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|---|---|---|---|---|---|---|
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
M N : Matrix n n R
x✝³ x✝² : n → n
x✝¹ : x✝³ ∈ filter Bijective univ
x✝ : x✝² ∈ filter Bijective univ
h : (fun p h => ofBijective p (_ : Bijective p)) x✝³ x✝¹ = (fun p h => ofBijective p (_ : Bijective p)) x✝² x✝
⊢ x✝³ = x✝² | /-
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 | @[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 | Mathlib.LinearAlgebra.Matrix.Determinant.150_0.U1f6HO8zRbnvZ95 | @[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N | 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
M N : Matrix n n R
⊢ ∑ τ : Perm n, ∑ σ : Perm n, ↑↑(sign σ) * ∏ i : n, M (σ i) (τ i) * N (τ i) i =
∑ σ : Perm n, ∑ τ : Perm n, (∏ i : n, N (σ i) i) * ↑↑(sign τ) * ∏ j : n, M (τ j) (σ 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] | @[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
| Mathlib.LinearAlgebra.Matrix.Determinant.150_0.U1f6HO8zRbnvZ95 | @[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N | 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
M N : Matrix n n R
σ : Perm n
x✝ : σ ∈ univ
τ : Perm n
⊢ (∏ i : n, N (σ i) i) * ↑↑(sign τ) * ∏ j : n, M (τ j) (σ j) =
(∏ i : n, N (σ i) i) * (↑↑(sign σ) * ↑↑(sign ((Equiv.mulRight σ⁻¹) τ))) * ∏ i : n, M (((Equiv.mulRight σ⁻¹) τ) i) 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] | @[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
| Mathlib.LinearAlgebra.Matrix.Determinant.150_0.U1f6HO8zRbnvZ95 | @[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N | 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
M N : Matrix n n R
σ : Perm n
x✝ : σ ∈ univ
τ : Perm n
⊢ ∏ j : n, M (τ j) (σ j) = ∏ j : n, M ((τ * σ⁻¹) 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]
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
| Mathlib.LinearAlgebra.Matrix.Determinant.150_0.U1f6HO8zRbnvZ95 | @[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N | 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
M N : Matrix n n R
σ : Perm n
x✝ : σ ∈ univ
τ : Perm n
⊢ ∏ i : n, M (τ (σ⁻¹ i)) (σ (σ⁻¹ i)) = ∏ j : n, M ((τ * σ⁻¹) 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] | @[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]
| Mathlib.LinearAlgebra.Matrix.Determinant.150_0.U1f6HO8zRbnvZ95 | @[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N | 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
M N : Matrix n n R
σ : Perm n
x✝ : σ ∈ univ
τ : Perm n
this : ∏ j : n, M (τ j) (σ j) = ∏ j : n, M ((τ * σ⁻¹) j) j
⊢ (∏ i : n, N (σ i) i) * ↑↑(sign τ) * ∏ j : n, M (τ j) (σ j) =
(∏ i : n, N (σ i) i) * (↑↑(sign σ) * ↑↑(sign ((Equiv.mulRight σ⁻¹) τ))) * ∏ i : n, M (((Equiv.mulRight σ⁻¹) τ) i) 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]
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]
| Mathlib.LinearAlgebra.Matrix.Determinant.150_0.U1f6HO8zRbnvZ95 | @[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N | 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
M N : Matrix n n R
σ : Perm n
x✝ : σ ∈ univ
τ : Perm n
this : ∏ j : n, M (τ j) (σ j) = ∏ j : n, M ((τ * σ⁻¹) j) j
⊢ ↑↑(sign σ) * ↑↑(sign (τ * σ⁻¹)) = ↑↑(sign (τ * σ⁻¹ * σ)) | /-
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]
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
| Mathlib.LinearAlgebra.Matrix.Determinant.150_0.U1f6HO8zRbnvZ95 | @[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N | 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
M N : Matrix n n R
σ : Perm n
x✝ : σ ∈ univ
τ : Perm n
this : ∏ j : n, M (τ j) (σ j) = ∏ j : n, M ((τ * σ⁻¹) j) j
⊢ ↑↑(sign (τ * σ⁻¹)) * ↑↑(sign σ) = ↑↑(sign (τ * σ⁻¹) * sign σ) | /-
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] | @[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)]
| Mathlib.LinearAlgebra.Matrix.Determinant.150_0.U1f6HO8zRbnvZ95 | @[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N | 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
M N : Matrix n n R
σ : Perm n
x✝ : σ ∈ univ
τ : Perm n
this : ∏ j : n, M (τ j) (σ j) = ∏ j : n, M ((τ * σ⁻¹) j) j
⊢ ↑↑(sign (τ * σ⁻¹ * σ)) = ↑↑(sign τ) | /-
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]
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 | Mathlib.LinearAlgebra.Matrix.Determinant.150_0.U1f6HO8zRbnvZ95 | @[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N | 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
M N : Matrix n n R
σ : Perm n
x✝ : σ ∈ univ
τ : Perm n
this : ∏ j : n, M (τ j) (σ j) = ∏ j : n, M ((τ * σ⁻¹) j) j
h : ↑↑(sign σ) * ↑↑(sign (τ * σ⁻¹)) = ↑↑(sign τ)
⊢ (∏ i : n, N (σ i) i) * ↑↑(sign τ) * ∏ j : n, M (τ j) (σ j) =
(∏ i : n, N (σ i) i) * (↑↑(sign σ) * ↑↑(sign ((Equiv.mulRight σ⁻¹) τ))) * ∏ i : n, M (((Equiv.mulRight σ⁻¹) τ) i) 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]
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]
| Mathlib.LinearAlgebra.Matrix.Determinant.150_0.U1f6HO8zRbnvZ95 | @[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N | 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
M N : Matrix n n R
σ : Perm n
