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Some people implement pattern and best practices without analyzing its
efficiency on their projects. Consequently, our goal in this article is to
convince software developers that it is worth to make an earnest effort to
evaluate the use of best practices and software patterns. For such purpose, in
this study we took a concrete case system for geographical locations inputs
through user interfaces. Then, we performed a comparative study on a
traditional method against our approach, named reverse logistic to retrieve
results, by measuring the time that a user spends to perform actions when
entering data into a system. Surprisingly, we had a decrease of 59% in the
amount of time spent in comparison to the time spent on the traditional method.
This result lays a foundation for feeding data from the typical final step and
search based on string matching algorithms, speeding up the interaction between
people and computer response
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We revisit Wschebor's theorems on small increments for processes with scaling
and stationary properties and deduce large deviation principles.
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Hydrogen-enhanced decohesion (HEDE) is one of the many mechanisms of hydrogen
embrittlement, a phenomenon that severely impacts structural materials such as
iron and iron alloys. Grain boundaries (GBs) play a critical role in this
mechanism, where they can provide trapping sites or act as hydrogen diffusion
pathways. The interaction of H with GBs and other crystallographic defects, and
thus the solubility and distribution of H in the microstructure, depends on the
concentration, chemical potential, and local stress. Therefore, for a
quantitative assessment of HEDE, a generalized solution energy in conjunction
with the cohesive strength as a function of hydrogen coverage is needed. In
this paper, we carry out density functional theory calculations to investigate
the influence of H on the decohesion of the $\Sigma$5(310)[001] and
$\Sigma$3(112)[1$\bar{1}$0] symmetrical tilt GBs in bcc Fe, as examples for
open and close-packed GB structures. A method to identify the segregation sites
at the GB plane is proposed. The results indicate that at higher local
concentrations, H leads to a significant reduction of the cohesive strength of
the GB planes, significantly more pronounced at the $\Sigma$5 than at the
$\Sigma$3 GB. Interestingly, at finite stress, the $\Sigma$3 GB becomes more
favorable for H solution, as opposed to the case of zero stress, where the
$\Sigma$5 GB is more attractive. This suggests that, under certain conditions,
stresses in the microstructure can lead to a redistribution of H to the
stronger grain boundary, which opens a path to designing H-resistant
microstructures. To round up our study, we investigate the effects of typical
alloying elements in ferritic steel, C, V, Cr, and Mn, on the solubility of H
and the strength of the GBs.
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Let $\varphi:X\to X$ be a homeomorphism of a compact metric space $X$. For
any continuous function $F:X\to \mathbb{R}$ there is a one-parameter group
$\alpha^{F}$ of automorphisms on the crossed product $C^*$-algebra
$C(X)\rtimes_{\varphi}\mathbb{Z}$ defined such that
$\alpha^{F}_{t}(fU)=fUe^{-itF}$ when $f \in C(X)$ and $U$ is the canonical
unitary in the construction of the crossed product. In this paper we study the
KMS states for these flows by developing an intimate relation to the ergodic
theory of non-singular transformations and show that the structure of
KMS-states can be very rich and complicated. Our results are complete
concerning the set of possible inverse temperatures; in particular, we show
that when $C(X) \rtimes_{\phi} \mathbb Z$ is simple this set is either $\{0\}$
or the whole line $\mathbb R$.
|
Maintaining tissue homeostasis requires appropriate regulation of stem cell
differentiation. The Waddington landscape posits that gene circuits in a cell
form a potential landscape of different cell types, wherein cells follow
attractors of the probability landscape to develop into distinct cell types.
However, how adult stem cells achieve a delicate balance between self-renewal
and differentiation remains unclear. We propose that random inheritance of
epigenetic states plays a pivotal role in stem cell differentiation and present
a hybrid model of stem cell differentiation induced by epigenetic
modifications. Our comprehensive model integrates gene regulation networks,
epigenetic state inheritance, and cell regeneration, encompassing multi-scale
dynamics ranging from transcription regulation to cell population. Through
model simulations, we demonstrate that random inheritance of epigenetic states
during cell divisions can spontaneously induce cell differentiation,
dedifferentiation, and transdifferentiation. Furthermore, we investigate the
influences of interfering with epigenetic modifications and introducing
additional transcription factors on the probabilities of dedifferentiation and
transdifferentiation, revealing the underlying mechanism of cell reprogramming.
This \textit{in silico} model provides valuable insights into the intricate
mechanism governing stem cell differentiation and cell reprogramming and offers
a promising path to enhance the field of regenerative medicine.
|
Magnetic reconnection in laser-produced magnetized plasma is investigated by
using optical diagnostics. The magnetic field is generated via Biermann battery
effect, and the inversely directed magnetic field lines interact with each
other. It is shown by self-emission measurement that two colliding plasmas
stagnate on a mid-plane forming two planar dense regions, and that they
interact later in time. Laser Thomson scattering spectra are distorted in the
direction of the self-generated magnetic field, indicating asymmetric ion
velocity distribution and plasma acceleration. In addition, the spectra
perpendicular to the magnetic field show different peak intensity, suggesting
an electron current formation. These results are interpreted as magnetic field
dissipation, reconnection, and outflow acceleration. Two-directional laser
Thomson scattering is, as discussed here, a powerful tool for the investigation
of microphysics in the reconnection region.
|
Large-scale fine-grained image retrieval has two main problems. First, low
dimensional feature embedding can fasten the retrieval process but bring
accuracy reduce due to overlooking the feature of significant attention regions
of images in fine-grained datasets. Second, fine-grained images lead to the
same category query hash codes mapping into the different cluster in database
hash latent space. To handle these two issues, we propose a feature consistency
driven attention erasing network (FCAENet) for fine-grained image retrieval.
