl
#align alg_hom.to_lie_hom_apply AlgHom.toLieHom_apply
@[simp]
theorem toLieHom_id : (AlgHom.id R A : A →ₗ⁅R⁆ A) = LieHom.id :=
rfl
#align alg_hom.to_lie_hom_id AlgHom.toLieHom_id
@[simp]
theorem toLieHom_comp : (g.comp f : A →ₗ⁅R⁆ C) = (g : B →ₗ⁅R⁆ C).comp (f : A →ₗ⁅R⁆ B) :=
rfl
#align alg_hom.to_lie_hom_comp AlgHom.toLieHom_comp
theorem toLieHom_injective {f g : A →ₐ[R] B} (h : (f : A →ₗ⁅R⁆ B) = (g : A →ₗ⁅R⁆ B)) : f = g := by
ext a; exact LieHom.congr_fun h a
#align alg_hom.to_lie_hom_injective AlgHom.toLieHom_injective
end AlgHom
end LieAlgebra
end OfAssociative
section AdjointAction
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie module yields a Lie algebra morphism into the linear endomorphisms of the module.
See also `LieModule.toModuleHom`. -/
@[simps]
def LieModule.toEndomorphism : L →ₗ⁅R⁆ Module.End R M where
toFun x :=
{ toFun := fun m => ⁅x, m⁆
map_add' := lie_add x
map_smul' := fun t => lie_smul t x }
map_add' x y := by ext m; apply add_lie
map_smul' t x := by ext m; apply smul_lie
map_lie' {x y} := by ext m; apply lie_lie
#align lie_module.to_endomorphism LieModule.toEndomorphism
/-- The adjoint action of a Lie algebra on itself. -/
def LieAlgebra.ad : L →ₗ⁅R⁆ Module.End R L :=
LieModule.toEndomorphism R L L
#align lie_algebra.ad LieAlgebra.ad
@[simp]
theorem LieAlgebra.ad_apply (x y : L) : LieAlgebra.ad R L x y = ⁅x, y⁆ :=
rfl
#align lie_algebra.ad_apply LieAlgebra.ad_apply
@[simp]
theorem LieModule.toEndomorphism_module_end :
LieModule.toEndomorphism R (Module.End R M) M = LieHom.id := by ext g m; simp [lie_eq_smul]
#align lie_module.to_endomorphism_module_End LieModule.toEndomorphism_module_end
theorem LieSubalgebra.toEndomorphism_eq (K : LieSubalgebra R L) {x : K} :
LieModule.toEndomorphism R K M x = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_eq LieSubalgebra.toEndomorphism_eq
@[simp]
theorem LieSubalgebra.toEndomorphism_mk (K : LieSubalgebra R L) {x : L} (hx : x ∈ K) :
LieModule.toEndomorphism R K M ⟨x, hx⟩ = LieModule.toEndomorphism R L M x :=
rfl
#align lie_subalgebra.to_endomorphism_mk LieSubalgebra.toEndomorphism_mk
variable {R L M}
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
(f : M →ₗ⁅R,L⁆ M₂) (k : ℕ) (x : L)
lemma toEndomorphism_pow_comp_lieHom :
(toEndomorphism R L M₂ x ^ k) ∘ₗ f = f ∘ₗ toEndomorphism R L M x ^ k := by
apply LinearMap.commute_pow_left_of_commute
ext
simp
lemma toEndomorphism_pow_apply_map (m : M) :
(toEndomorphism R L M₂ x ^ k) (f m) = f ((toEndomorphism R L M x ^ k) m) :=
LinearMap.congr_fun (toEndomorphism_pow_comp_lieHom f k x) m
end LieModule
namespace LieSubmodule
open LieModule Set
variable {N : LieSubmodule R L M} {x : L}
theorem coe_map_toEndomorphism_le :
(N : Submodule R M).map (LieModule.toEndomorphism R L M x) ≤ N := by
rintro n ⟨m, hm, rfl⟩
exact N.lie_mem hm
#align lie_submodule.coe_map_to_endomorphism_le LieSubmodule.coe_map_toEndomorphism_le
variable (N x)
theorem toEndomorphism_comp_subtype_mem (m : M) (hm : m ∈ (N : Submodule R M)) :
(toEndomorphism R L M x).comp (N : Submodule R M).subtype ⟨m, hm⟩ ∈ (N : Submodule R M) := by
simpa using N.lie_mem hm
#align lie_submodule.to_endomorphism_comp_subtype_mem LieSubmodule.toEndomorphism_comp_subtype_mem
@[simp]
theorem toEndomorphism_restrict_eq_toEndomorphism (h := N.toEndomorphism_comp_subtype_mem x) :
(toEndomorphism R L M x).restrict h = toEndomorphism R L N x := by
ext; simp [LinearMap.restrict_apply]
#align lie_submodule.to_endomorphism_restrict_eq_to_endomorphism LieSubmodule.toEndomorphism_restrict_eq_toEndomorphism
lemma mapsTo_pow_toEndomorphism_sub_algebraMap {φ : R} {k : ℕ} {x : L} :
MapsTo ((toEndomorphism R L M x - algebraMap R (Module.End R M) φ) ^ k) N N := by
rw [LinearMap.coe_pow]
exact MapsTo.iterate (fun m hm ↦ N.sub_mem (N.lie_mem hm) (N.smul_mem _ hm)) k
end LieSubmodule
open LieAlgebra
theorem LieAlgebra.ad_eq_lmul_left_sub_lmul_right (A : Type v) [Ring A] [Algebra R A] :
(ad R A : A → Module.End R A) = LinearMap.mulLeft R - LinearMap.mulRight R := by
ext a b; simp [LieRing.of_associative_ring_bracket]
#align lie_algebra.ad_eq_lmul_left_sub_lmul_right LieAlgebra.ad_eq_lmul_left_sub_lmul_right
theorem LieSubalgebra.ad_comp_incl_eq (K : LieSubalgebra R L) (x : K) :
(ad R L ↑x).comp (K.incl : K →ₗ[R] L) = (K.incl : K →ₗ[R] L).comp (ad R K x) := by
ext y
| simp only [ad_apply, LieHom.coe_toLinearMap, LieSubalgebra.coe_incl, LinearMap.coe_comp,
LieSubalgebra.coe_bracket, Function.comp_apply] | theorem LieSubalgebra.ad_comp_incl_eq (K : LieSubalgebra R L) (x : K) :
(ad R L ↑x).comp (K.incl : K →ₗ[R] L) = (K.incl : K →ₗ[R] L).comp (ad R K x) := by
ext y
| Mathlib.Algebra.Lie.OfAssociative.313_0.ll51mLev4p7Z1wP | theorem LieSubalgebra.ad_comp_incl_eq (K : LieSubalgebra R L) (x : K) :
(ad R L ↑x).comp (K.incl : K →ₗ[R] L) = (K.incl : K →ₗ[R] L).comp (ad R K x) | Mathlib_Algebra_Lie_OfAssociative |
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