x✝ : σ ∈ univ
τ : Perm n
this : ∏ j : n, M (τ j) (σ j) = ∏ j : n, M ((τ * σ⁻¹) j) j
h : ↑↑(sign σ) * ↑↑(sign (τ * σ⁻¹)) = ↑↑(sign τ)
⊢ (∏ i : n, N (σ i) i) * ↑↑(sign τ) * ∏ j : n, M (τ j) (σ j) =
(∏ i : n, N (σ i) i) * ↑↑(sign τ) * ∏ x : n, M ((τ * σ⁻¹) x) 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] | @[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]
| Mathlib.LinearAlgebra.Matrix.Determinant.150_0.U1f6HO8zRbnvZ95 | @[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N | 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
M N : Matrix n n R
⊢ ∑ σ : Perm n, ∑ τ : Perm n, (∏ i : n, N (σ i) i) * (↑↑(sign σ) * ↑↑(sign τ)) * ∏ i : n, M (τ i) i = det M * det N | /-
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] | @[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
| Mathlib.LinearAlgebra.Matrix.Determinant.150_0.U1f6HO8zRbnvZ95 | @[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N | 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
M N : Matrix m m R
⊢ det (M * N) = det (N * M) | /-
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] | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.199_0.U1f6HO8zRbnvZ95 | /-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) | 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
M N P : Matrix m m R
⊢ det (M * (N * P)) = det (N * (M * P)) | /-
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] | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.204_0.U1f6HO8zRbnvZ95 | /-- 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)) | 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
M N P : Matrix m m R
⊢ det (M * N * P) = det (M * P * N) | /-
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] | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.209_0.U1f6HO8zRbnvZ95 | /-- 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) | 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
M : (Matrix m m R)ˣ
N : Matrix m m R
⊢ det (↑M * N * ↑M⁻¹) = det N | /-
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] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.215_0.U1f6HO8zRbnvZ95 | theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det ((M : Matrix _ _ _) * N * (↑M⁻¹ : Matrix _ _ _)) = det N | 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
M : Matrix n n R
⊢ det Mᵀ = det M | /-
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'] | /-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
| Mathlib.LinearAlgebra.Matrix.Determinant.226_0.U1f6HO8zRbnvZ95 | /-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.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
M : Matrix n n R
⊢ ∑ σ : Perm n, ↑↑(sign σ) * ∏ i : n, Mᵀ (σ i) i = ∑ σ : Perm n, ↑↑(sign σ) * ∏ i : n, M (σ i) 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 _ _ _ | /-- 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']
| Mathlib.LinearAlgebra.Matrix.Determinant.226_0.U1f6HO8zRbnvZ95 | /-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.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
M : Matrix n n R
⊢ ∀ (x : Perm n), ↑↑(sign x) * ∏ i : n, Mᵀ (x i) i = ↑↑(sign x⁻¹) * ∏ i : n, M (x⁻¹ i) 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 | /-- 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 _ _ _
| Mathlib.LinearAlgebra.Matrix.Determinant.226_0.U1f6HO8zRbnvZ95 | /-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.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
M : Matrix n n R
σ : Perm n
⊢ ↑↑(sign σ) * ∏ i : n, Mᵀ (σ i) i = ↑↑(sign σ⁻¹) * ∏ i : n, M (σ⁻¹ i) 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] | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.226_0.U1f6HO8zRbnvZ95 | /-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.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
M : Matrix n n R
σ : Perm n
⊢ ↑↑(sign σ) * ∏ i : n, Mᵀ (σ i) i = ↑↑(sign σ) * ∏ i : n, M (σ⁻¹ i) 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 | /-- 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]
| Mathlib.LinearAlgebra.Matrix.Determinant.226_0.U1f6HO8zRbnvZ95 | /-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det | 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
M : Matrix n n R
σ : Perm n
⊢ ∏ i : n, Mᵀ (σ i) i = ∏ i : n, M (σ⁻¹ i) 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 | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.226_0.U1f6HO8zRbnvZ95 | /-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case e_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
M : Matrix n n R
σ : Perm n
⊢ ∀ (x : n), Mᵀ (σ x) x = M (σ⁻¹ (σ x)) (σ 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 | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.226_0.U1f6HO8zRbnvZ95 | /-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det | Mathlib_LinearAlgebra_Matrix_Determinant |
case e_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
M : Matrix n n R
σ : Perm n
x✝ : n
⊢ Mᵀ (σ x✝) x✝ = M (σ⁻¹ (σ x✝)) (σ 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 | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.226_0.U1f6HO8zRbnvZ95 | /-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.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