For the first issue, we propose an adaptive augmentation module in FCAENet,
which is selective region erasing module (SREM). SREM makes the network more
robust on subtle differences of fine-grained task by adaptively covering some
regions of raw images. The feature extractor and hash layer can learn more
representative hash code for fine-grained images by SREM. With regard to the
second issue, we fully exploit the pair-wise similarity information and add the
enhancing space relation loss (ESRL) in FCAENet to make the vulnerable relation
stabler between the query hash code and database hash code. We conduct
extensive experiments on five fine-grained benchmark datasets (CUB2011,
Aircraft, NABirds, VegFru, Food101) for 12bits, 24bits, 32bits, 48bits hash
code. The results show that FCAENet achieves the state-of-the-art (SOTA)
fine-grained retrieval performance compared with other methods.
|
Some families of carbonaceous chondrites are rich in prebiotic organics that
may have contributed to the origin of life on Earth and elsewhere. However, the
formation and chemical evolution of complex soluble organic molecules from
interstellar precursors under relevant parent body conditions has not been
thoroughly investigated. In this study, we approach this topic by simulating
meteorite parent body aqueous alteration of interstellar residue analogs. The
distributions of amines and amino acids are qualitatively and quantitatively
investigated and linked to closing the gap between interstellar and meteoritic
prebiotic organic abundances. We find that the abundance trend of methylamine >
ethylamine> glycine > serine > alanine > \b{eta}-alanine does not change from
pre- to post-aqueous alteration, suggesting that certain cloud conditions have
an influential role on the distributions of interstellar-inherited meteoritic
organics. However, the abundances for most of the amines and amino acids
studied here varied by about 2-fold when aqueously processed for 7 days at 125
{\deg}C, and the changes in the {\alpha}- to \b{eta}-alanine ratio were
consistent with those of aqueously altered carbonaceous chondrites, pointing to
an influential role of meteorite parent body processing on the distributions of
interstellar-inherited meteoritic organics. We detected higher abundances of
{\alpha}- over \b{eta}-alanine, which is opposite to what is typically observed
in aqueously altered carbonaceous chondrites; these results may be explained by
at least the lack of minerals and insoluble organic matter-relevant materials
in the experiments. The high abundance of volatile amines in the non-aqueously
altered samples suggests that these types of interstellar volatiles can be
efficiently transferred to asteroids and comets, supporting the idea of the
presence of interstellar organics in solar system objects.
|
We give a new construction, based on categorical logic, of Nori's $\mathbb
Q$-linear abelian category of mixed motives associated to a cohomology or
homology functor with values in finite-dimensional vector spaces over $\mathbb
Q$. This new construction makes sense for infinite-dimensional vector spaces as
well, so that it associates a $\mathbb Q$-linear abelian category of mixed
motives to any (co)homology functor, not only Betti homology (as Nori had done)
but also, for instance, $\ell$-adic, $p$-adic or motivic cohomology. We prove
that the $\mathbb Q$-linear abelian categories of mixed motives associated to
different (co)homology functors are equivalent if and only a family (of logical
nature) of explicit properties is shared by these different functors. The
problem of the existence of a universal cohomology theory and of the
equivalence of the information encoded by the different classical cohomology
functors thus reduces to that of checking these explicit conditions.
|
The inherent noise in the observed (e.g., scanned) binary document image
degrades the image quality and harms the compression ratio through breaking the
pattern repentance and adding entropy to the document images. In this paper, we
design a cost function in Bayesian framework with dictionary learning.
Minimizing our cost function produces a restored image which has better quality
than that of the observed noisy image, and a dictionary for representing and
encoding the image. After the restoration, we use this dictionary (from the
same cost function) to encode the restored image following the
symbol-dictionary framework by JBIG2 standard with the lossless mode.
Experimental results with a variety of document images demonstrate that our
method improves the image quality compared with the observed image, and
simultaneously improves the compression ratio. For the test images with
synthetic noise, our method reduces the number of flipped pixels by 48.2% and
improves the compression ratio by 36.36% as compared with the best encoding
methods. For the test images with real noise, our method visually improves the
image quality, and outperforms the cutting-edge method by 28.27% in terms of
the compression ratio.
|
We present an approach to study functional segregation and integration in the
living brain based on community structure decomposition determined by maximum
modularity. We demonstrate this method with a network derived from functional
imaging data with nodes defined by individual image pixels, and edges in terms
of correlated signal changes. We found communities whose anatomical
distributions correspond to biologically meaningful structures and include
compelling functional subdivisions between anatomically equivalent brain
regions.
|
To control how a robot moves, motion planning algorithms must compute paths
in high-dimensional state spaces while accounting for physical constraints
related to motors and joints, generating smooth and stable motions, avoiding
obstacles, and preventing collisions. A motion planning algorithm must
therefore balance competing demands, and should ideally incorporate uncertainty
to handle noise, model errors, and facilitate deployment in complex
environments. To address these issues, we introduce a framework for robot
motion planning based on variational Gaussian processes, which unifies and
generalizes various probabilistic-inference-based motion planning algorithms,
and connects them with optimization-based planners. Our framework provides a
principled and flexible way to incorporate equality-based, inequality-based,
and soft motion-planning constraints during end-to-end training, is
straightforward to implement, and provides both interval-based and
Monte-Carlo-based uncertainty estimates. We conduct experiments using different
environments and robots, comparing against baseline approaches based on the
feasibility of the planned paths, and obstacle avoidance quality. Results show
that our proposed approach yields a good balance between success rates and path
quality.
|
Starting from light to superheavy nuclei, we have calculated the effective
surface properties such as the symmetry energy, neutron pressure, and symmetry
energy curvature using the coherent density fluctuation model. The isotopic
chains of O, Ca, Ni, Zr, Sn, Pb, and Z = 120 are considered in the present
analysis, which cover nuclei over the whole nuclear chart. The matter density
distributions of these nuclei along with the ground state bulk properties are
calculated within the spherically symmetric effective field theory motivated
relativistic mean field model by using the recently developed IOPB-I,
FSUGarnet, and G3 parameter sets. The calculated results are compared with the
predictions of the widely used NL3 parameter set and found in good agreement.