σ : Perm n
M : Matrix n n R
⊢ sign σ • detRowAlternating M = ↑↑(sign σ) * det M | /-
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] | /-- 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 | Mathlib.LinearAlgebra.Matrix.Determinant.239_0.U1f6HO8zRbnvZ95 | /-- 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 | 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
e : n ≃ m
A : Matrix m m R
⊢ det (submatrix A ⇑e ⇑e) = 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'] | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.245_0.U1f6HO8zRbnvZ95 | /-- 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 | 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
e : n ≃ m
A : Matrix m m R
⊢ ∑ σ : Perm n, ↑↑(sign σ) * ∏ i : n, submatrix A (⇑e) (⇑e) (σ i) i = ∑ σ : Perm m, ↑↑(sign σ) * ∏ i : m, A (σ i) 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) | /-- 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']
| Mathlib.LinearAlgebra.Matrix.Determinant.245_0.U1f6HO8zRbnvZ95 | /-- 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 | 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
e : n ≃ m
A : Matrix m m R
⊢ ∀ (x : Perm n),
↑↑(sign x) * ∏ i : n, submatrix A (⇑e) (⇑e) (x i) i =
↑↑(sign ((permCongr e) x)) * ∏ i : m, A (((permCongr e) x) i) 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 | /-- 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)
| Mathlib.LinearAlgebra.Matrix.Determinant.245_0.U1f6HO8zRbnvZ95 | /-- 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 | 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
e : n ≃ m
A : Matrix m m R
σ : Perm n
⊢ ↑↑(sign σ) * ∏ i : n, submatrix A (⇑e) (⇑e) (σ i) i = ↑↑(sign ((permCongr e) σ)) * ∏ i : m, A (((permCongr e) σ) i) 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] | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.245_0.U1f6HO8zRbnvZ95 | /-- 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 | 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
e : n ≃ m
A : Matrix m m R
σ : Perm n
⊢ ↑↑(sign σ) * ∏ i : n, submatrix A (⇑e) (⇑e) (σ i) i = ↑↑(sign σ) * ∏ i : m, A (((permCongr e) σ) i) 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 | /-- 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]
| Mathlib.LinearAlgebra.Matrix.Determinant.245_0.U1f6HO8zRbnvZ95 | /-- 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case h.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
e : n ≃ m
A : Matrix m m R
σ : Perm n
⊢ ∏ i : n, submatrix A (⇑e) (⇑e) (σ i) i = ∏ i : m, A (((permCongr e) σ) i) 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 | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.245_0.U1f6HO8zRbnvZ95 | /-- 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case h.e_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
e : n ≃ m
A : Matrix m m R
σ : Perm n
⊢ ∀ (x : n), submatrix A (⇑e) (⇑e) (σ x) x = A (((permCongr e) σ) (e x)) (e 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 | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.245_0.U1f6HO8zRbnvZ95 | /-- 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case h.e_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
e : n ≃ m
A : Matrix m m R
σ : Perm n
i : n
⊢ submatrix A (⇑e) (⇑e) (σ i) i = A (((permCongr e) σ) (e i)) (e 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] | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.245_0.U1f6HO8zRbnvZ95 | /-- 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 | 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
σ : Perm n
⊢ det (PEquiv.toMatrix (toPEquiv σ)) = ↑↑(sign σ) | /-
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] | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.268_0.U1f6HO8zRbnvZ95 | /-- 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 | 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 n n R
c : R
⊢ det (c • A) = det ((diagonal fun x => c) * 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] | 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 | Mathlib.LinearAlgebra.Matrix.Determinant.276_0.U1f6HO8zRbnvZ95 | theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A | 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 n n R
c : R
⊢ det (diagonal fun x => c) * det A = c ^ Fintype.card n * 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] | 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 | Mathlib.LinearAlgebra.Matrix.Determinant.276_0.U1f6HO8zRbnvZ95 | theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁸ : DecidableEq n
inst✝⁷ : Fintype n
inst✝⁶ : DecidableEq m
inst✝⁵ : Fintype m
R : Type v
inst✝⁴ : CommRing R
α : Type u_3
inst✝³ : Monoid α
inst✝² : DistribMulAction α R
inst✝¹ : IsScalarTower α R R
inst✝ : SMulCommClass α R R
c : α
A : Matrix n n R
⊢ det (c • A) = c ^ Fintype.card n • 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] | @[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 | Mathlib.LinearAlgebra.Matrix.Determinant.283_0.U1f6HO8zRbnvZ95 | @[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 | 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 n n R
⊢ det (-A) = (-1) ^ Fintype.card n * 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] | theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
| Mathlib.LinearAlgebra.Matrix.Determinant.289_0.U1f6HO8zRbnvZ95 | theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A | 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 n n R
⊢ det (-A) = (-1) ^ Fintype.card n • 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] | /-- 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 | Mathlib.LinearAlgebra.Matrix.Determinant.293_0.U1f6HO8zRbnvZ95 | /-- 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 | 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
v : n → R
A : Matrix n n R
⊢ (of fun i j => v j * A i j) = A * diagonal v | /-
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 | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.299_0.U1f6HO8zRbnvZ95 | /-- 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 | 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
v : n → R
A : Matrix n n R
i✝ x✝ : n
⊢ of (fun i j => v j * A i j) i✝ x✝ = (A * diagonal v) i✝ 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] | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.299_0.U1f6HO8zRbnvZ95 | /-- 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 | 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
v : n → R
A : Matrix n n R
⊢ det (A * diagonal v) = (∏ i : n, v 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] | /-- 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 | Mathlib.LinearAlgebra.Matrix.Determinant.299_0.U1f6HO8zRbnvZ95 | /-- 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
m : Type u_1
n : Type u_2
inst✝⁵ : DecidableEq n
inst✝⁴ : Fintype n
inst✝³ : DecidableEq m
inst✝² : Fintype m
R : Type v
inst✝¹ : CommRing R
S : Type w
inst✝ : CommRing S
f : R →+* S
M : Matrix n n R
⊢ f (det M) = det ((RingHom.mapMatrix f) M) | /-
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] | theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
by | Mathlib.LinearAlgebra.Matrix.Determinant.327_0.U1f6HO8zRbnvZ95 | theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) | 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 n n R
j : n
h : ∀ (i : n), A i j = 0
⊢ det 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] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.367_0.U1f6HO8zRbnvZ95 | theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 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 n n R
j : n
h : ∀ (i : n), A i j = 0
⊢ det Aᵀ = 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 | 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]
| Mathlib.LinearAlgebra.Matrix.Determinant.367_0.U1f6HO8zRbnvZ95 | theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 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
M : Matrix n n R
i j : n
i_ne_j : i ≠ j
hij : ∀ (k : n), M k i = M k j
⊢ det M = 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] | /-- 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
| Mathlib.LinearAlgebra.Matrix.Determinant.380_0.U1f6HO8zRbnvZ95 | /-- 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 | 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
M : Matrix n n R
i j : n
i_ne_j : i ≠ j
hij : ∀ (k : n), M k i = M k j
⊢ Mᵀ i = Mᵀ 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 | /-- 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]
| Mathlib.LinearAlgebra.Matrix.Determinant.380_0.U1f6HO8zRbnvZ95 | /-- 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 | 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
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) | /-
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] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.393_0.U1f6HO8zRbnvZ95 | 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) | 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
M : Matrix n n R
j : n
u v : n → R
⊢ det (updateRow Mᵀ j u) + det (updateRow Mᵀ j v) = det (updateColumn M j u) + det (updateColumn M j v) | /-
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] | 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]
| Mathlib.LinearAlgebra.Matrix.Determinant.393_0.U1f6HO8zRbnvZ95 | 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) | 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
M : Matrix n n R
j : n
s : R
u : n → R
⊢ det (updateColumn M j (s • u)) = s * det (updateColumn M j u) | /-
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] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.404_0.U1f6HO8zRbnvZ95 | 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) | 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
M : Matrix n n R
j : n
s : R
u : n → R
⊢ s * det (updateRow Mᵀ j u) = s * det (updateColumn M j u) | /-
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] | 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]
| Mathlib.LinearAlgebra.Matrix.Determinant.404_0.U1f6HO8zRbnvZ95 | 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) | 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