We observe a few signatures of shell and/or sub-shell structure in the isotopic
chains of nuclei. The present investigations are quite relevant for the
synthesis of exotic nuclei with high isospin asymmetry including superheavy and
also to constrain an equation of state of nuclear matter.
|
Many biological and physical systems exhibit population-density dependent
transitions to synchronized oscillations in a process often termed "dynamical
quorum sensing". Synchronization frequently arises through chemical
communication via signaling molecules distributed through an external media. We
study a simple theoretical model for dynamical quorum sensing: a heterogenous
population of limit-cycle oscillators diffusively coupled through a common
media. We show that this model exhibits a rich phase diagram with four
qualitatively distinct mechanisms fueling population-dependent transitions to
global oscillations, including a new type of transition we term "dynamic
death". We derive a single pair of analytic equations that allows us to
calculate all phase boundaries as a function of population density and show
that the model reproduces many of the qualitative features of recent
experiments of BZ catalytic particles as well as synthetically engineered
bacteria.
|
Face recognition models embed a face image into a low-dimensional identity
vector containing abstract encodings of identity-specific facial features that
allow individuals to be distinguished from one another. We tackle the
challenging task of inverting the latent space of pre-trained face recognition
models without full model access (i.e. black-box setting). A variety of methods
have been proposed in literature for this task, but they have serious
shortcomings such as a lack of realistic outputs and strong requirements for
the data set and accessibility of the face recognition model. By analyzing the
black-box inversion problem, we show that the conditional diffusion model loss
naturally emerges and that we can effectively sample from the inverse
distribution even without an identity-specific loss. Our method, named identity
denoising diffusion probabilistic model (ID3PM), leverages the stochastic
nature of the denoising diffusion process to produce high-quality,
identity-preserving face images with various backgrounds, lighting, poses, and
expressions. We demonstrate state-of-the-art performance in terms of identity
preservation and diversity both qualitatively and quantitatively, and our
method is the first black-box face recognition model inversion method that
offers intuitive control over the generation process.
|
Polynomials commute under composition are referred to as commuting
polynomials. In this paper, we study division properties for commuting
polynomials with rational (and integer) coefficients. As a consequence, we show
an algebraic particularity of the commuting polynomials coming from weighted
sums for cycle graphs with pendant edges (arXiv:2402.07209v1.).
|
We prove the following theorem: if $w$ is a quasiconformal mapping of the
unit disk onto itself satisfying elliptic partial differential inequality
$|L[w]|\le \mathcal{B}|\nabla w|^2+\Gamma$, then $w$ is Lipschitz continuous.
This {result} extends some recent results, where instead of an elliptic
differential operator is {only} considered {the} Laplace operator.
|
Content:
1. Introduction
2. Regge calculus and dynamical triangulations
Simplicial manifolds and piecewise linear spaces - dual complex and volume
elements - curvature and Regge action - topological invariants - quantum Regge
calculus - dynamical triangulations
3. Two dimensional quantum gravity, dynamical triangulations and matrix
models
continuum formulation - dynamical triangulations and continuum limit - one
matrix model - various matrix models - numerical studies - c=1 barrier -
intrinsic geometry of 2d gravity - Liouville at c>25
4. Euclidean quantum gravity in three and four dimensions
what are we looking for? - 3d simplicial gravity - 4d simplicial gravity - 3d
and 4d Regge calculus
5. Non-perturbative problems in two dimensional quantum gravity
double scaling limit - string equation - non-perturbative properties of the
string equation - divergent series and Borel summability - non-perturbative
effects in 2d gravity and string theories - stabilization proposals
6. Conclusion
|
The expression for entropy sometimes appears mysterious - as it often is
asserted without justification. This short manuscript contains a discussion of
the underlying assumptions behind entropy as well as simple derivation of this
ubiquitous quantity.
|
Session-based recommendation techniques aim to capture dynamic user behavior
by analyzing past interactions. However, existing methods heavily rely on
historical item ID sequences to extract user preferences, leading to challenges
such as popular bias and cold-start problems. In this paper, we propose a
hybrid multimodal approach for session-based recommendation to address these
challenges. Our approach combines different modalities, including textual
content and item IDs, leveraging the complementary nature of these modalities
using CatBoost. To learn universal item representations, we design a language
representation-based item retrieval architecture that extracts features from
the textual content utilizing pre-trained language models. Furthermore, we
introduce a novel Decoupled Contrastive Learning method to enhance the
effectiveness of the language representation. This technique decouples the
sequence representation and item representation space, facilitating
bidirectional alignment through dual-queue contrastive learning.
Simultaneously, the momentum queue provides a large number of negative samples,
effectively enhancing the effectiveness of contrastive learning. Our approach
yielded competitive results, securing a 5th place ranking in KDD CUP 2023 Task
1. We have released the source code and pre-trained models associated with this
work.
|
The Magnetism in Massive Stars (MiMeS) project represents the largest
systematic survey of stellar magnetism ever undertaken. Based on a sample of
over 550 Galactic B and O-type stars, the MiMeS project has derived the basic
characteristics of magnetism in hot, massive stars. Herein we report
preliminary results.
|
Several hairy black hole solutions are known to violate the original version
of the celebrated no-hair conjecture. This prompted the development of a new
theorem that establishes a universal lower bound on the extension of hairs
outside any $4$-dimensional black hole solutions of general relativity. Our
work presents a novel generalization of this ``no-short hair'' theorem, which
notably does not use gravitational field equations and is valid for arbitrary
spacetime dimensions ($D \geq 4$). Consequently, irrespective of the underlying
theory of gravity, the ``hairosphere'' must extend to the innermost light ring
of the black hole spacetime. Various possible observational implications of
this intriguing theorem are discussed, and other useful consequences are
explored.
|
Knowledge of the severity of an influenza outbreak is crucial for informing
and monitoring appropriate public health responses, both during and after an
epidemic. However, case-fatality, case-intensive care admission and
case-hospitalisation risks are difficult to measure directly. Bayesian evidence
synthesis methods have previously been employed to combine fragmented,
under-ascertained and biased surveillance data coherently and consistently, to
estimate case-severity risks in the first two waves of the 2009 A/H1N1
influenza pandemic experienced in England. We present in detail the complex
probabilistic model underlying this evidence synthesis, and extend the analysis
to also estimate severity in the third wave of the pandemic strain during the
2010/2011 influenza season. We adapt the model to account for changes in the
surveillance data available over the three waves. We consider two approaches:
(a) a two-stage approach using posterior distributions from the model for the
first two waves to inform priors for the third wave model; and (b) a one-stage
approach modelling all three waves simultaneously. Both approaches result in
the same key conclusions: (1) that the age-distribution of the case-severity
risks is "u"-shaped, with children and older adults having the highest
severity; (2) that the age-distribution of the infection attack rate changes
over waves, school-age children being most affected in the first two waves and
the attack rate in adults over 25 increasing from the second to third waves;
and (3) that when averaged over all age groups, case-severity appears to
increase over the three waves. The extent to which the final conclusion is
driven by the change in age-distribution of those infected over time is subject
to discussion.