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) | /-
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'] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.415_0.U1f6HO8zRbnvZ95 | 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) | 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
M : Matrix n n R
j : n
s : R
u : n → R
⊢ s ^ (Fintype.card n - 1) * det (updateRow Mᵀ j u) = s ^ (Fintype.card n - 1) * det (updateColumn M j u) | /-
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] | 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']
| Mathlib.LinearAlgebra.Matrix.Determinant.415_0.U1f6HO8zRbnvZ95 | 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) | 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 B C : Matrix n n R
hC : det C = 1
hA : A = B * C
⊢ det B * det C = det B | /-
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] | 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 | Mathlib.LinearAlgebra.Matrix.Determinant.429_0.U1f6HO8zRbnvZ95 | 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 | 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 B C : Matrix n n R
hC : det C = 1
hA : A = C * B
⊢ det C * det B = det B | /-
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] | 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 | Mathlib.LinearAlgebra.Matrix.Determinant.437_0.U1f6HO8zRbnvZ95 | 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 | 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 n n R
i j : n
hij : i ≠ j
⊢ det (updateRow A i (A i + A j)) = 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)] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.445_0.U1f6HO8zRbnvZ95 | 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 | 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 n n R
i j : n
hij : i ≠ j
⊢ det (updateColumn A i fun k => A k i + A k j) = 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] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.451_0.U1f6HO8zRbnvZ95 | 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 | 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 n n R
i j : n
hij : i ≠ j
⊢ det (updateRow Aᵀ i fun k => A k i + A k j) = det Aᵀ | /-
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 | 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]
| Mathlib.LinearAlgebra.Matrix.Determinant.451_0.U1f6HO8zRbnvZ95 | 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 | 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 n n R
i j : n
hij : i ≠ j
c : R
⊢ det (updateRow A i (A i + c • A j)) = 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)] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.457_0.U1f6HO8zRbnvZ95 | 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 | 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 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 | /-
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] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.463_0.U1f6HO8zRbnvZ95 | 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 | 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 n n R
i j : n
hij : i ≠ j
c : R
⊢ det (updateRow Aᵀ i fun k => A k i + c • A k j) = det Aᵀ | /-
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 | 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]
| Mathlib.LinearAlgebra.Matrix.Determinant.463_0.U1f6HO8zRbnvZ95 | 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 | 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 B : Matrix n n R
s : Finset n
⊢ ∀ (c : n → R), (∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B | /-
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] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | 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 B : Matrix n n R
s : Finset n
⊢ ∀ (c : n → R), (∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B | /-
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] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case empty
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 B : Matrix n n R
⊢ ∀ (c : n → R), (∀ i ∉ ∅, c i = 0) → ∀ k ∉ ∅, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B | /-
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] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case empty
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 B : Matrix n n R
⊢ ∀ (c : n → R), (∀ i ∉ ∅, c i = 0) → ∀ k ∉ ∅, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B | /-
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 | 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 =>
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case empty
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 B : Matrix n n R
c : n → R
hs : ∀ i ∉ ∅, c i = 0
k : n
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
⊢ det A = det B | /-
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] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | 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 B : Matrix n n R
c : n → R
hs : ∀ i ∉ ∅, c i = 0
k : n
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