|
A Theorem of Hou, Leung and Xiang generalised Kneser's addition Theorem to
field extensions. This theorem was known to be valid only in separable
extensions, and it was a conjecture of Hou that it should be valid for all
extensions. We give an alternative proof of the theorem that also holds in the
non-separable case, thus solving Hou's conjecture. This result is a consequence
of a strengthening of Hou et al.'s theorem that is a transposition to extension
fields of an addition theorem of Balandraud.
|
In some class of supersymmetric (SUSY) models, the neutral Wino becomes the
lightest superparticle and the Bino decays into the Wino and standard-model
particles. In such models, we show that the measurement of the Bino mass is
possible if the short charged tracks (with the length of O(10 cm)) can be
identified as a signal of the charged-Wino production. We pay particular
attention to the anomaly-mediated SUSY-breaking (AMSB) model with a generic
form of K\"ahler potential, in which only the gauginos are kinematically
accessible superparticles to the LHC, and discuss the implication of the Bino
mass measurement for the test of the AMSB model.
|
The non-Abelian symmetries of the half-infinite XXZ spin chain for all
possible types of integrable boundary conditions are classified. For each type
of boundary conditions, an analog of the Chevalley-type presentation is given
for the corresponding symmetry algebra. In particular, two new algebras arise
that are, respectively, generated by the symmetry operators of the model with
triangular and special $U_q(gl_2)-$invariant integrable boundary conditions.
|
We study the spin dynamics in a 3D quantum antiferromagnet on a face-centered
cubic (FCC) lattice. The effects of magnetic field, single-ion anisotropy, and
biquadratic interactions are investigated using linear spin wave theory with
spins in a canted basis about the Type IIA FCC antiferromagnetic ground state
structure which is known to be stable. We calculate the expected finite
frequency neutron scattering intensity and give qualitative criteria for
typical FCC materials MnO and CoO. The magnetization reduction due to quantum
zero point fluctuations is also analyzed.
|
The transport of energy in heated plasmas requires the knowledge of the
radiation coefficients. These coefficients consist of contribution of
bremsstrahlung, photoionisation, bound-bound transmissions and scattering.
Scattering of photons on electrons is taken into account by the model of
Thomson, Klein-Nishina and the first order angular momentum of Klein-Nishina.
It is shown that radiative scattering becomes an important part of energy
transport in high temperature plasmas. Moreover, the contribution of transport
correction to scattering is taken into account. The physics is discussed on the
example of a heated plutonium plasma at different particle densities and
temperatures in radiative equilibrium.
|
We construct covariant $q$-deformed holomorphic structures for all
finitely-generated relative Hopf modules over the irreducible quantum flag
manifolds endowed with their Heckenberger--Kolb calculi. In the classical limit
these reduce to modules of sections of holomorphic homogeneous vector bundles
over irreducible flag manifolds. For the case of simple relative Hopf modules,
we show that this covariant holomorphic structure is unique. This generalises
earlier work of Majid, Khalkhali, Landi, and van Suijlekom for line modules of
the Podle\'s sphere, and subsequent work of Khalkhali and Moatadelro for
general quantum projective space.
|
We present alfonso, an open-source Matlab package for solving conic
optimization problems over nonsymmetric convex cones. The implementation is
based on the authors' corrected analysis of a primal-dual interior-point method
of Skajaa and Ye. This method enables optimization over any convex cone as long
as a logarithmically homogeneous self-concordant barrier is available for the
cone or its dual. This includes many nonsymmetric cones, for example,
hyperbolicity cones and their duals (such as sum-of-squares cones),
semidefinite and second-order cone representable cones, power cones, and the
exponential cone. Besides enabling the solution of problems which cannot be
cast as optimization problems over a symmetric cone, it also offers performance
advantages for problems whose symmetric cone programming representation
requires a large number of auxiliary variables or has a special structure that
can be exploited in the barrier computation.
The worst-case iteration complexity of alfonso is the best known for
non-symmetric cone optimization: $O(\sqrt{\nu}\log(1/\epsilon))$ iterations to
reach an $\epsilon$-optimal solution, where $\nu$ is the barrier parameter of
the barrier function used in the optimization.
alfonso can be interfaced with a Matlab function (supplied by the user) that
computes the Hessian of a barrier function for the cone. For convenience, a
simplified interface is also available to optimize over the direct product of
cones for which a barrier function has already been built into the software.
This interface can be easily extended to include new cones. Both interfaces are
illustrated by solving linear programs. The oracle interface and the efficiency
of alfonso are also demonstrated using a design of experiments problem in which
the tailored barrier computation greatly decreases the solution time compared
to using state-of-the-art conic optimization software.
|
We consider maximal slices of the Myers-Perry black hole, the doubly spinning
black ring, and the Black Saturn solution. These slices are complete,
asymptotically flat Riemannian manifolds with inner boundaries corresponding to
black hole horizons. Although these spaces are simply connected as a
consequence of topological censorship, they have non-trivial topology. In this
note we investigate the question of whether the topology of spatial sections of
the horizon uniquely determines the topology of the maximal slices. We show
that the horizon determines the homological invariants of the slice under
certain conditions. The homological analysis is extended to black holes for
which explicit geometries are not yet known. We believe that these results
could provide insights in the context of proving existence of deformations of
this initial data. For the topological slices of the doubly spinning black ring
and the Black Saturn we compute the homotopy groups up to dimension 3 and show
that their 4-dimensional homotopy group is not trivial.
|
We study the large-time behavior of bounded from below solutions of parabolic
viscous Hamilton-Jacobi Equations in the whole space $\mathbb{R}^N$ in the case
of superquadratic Hamiltonians. Existence and uniqueness of such solutions are
shown in a very general framework, namely when the source term and the initial
data are only bounded from below with an arbitrary growth at infinity. Our main
result is that these solutions have an ergodic behavior when $t\to +\infty$,
i.e., they behave like $\lambda^*t + \phi(x)$ where $\lambda^*$ is the maximal
ergodic constant and $\phi$ is a solution of the associated ergodic problem.
The main originality of this result comes from the generality of the data: in
particular, the initial data may have a completely different growth at infinity
from those of the solution of the ergodic problem.
|
We provide a new method to prove and improve the Chemin-Masmoudi criterion
for viscoelastic systems of Oldroyd type in \cite{CM} in two space dimensions.
Our method is much easier than the one based on the well-known \textit{losing a
priori estimate} and is expected to be easily adopted to other problems
involving the losing \textit{a priori} estimate.
|
Through molecular dynamics simulations, we examined hydrodynamic behavior of
the Brownian motion of fullerene particles based on molecular interactions. The
solvation free energy and the velocity autocorrelation function (VACF) were
calculated by using the Lennard-Jones (LJ) and Weeks-Chandler-Andersen (WCA)
potentials for the solute-solvent and solvent-solvent interactions and by
changing the size of the fullerene particles. We also measured the diffusion
constant of the fullerene particles and the shear viscosity of the host fluid,
and then the hydrodynamic radius $a_\mathrm{HD}$ was quantified from the
Stokes-Einstein relation. The $a_\mathrm{HD}$ value exceeds that of the
gyration radius of the fullerene when the solvation free energy exhibits
largely negative values using the LJ potential. In contrast, $a_\mathrm{HD}$
becomes comparable to the size of bare fullerene, when the solvation free
energy is positive using the WCA potential. Furthermore, the VACF of the
fullerene particles is directly comparable with the analytical expressions
utilizing the Navier-Stokes equations both in incompressible and compressible
forms. Hydrodynamic long-time tail $t^{-3/2}$ is demonstrated for timescales
longer than the kinematic time of the momentum diffusion over the particles'
size. However, the VACF in shorter timescales deviates from the hydrodynamic
description, particularly for smaller fullerene particles and for the LJ
potential. This occurs even though the compressible effect is considered when
characterizing the decay of VACF around the sound propagation time scale over
the particles' size. These results indicate that the nanoscale Brownian motion
is influenced by the solvation structure around the solute particles
originating from the molecular interaction.
|
Mutual exclusion is one of the most commonly used techniques to handle
contention in concurrent systems. Traditionally, mutual exclusion algorithms
have been designed under the assumption that a process does not fail while
acquiring/releasing a lock or while executing its critical section. However,
failures do occur in real life, potentially leaving the lock in an inconsistent
state. This gives rise to the problem of recoverable mutual exclusion (RME)
that involves designing a mutual exclusion (ME) algorithm that can tolerate
failures, while maintaining safety and liveness properties.
In this work, we present a framework that transforms any algorithm that
solves the RME problem into an algorithm that can also simultaneously adapt to
(1) the number of processes competing for the lock, as well as (2) the number
of failures that have occurred in the recent past, while maintaining the
correctness and performance properties of the underlying RME algorithm.
Additionally, the algorithm constructed as a result of this transformation adds
certain desirable properties like fairness (a variation of FCFS) and bounded
recovery. Assume that the worst-case RMR complexity of a critical section
request in the underlying RME algorithm is $R(n)$. Then, our framework yields
an RME algorithm for which the worst-case RMR complexity of a critical section
request is given by $\mathcal{O}(\min \{\ddot{c}, \sqrt{F+1}, R(n)\})$, where
$\ddot{c}$ denotes the point contention of the request and $F$ denotes the
number of failures in the recent past of the request.
We further extend our framework by presenting a novel memory reclamation
algorithm to bound the worst-case space complexity of the RME algorithm. The
memory reclamation techniques maintain the fairness, performance and
correctness properties of our transformation and is general enough to be
employed to bound the space of other RME algorithms.
|
We entirely compute the cohomology for a natural and large class of
$\mathfrak{osp}(1|2)$ modules $M$. We study the restriction to the
$\mathfrak{sl}(2)$ cohomology of $M$ and apply our results to the module
$M={\mathfrak D}_{\lambda,\mu}$ of differential operators on the super circle,
acting on densities.
|
This workshop aims to demonstrate how the Tracker Video Analysis and Modeling
Tool engages, enables and empowers teachers to be learners so that we can be
leaders in our teaching practice. Through this workshop, the kinematics of a
falling ball and a projectile motion are explored using video analysis and in
the later video modeling. We hope to lead and inspire other teachers by
facilitating their experiences with this ICT-enabled video modeling pedagogy
(Brown, 2008) and free tool for facilitating students-centered active learning,
thus motivate students to be more self-directed.
|
Considering that Coupled Dictionary Learning (CDL) method can obtain a
reasonable linear mathematical relationship between resource images, we propose
a novel CDL-based Synthetic Aperture Radar (SAR) and multispectral pseudo-color
fusion method. Firstly, the traditional Brovey transform is employed as a
pre-processing method on the paired SAR and multispectral images. Then, CDL is
used to capture the correlation between the pre-processed image pairs based on
the dictionaries generated from the source images via enforced joint sparse
coding. Afterward, the joint sparse representation in the pair of dictionaries
is utilized to construct an image mask via calculating the reconstruction
errors, and therefore generate the final fusion image. The experimental
verification results of the SAR images from the Sentinel-1 satellite and the
multispectral images from the Landsat-8 satellite show that the proposed method
can achieve superior visual effects, and excellent quantitative performance in
terms of spectral distortion, correlation coefficient, MSE, NIQE, BRISQUE, and
PIQE.
|
In this paper, the potential benefits of applying non-orthogonal multiple
access (NOMA) technique in $K$-tier hybrid heterogeneous networks (HetNets) is
explored. A promising new transmission framework is proposed, in which NOMA is
adopted in small cells and massive multiple-input multiple-output (MIMO) is
employed in macro cells. For maximizing the biased average received power for
mobile users, a NOMA and massive MIMO based user association scheme is
developed. To evaluate the performance of the proposed framework, we first
derive the analytical expressions for the coverage probability of NOMA enhanced
small cells. We then examine the spectrum efficiency of the whole network, by
deriving exact analytical expressions for NOMA enhanced small cells and a
tractable lower bound for massive MIMO enabled macro cells. Lastly, we
investigate the energy efficiency of the hybrid HetNets. Our results
demonstrate that: 1) The coverage probability of NOMA enhanced small cells is
affected to a large extent by the targeted transmit rates and power sharing
coefficients of two NOMA users; 2) Massive MIMO enabled macro cells are capable
of significantly enhancing the spectrum efficiency by increasing the number of
antennas; 3) The energy efficiency of the whole network can be greatly improved
by densely deploying NOMA enhanced small cell base stations (BSs); and 4) The
proposed NOMA enhanced HetNets transmission scheme has superior performance
compared to the orthogonal multiple access~(OMA) based HetNets.
|
A reliable critic is central to on-policy actor-critic learning. But it
becomes challenging to learn a reliable critic in a multi-agent sparse reward
scenario due to two factors: 1) The joint action space grows exponentially with
the number of agents 2) This, combined with the reward sparseness and
environment noise, leads to large sample requirements for accurate learning. We
show that regularising the critic with spectral normalization (SN) enables it
to learn more robustly, even in multi-agent on-policy sparse reward scenarios.