⊢ ∀ (i : n), c 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 | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | 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 B : Matrix n n R
c : n → R
hs : ∀ i ∉ ∅, c i = 0
k : n
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
i : n
⊢ c 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 | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | 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 B : Matrix n n R
c : n → R
k : n
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
i : n
hs : i ∉ ∅ → c i = 0
⊢ c 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 | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | 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 B : Matrix n n R
c : n → R
k : n
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
i : n
hs : c i ≠ 0
⊢ i ∉ ∅ ∧ c 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] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case empty
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 B : Matrix n n R
c : n → R
hs : ∀ i ∉ ∅, c i = 0
k : n
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
this : ∀ (i : n), c i = 0
⊢ det A = det B | /-
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 | 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]
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case empty.e_M
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 B : Matrix n n R
c : n → R
hs : ∀ i ∉ ∅, c i = 0
k : n
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
this : ∀ (i : n), c i = 0
⊢ A = B | /-
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 | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case empty.e_M.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 B : Matrix n n R
c : n → R
hs : ∀ i ∉ ∅, c i = 0
k : n
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
this : ∀ (i : n), c i = 0
i j : n
⊢ A i j = B i 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] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case insert
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
⊢ ∀ (c : n → R),
(∀ i_1 ∉ insert i s, c i_1 = 0) → ∀ k ∉ insert i s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B | /-
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] | 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]
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case insert
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
⊢ ∀ (c : n → R),
(∀ i_1 ∉ insert i s, c i_1 = 0) → ∀ k ∉ insert i s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B | /-
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 | 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 =>
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case insert
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
⊢ det A = det B | /-
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) | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case insert
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
hAi : A i = B i + c i • B k
⊢ det A = det B | /-
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] | 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)
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case insert.hij
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
hAi : A i = B i + c i • B k
⊢ i ≠ k | /-
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 | 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]
· | Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case insert.x
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
hAi : A i = B i + c i • B k
⊢ ∀ i_1 ∉ s, update c i 0 i_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' | 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
· | Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case insert.x
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
hAi : A i = B i + c i • B k
i' : n
hi' : i' ∉ s
⊢ update c i 0 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] | 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'
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case insert.x
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
hAi : A i = B i + c i • B k
i' : n
hi' : i' ∉ s
⊢ (if i' = i then 0 else c 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 | 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]
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case pos
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
hAi : A i = B i + c i • B k
i' : n
hi' : i' ∉ s
hi'i : i' = i
⊢ 0 = 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 | 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
· | Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case neg
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
hAi : A i = B i + c i • B k
i' : n
hi' : i' ∉ s
hi'i : ¬i' = i
⊢ c 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) | 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
· | Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case insert.k
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
hAi : A i = B i + c i • B k
⊢ n | /-