Our experiments show that the regularised critic is quickly able to learn from
the sparse rewarding experience in the complex SMAC and RWARE domains. These
findings highlight the importance of regularisation in the critic for stable
learning.
|
We study the representations of large integers $n$ as sums $p_1^2 + ... +
p_s^2$, where $p_1,..., p_s$ are primes with $| p_i - (n/s)^{1/2} | \le
n^{\theta/2}$, for some fixed $\theta < 1$. When $s = 5$ we use a sieve method
to show that all sufficiently large integers $n \equiv 5 \pmod {24}$ can be
represented in the above form for $\theta > 8/9$. This improves on earlier work
by Liu, L\"{u} and Zhan, who established a similar result for $\theta > 9/10$.
We also obtain estimates for the number of integers $n$ satisfying the
necessary local conditions but lacking representations of the above form with
$s = 3, 4$. When $s = 4$ our estimates improve and generalize recent results by
L\"{u} and Zhai, and when $s = 3$ they appear to be first of their kind.
|
This is an early but comprehensive review of the PNP Poisson Nernst Planck
theory of ion channels. Extensive reference is made to the earlier literature.
The starting place for this theory of open channels is a theory of
electrodiffusion rather like that used previously to describe membranes. The
theory uses Poisson's equation to describe how charge on ions and the channel
protein creates electrical potential; it uses the Nernst-Planck equations to
describe migration and diffusion of ions in gradients of concentration and
electrical potential. Combined, these are also the "drift-diffusion equations"
of solid state physics, which are widely, if not universally used to describe
the flow of current and the behavior of semiconductors.
|
In recent years, the development of Artificial Intelligence (AI) has offered
the possibility to tackle many interdisciplinary problems, and the field of
chemistry is not an exception. Drug analysis is crucial in drug discovery,
playing an important role in human life. However, this task encounters many
difficulties due to the wide range of computational chemistry methods. Drug
analysis also involves a massive amount of work, including determining taste.
Thus, applying deep learning to predict a molecule's bitterness is inevitable
to accelerate innovation in drug analysis by reducing the time spent. This
paper proposes an artificial neural network (ANN) based approach (EC-ANN) for
the molecule's bitter prediction. Our approach took the SMILE (Simplified
molecular-input line-entry system) string of a molecule as the input data for
the prediction, and the 256-bit ECFP descriptor is the input vector for our
network. It showed impressive results compared to state-of-the-art, with a
higher performance on two out of three test sets according to the experiences
on three popular test sets: Phyto-Dictionary, Unimi, and Bitter-new set [1].
For the Phyto-Dictionary test set, our model recorded 0.95 and 0.983 in
F1-score and AUPR, respectively, depicted as the highest score in F1-score. For
the Unimi test set, our model achieved 0.88 in F1-score and 0.88 in AUPR, which
is roughly 12.3% higher than the peak of previous models [1, 2, 3, 4, 5].
|
Let $p$ be an odd prime. It is well known that $F_{p-(\frac p5)}\equiv
0\pmod{p}$, where $\{F_n\}_{n\ge0}$ is the Fibonacci sequence and $(-)$ is the
Jacobi symbol. In this paper we show that if $p\not=5$ then we may determine
$F_{p-(\frac p5)}$ mod $p^3$ in the following way:
$$\sum_{k=0}^{(p-1)/2}\frac{\binom{2k}k}{(-16)^k}\equiv\left(\frac{p}5\right)\left(1+\frac{F_{p-(\frac
{p}5)}}2\right)\pmod{p^3}.$$ We also use Lucas quotients to determine
$\sum_{k=0}^{(p-1)/2}\binom{2k}k/m^k$ modulo $p^2$ for any integer
$m\not\equiv0\pmod{p}$; in particular, we obtain
$$\sum_{k=0}^{(p-1)/2}\frac{\binom{2k}k}{16^k}\equiv\left(\frac3{p}\right)\pmod{p^2}.$$
In addition, we pose three conjectures for further research.
|
This paper presents a rewriting logic specification of the Illinois Browser
Operating System (IBOS) and defines several security properties, including the
same-origin policy (SOP) in reachability logic. It shows how these properties
can be deductively verified using our constructor-based reachability logic
theorem prover. This paper also highlights the reasoning techniques used in the
proof and three modularity principles that have been crucial to scale up and
complete the verification effort.
|
Quantum versions of random walks on the line and cycle show a quadratic
improvement in their spreading rate and mixing times respectively. The addition
of decoherence to the quantum walk produces a more uniform distribution on the
line, and even faster mixing on the cycle by removing the need for
time-averaging to obtain a uniform distribution. We calculate numerically the
entanglement between the coin and the position of the quantum walker and show
that the optimal decoherence rates are such that all the entanglement is just
removed by the time the final measurement is made.
|
Making use of the T-duality symmetry of superstring theory, and of the double
geometry from Double Field Theory, we argue that cosmological singularities of
a homogeneous and isotropic universe disappear. In fact, an apparent big bang
singularity in Einstein gravity corresponds to a universe expanding to infinite
size in the dual dimensions.
|
The electric-field response of a one-dimensional ring of interacting
fermions, where the interactions are described by the extended Hubbard model,
is investigated. By using an accurate real-time propagation scheme based on the
Chebyshev expansion of the evolution operator, we uncover various non-linear
regimes for a range of interaction parameters that allows modeling of metallic
and insulating (either charge density wave or spin density wave insulators)
rings. The metallic regime appears at the phase boundary between the two
insulating phases and provides the opportunity to describe either weakly or
strongly correlated metals. We find that the {\it fidelity susceptibility} of
the ground state as a function of magnetic flux piercing the ring provides a
very good measure of the short-time response. Even completely different
interacting regimes behave in a similar manner at short time-scales as long as
the fidelity susceptibility is the same. Depending on the strength of the
electric field we find various types of responses: persistent currents in the
insulating regime, dissipative regime or damped Bloch-like oscillations with
varying frequencies or even irregular in nature. Furthermore, we also consider
the dimerization of the ring and describe the response of a correlated band
insulator. In this case the distribution of the energy levels is more clustered
and the Bloch-like oscillations become even more irregular.
|
This article offers a simplified approach to the distribution theory of
randomly weighted averages or $P$-means $M_P(X):= \sum_{j} X_j P_j$, for a
sequence of i.i.d.random variables $X, X_1, X_2, \ldots$, and independent
random weights $P:= (P_j)$ with $P_j \ge 0$ and $\sum_{j} P_j = 1$. The
collection of distributions of $M_P(X)$, indexed by distributions of $X$, is
shown to encode Kingman's partition structure derived from $P$. For instance,
if $X_p$ has Bernoulli$(p)$ distribution on $\{0,1\}$, the $n$th moment of
$M_P(X_p)$ is a polynomial function of $p$ which equals the probability
generating function of the number $K_n$ of distinct values in a sample of size
$n$ from $P$: $E (M_P(X_p))^n = E p^{K_n}$. This elementary identity
illustrates a general moment formula for $P$-means in terms of the partition
structure associated with random samples from $P$, first developed by Diaconis
and Kemperman (1996) and Kerov (1998) in terms of random permutations. As shown
by Tsilevich (1997) if the partition probabilities factorize in a way
characteristic of the generalized Ewens sampling formula with two parameters
$(\alpha,\theta)$, found by Pitman (1992), then the moment formula yields the
Cauchy-Stieltjes transform of an $(\alpha,\theta)$ mean. The analysis of these
random means includes the characterization of $(0,\theta)$-means, known as
Dirichlet means, due to Von Neumann (1941), Watson (1956) and Cifarelli and
Regazzini (1990) and generalizations of L\'evy's arcsine law for the time spent
positive by a Brownian motion, due to Darling (1949) Lamperti (1958) and
Barlow, Pitman and Yor (1989).
|
The breakup of an interface into a cascade of droplets and their subsequent
coalescence is a generic problem of central importance to a large number of
industrial settings such as mixing, separations, and combustion. We study the
breakup of a liquid jet introduced through a cylindrical nozzle into a stagnant
viscous phase via a hybrid interface-tracking/level-set method to account for
the surface tension forces in a three-dimensional Cartesian domain. Numerical
solutions are obtained for a range of Reynolds (Re) and Weber (We) numbers. We
find that the interplay between the azimuthal and streamwise vorticity
components leads to different interfacial features and flow regimes in Re-We
space. We show that the streamwise vorticity plays a critical role in the
development of the three-dimensional instabilities on the jet surface. In the
inertia-controlled regime at high Re and We, we expose the details of the
spatio-temporal development of the vortical structures affecting the
interfacial dynamics. A mushroom-like structure is formed at the leading edge
of the jet inducing the generation of a liquid sheet in its interior that
undergoes rupture to form droplets. These droplets rotate inside the mushroom
structure due to their interaction with the prevailing vortical structures.
Additionally, Kelvin-Helmholtz vortices that form near the injection point
deform in the streamwise direction to form hairpin vortices, which, in turn,
trigger the formation of interfacial lobes in the jet core. The thinning of the
lobes induces the creation of holes which expand to form liquid threads that
undergo capillary breakup to form droplets.
|
The formalism that describes the non-linear growth of the angular momentum L
of protostructures from tidal torques in a Friedmann Universe, as developed in
a previous paper, is extended to include non-Gaussian initial conditions. We
restrict our analysis here to a particular class of non-Gaussian primordial
distributions, namely multiplicative models. In such models, strongly
correlated phases are produced by obtaining the gravitational potential via a
nonlinear local transformation of an underlying Gaussian random field. The
dynamical evolution of the system is followed by describing the trajectories of
fluid particles using second-order Lagrangian perturbation theory. In the
Einstein-de Sitter universe, the lowest-order perturbative correction to the
variance of the linear angular momentum of collapsing structures grows as t^8/3
for generic non-Gaussian statistics, which contrasts with the t^10/3 growth
rate characteristic of Gaussian statistics. This is a consequence of the fact
that the lowest-order perturbative spin contribution in the non-Gaussian case
arises from the third moment of the gravitational potential, which is
identically zero for a Gaussian field. Evaluating these corrections at the
maximum expansion time of the collapsing structure, we find that these
non-Gaussian and non-linear terms can be as high as the linear estimate,
without the degree of non-Gaussianity as quantified by skewness and kurtosis of
the density field being unacceptably large. The results suggest that
higher-order terms in the perturbative expansion may contribute significantly
to galactic spin which contrasts with the straightforward Gaussian case.
|
AA Tau, a classical T Tauri star in the Taurus cloud, has been the subject of
intensive photometric monitoring for more than two decades due to its
quasi-cyclic variation in optical brightness. Beginning in 2011, AA Tau showed
another peculiar variation -- its median optical though near-IR flux dimmed
significantly, a drop consistent with a 4-mag increase in visual extinction. It
has stayed in the faint state since.Here we present 4.7um CO rovibrational
spectra of AA Tau over eight epochs, covering an eleven-year time span, that
reveal enhanced 12CO and 13CO absorption features in the $J_{\rm
low}\leqslant$13 transitions after the dimming. These newly appeared
absorptions require molecular gas along the line of sight with T~500 K and a
column density of log (N12CO)~18.5 cm^{-2}, with line centers that show a
constant 6 km s$^{-1}$ redshift. The properties of the molecular gas confirm an
origin in the circumstellar material. We suggest that the dimming and
absorption are caused by gas and dust lifted to large heights by a magnetic
buoyancy instability. This material is now propagating inward, and on reaching
the star within a few years will be observed as an accretion outburst.
|
The gyrokinetic theory of the residual flow, in the electrostatic limit, is
revisited, with optimized stellarators in mind. We consider general initial
conditions for the problem, and identify cases that lead to a non-zonal
residual electrostatic potential, i.e. one having a significant component that
varies within a flux surface. We investigate the behavior of the ``intermediate
residual'' in stellarators, a measure of the flow that remains after geodesic
acoustic modes have damped away, but before the action of the slower damping
that is caused by unconfined particle orbits. The case of a quasi-isodynamic
stellarator is identified as having a particularly large such residual, owing
to the small orbit width achieved by optimization.
|
We present an efficient method for training slack-rescaled structural SVM.