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 | 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)
· | Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case insert.x
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
hAi : A i = B i + c i • B k
⊢ k ∉ s | /-
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) | 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
· | Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case insert.x
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
hAi : A i = B i + c i • B k
⊢ ∀ (i_1 j : n), A i_1 j = updateRow B i (A i) i_1 j + update c i 0 i_1 * updateRow B i (A i) k 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' | 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)
· | Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case insert.x
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
hAi : A i = B i + c i • B k
i' j' : n
⊢ A i' j' = updateRow B i (A i) i' j' + update c i 0 i' * updateRow B i (A i) k 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] | 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'
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case insert.x
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
hAi : A i = B i + c i • B k
i' j' : n
⊢ A i' j' = (if i' = i then A i j' else B i' j') + (if i' = i then 0 else c i') * updateRow B i (A i) k 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 | 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]
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case pos
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
hAi : A i = B i + c i • B k
i' j' : n
hi'i : i' = i
⊢ A i' j' = A i j' + 0 * updateRow B i (A i) k 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] | 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
· | Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case neg
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 n n R
i : n
s : Finset n
_hi : i ∉ s
ih :
∀ {B : Matrix n n R} (c : n → R),
(∀ i ∉ s, c i = 0) → ∀ k ∉ s, (∀ (i j : n), A i j = B i j + c i * B k j) → det A = det B
B : Matrix n n R
c : n → R
hs : ∀ i_1 ∉ insert i s, c i_1 = 0
k : n
hk : k ∉ insert i s
A_eq : ∀ (i j : n), A i j = B i j + c i * B k j
hAi : A i = B i + c i • B k
i' j' : n
hi'i : ¬i' = i
⊢ A i' j' = B i' j' + c i' * updateRow B i (A i) k 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] | 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]
| Mathlib.LinearAlgebra.Matrix.Determinant.469_0.U1f6HO8zRbnvZ95 | 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 | 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
k : Fin (n + 1)
⊢ ∀ (c : Fin n → R),
(∀ (i : Fin n), k < Fin.succ i → c i = 0) →
∀ {M N : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R},
(∀ (j : Fin (Nat.succ n)), M 0 j = N 0 j) →
(∀ (i : Fin n) (j : Fin (Nat.succ n)), M (Fin.succ i) j = N (Fin.succ i) j + c i * M (Fin.castSucc i) j) →
det M = det N | /-
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 | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.513_0.U1f6HO8zRbnvZ95 | 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 | 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
k : Fin (n + 1)
⊢ ∀ (c : Fin n → R),
(∀ (i : Fin n), 0 < Fin.succ i → c i = 0) →
∀ {M N : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R},
(∀ (j : Fin (Nat.succ n)), M 0 j = N 0 j) →
(∀ (i : Fin n) (j : Fin (Nat.succ n)), M (Fin.succ i) j = N (Fin.succ i) j + c i * M (Fin.castSucc i) j) →
det M = det N | /-
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 | 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 <;> | Mathlib.LinearAlgebra.Matrix.Determinant.513_0.U1f6HO8zRbnvZ95 | 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 | 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
k✝ : Fin (n + 1)
k : Fin n
ih :
∀ (c : Fin n → R),
(∀ (i : Fin n), Fin.castSucc k < Fin.succ i → c i = 0) →
∀ {M N : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R},
(∀ (j : Fin (Nat.succ n)), M 0 j = N 0 j) →
(∀ (i : Fin n) (j : Fin (Nat.succ n)), M (Fin.succ i) j = N (Fin.succ i) j + c i * M (Fin.castSucc i) j) →
det M = det N
⊢ ∀ (c : Fin n → R),
(∀ (i : Fin n), Fin.succ k < Fin.succ i → c i = 0) →
∀ {M N : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R},
(∀ (j : Fin (Nat.succ n)), M 0 j = N 0 j) →
(∀ (i : Fin n) (j : Fin (Nat.succ n)), M (Fin.succ i) j = N (Fin.succ i) j + c i * M (Fin.castSucc i) j) →
det M = det N | /-
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 | 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 <;> | Mathlib.LinearAlgebra.Matrix.Determinant.513_0.U1f6HO8zRbnvZ95 | 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 | 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
k : Fin (n + 1)
c : Fin n → R
hc : ∀ (i : Fin n), 0 < Fin.succ i → c i = 0
M N : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
h0 : ∀ (j : Fin (Nat.succ n)), M 0 j = N 0 j
hsucc : ∀ (i : Fin n) (j : Fin (Nat.succ n)), M (Fin.succ i) j = N (Fin.succ i) j + c i * M (Fin.castSucc i) j
⊢ det M = det N | /-
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 | 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
· | Mathlib.LinearAlgebra.Matrix.Determinant.513_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case refine'_1.e_M
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
k : Fin (n + 1)
c : Fin n → R
hc : ∀ (i : Fin n), 0 < Fin.succ i → c i = 0
M N : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
h0 : ∀ (j : Fin (Nat.succ n)), M 0 j = N 0 j
hsucc : ∀ (i : Fin n) (j : Fin (Nat.succ n)), M (Fin.succ i) j = N (Fin.succ i) j + c i * M (Fin.castSucc i) j
⊢ M = N | /-
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 | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.513_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case refine'_1.e_M.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
n : ℕ
k : Fin (n + 1)
c : Fin n → R
hc : ∀ (i : Fin n), 0 < Fin.succ i → c i = 0
M N : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
h0 : ∀ (j : Fin (Nat.succ n)), M 0 j = N 0 j
hsucc : ∀ (i : Fin n) (j : Fin (Nat.succ n)), M (Fin.succ i) j = N (Fin.succ i) j + c i * M (Fin.castSucc i) j
i j : Fin (Nat.succ n)
⊢ M i j = N i 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 | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.513_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
case refine'_1.e_M.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
n : ℕ
k : Fin (n + 1)
c : Fin n → R
hc : ∀ (i : Fin n), 0 < Fin.succ i → c i = 0
M N : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
h0 : ∀ (j : Fin (Nat.succ n)), M 0 j = N 0 j
hsucc : ∀ (i : Fin n) (j : Fin (Nat.succ n)), M (Fin.succ i) j = N (Fin.succ i) j + c i * M (Fin.castSucc i) j
i✝ j : Fin (Nat.succ n)
i : Fin n
⊢ M (Fin.succ i) j = N (Fin.succ i) 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] | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.513_0.U1f6HO8zRbnvZ95 | 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 | 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
k✝ : Fin (n + 1)
k : Fin n
ih :
∀ (c : Fin n → R),
(∀ (i : Fin n), Fin.castSucc k < Fin.succ i → c i = 0) →
∀ {M N : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R},
(∀ (j : Fin (Nat.succ n)), M 0 j = N 0 j) →
(∀ (i : Fin n) (j : Fin (Nat.succ n)), M (Fin.succ i) j = N (Fin.succ i) j + c i * M (Fin.castSucc i) j) →
det M = det N
c : Fin n → R
hc : ∀ (i : Fin n), Fin.succ k < Fin.succ i → c i = 0
M N : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
h0 : ∀ (j : Fin (Nat.succ n)), M 0 j = N 0 j
hsucc : ∀ (i : Fin n) (j : Fin (Nat.succ n)), M (Fin.succ i) j = N (Fin.succ i) j + c i * M (Fin.castSucc i) j
⊢ det M = det N | /-
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' | 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]
| Mathlib.LinearAlgebra.Matrix.Determinant.513_0.U1f6HO8zRbnvZ95 | 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 | 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
k✝ : Fin (n + 1)
k : Fin n
ih :
∀ (c : Fin n → R),
(∀ (i : Fin n), Fin.castSucc k < Fin.succ i → c i = 0) →
∀ {M N : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R},
(∀ (j : Fin (Nat.succ n)), M 0 j = N 0 j) →
(∀ (i : Fin n) (j : Fin (Nat.succ n)), M (Fin.succ i) j = N (Fin.succ i) j + c i * M (Fin.castSucc i) j) →
det M = det N
c : Fin n → R
hc : ∀ (i : Fin n), Fin.succ k < Fin.succ i → c i = 0
M N : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
h0 : ∀ (j : Fin (Nat.succ n)), M 0 j = N 0 j
hsucc : ∀ (i : Fin n) (j : Fin (Nat.succ n)), M (Fin.succ i) j = N (Fin.succ i) j + c i * M (Fin.castSucc i) j
M' : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R := updateRow M (Fin.succ k) (N (Fin.succ k))
hM' : M' = updateRow M (Fin.succ k) (N (Fin.succ k))
⊢ det M = det N | /-
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] | 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'
| Mathlib.LinearAlgebra.Matrix.Determinant.513_0.U1f6HO8zRbnvZ95 | 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 | 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
k✝ : Fin (n + 1)
k : Fin n
ih :
∀ (c : Fin n → R),
(∀ (i : Fin n), Fin.castSucc k < Fin.succ i → c i = 0) →
∀ {M N : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R},
(∀ (j : Fin (Nat.succ n)), M 0 j = N 0 j) →
(∀ (i : Fin n) (j : Fin (Nat.succ n)), M (Fin.succ i) j = N (Fin.succ i) j + c i * M (Fin.castSucc i) j) →
det M = det N
c : Fin n → R
hc : ∀ (i : Fin n), Fin.succ k < Fin.succ i → c i = 0
M N : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R
h0 : ∀ (j : Fin (Nat.succ n)), M 0 j = N 0 j
hsucc : ∀ (i : Fin n) (j : Fin (Nat.succ n)), M (Fin.succ i) j = N (Fin.succ i) j + c i * M (Fin.castSucc i) j
M' : Matrix (Fin (Nat.succ n)) (Fin (Nat.succ n)) R := updateRow M (Fin.succ k) (N (Fin.succ k))
hM' : M' = updateRow M (Fin.succ k) (N (Fin.succ k))
⊢ M = updateRow M' (Fin.succ k) (M' (Fin.succ k) + c k • M (Fin.castSucc k)) | /-
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 | 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
| Mathlib.LinearAlgebra.Matrix.Determinant.513_0.U1f6HO8zRbnvZ95 | 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 | Mathlib_LinearAlgebra_Matrix_Determinant |
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