Although finding the most violating label in a margin-rescaled formulation is
often easy since the target function decomposes with respect to the structure,
this is not the case for a slack-rescaled formulation, and finding the most
violated label might be very difficult. Our core contribution is an efficient
method for finding the most-violating-label in a slack-rescaled formulation,
given an oracle that returns the most-violating-label in a (slightly modified)
margin-rescaled formulation. We show that our method enables accurate and
scalable training for slack-rescaled SVMs, reducing runtime by an order of
magnitude compared to previous approaches to slack-rescaled SVMs.
|
The defect in diamond formed by a vacancy surrounded by three
nearest-neighbor nitrogen atoms and one carbon atom,
$\mathrm{N}_{3}\mathrm{V}$, is found in $\approx98\%$ of natural diamonds.
Despite $\mathrm{N}_{3}\mathrm{V}^{0}$ being the earliest electron paramagnetic
resonance spectrum observed in diamond, to date no satisfactory simulation of
the spectrum for an arbitrary magnetic field direction has been produced due to
its complexity. In this work, $\mathrm{N}_{3}\mathrm{V}^{0}$ is identified in
$^{15}\mathrm{N}$-doped synthetic diamond following irradiation and annealing.
The $\mathrm{^{15}N}_{3}\mathrm{V}^{0}$ spin Hamiltonian parameters are revised
and used to refine the parameters for $\mathrm{^{14}N}_{3}\mathrm{V}^{0}$,
enabling the latter to be accurately simulated and fitted for an arbitrary
magnetic field direction. Study of $\mathrm{^{15}N}_{3}\mathrm{V}^{0}$ under
excitation with green light indicates charge transfer between
$\mathrm{N}_{3}\mathrm{V}$ and $\mathrm{N_s}$. It is argued that this charge
transfer is facilitated by direct ionization of $\mathrm{N}_{3}\mathrm{V}^{-}$,
an as-yet unobserved charge state of $\mathrm{N}_{3}\mathrm{V}$.
|
We studied the magnetic excitations in the quasi-one-dimensional (q-1D)
ladder subsystem of Sr_(14-x) Ca_x Cu_24 O_41(SCCO) using Cu L_3-edge resonant
inelastic X-ray scattering (RIXS). By comparing momentum-resolved RIXS spectra
with (x=12.2) and without (x=0) high Ca content, we track the evolution of the
magnetic excitations from collective two-triplon (2T) excitations (x=0) to
weakly-dispersive gapped modes at an energy of 280 meV (x=12.2). Density matrix
renormalization group (DMRG) calculations of the RIXS response in the doped
ladders suggest that the flat magnetic dispersion and damped excitation profile
observed at x=12.2 originates from enhanced hole localization. This
interpretation is supported by polarization-dependent RIXS measurements, where
we disentangle the spin-conserving {\Delta}S=0 scattering from the predominant
{\Delta}S=1 spin-flip signal in the RIXS spectra. The results show that the
low-energy weight in the {\Delta}S=0 channel is depleted when Sr is replaced by
Ca, consistent with a reduced carrier mobility. Our results demonstrate that
off-ladder impurities can affect both the low-energy magnetic excitations and
superconducting correlations in the CuO_4 plaquettes. Finally, our study
characterizes the magnetic and charge fluctuations in the phase from which
superconductivity emerges in SCCO at elevated pressures.
|
Nonadiabatic effects in the electron-phonon coupling are important whenever
the ratio between the phononic and the electronic energy scales, the adiabatic
ratio, is non negligible. For superconducting systems, this gives rise to
additional diagrams in the superconducting self-energy, the vertex and cross
corrections. In this work we explore these corrections in a two-dimensional
single-band system through the crossover between the weak-coupling BCS and
strong-coupling Bose-Einstein regimes. By focusing on the pseudogap phase, we
identify the parameter range in which the pairing amplitude is amplified by
nonadiabatic effects and map them throughout the BCS-BEC crossover. These
effects become stronger as the system is driven deeply in the crossover regime,
for phonon frequencies of the order of the hopping energy and for large enough
electron-phonon coupling. Finally, we provide the phase space regions in which
the effects of nonadiabaticity are more relevant for unconventional
superconductors.
|
In singing voice synthesis (SVS), generating singing voices from musical
scores faces challenges due to limited data availability. This study proposes a
unique strategy to address the data scarcity in SVS. We employ an existing
singing voice synthesizer for data augmentation, complemented by detailed
manual tuning, an approach not previously explored in data curation, to reduce
instances of unnatural voice synthesis. This innovative method has led to the
creation of two expansive singing voice datasets, ACE-Opencpop and ACE-KiSing,
which are instrumental for large-scale, multi-singer voice synthesis. Through
thorough experimentation, we establish that these datasets not only serve as
new benchmarks for SVS but also enhance SVS performance on other singing voice
datasets when used as supplementary resources. The corpora, pre-trained models,
and their related training recipes are publicly available at ESPnet-Muskits
(\url{https://github.com/espnet/espnet})
|
We derive the evolution of the infrared (IR) luminosity function (LF) over
the last 4/5ths of cosmic time, using deep 24um and 70um imaging of the GOODS
North and South fields. We use an extraction technique based on prior source
positions at shorter wavelengths to build the 24 and 70um source catalogs. The
majority (93%) of the sources have a spectroscopic (39%) or a photometric
redshift (54%) and, in our redshift range of interest (i.e., 1.3<z<2.3) ~20% of
the sources have a spectroscopic redshifts. To extend our study to lower 70um
luminosities we perform a stacking analysis and we characterize the observed
L_24/(1+z) vs L_70/(1+z) correlation. Using spectral energy distribution
templates which best fit this correlation, we derive the IR luminosity of
sources from their 24 and 70 um fluxes. We then compute the IR LF at
z=1.55+/-0.25 and z=2.05+/-0.25. The redshift evolution of the IR LF from z=1.3
to z=2.3 is consistent with a luminosity evolution proportional to
(1+z)^1.0+/-0.9 combined with a density evolution proportional to
(1+z)^-1.1+/-1.5. At z~2, luminous IR galaxies (LIRGs: 10^11Lsun< LIR
<10^12Lsun) are still the main contributors to the total comoving IR luminosity
density (IR LD) of the Universe. At z~2, LIRGs and ultra-luminous IR galaxies
(ULIRGs: 10^12Lsun< LIR) account for ~49% and ~17% respectively of the total IR
LD of the Universe. Combined with previous results for galaxies at z<1.3 and
assuming a constant conversion between the IR luminosity and star-formation
rate (SFR) of a galaxy, we study the evolution of the SFR density of the
Universe from z=0 to z=2.3. We find that the SFR density of the Universe
strongly increased with redshift from z=0 to z=1.3, but is nearly constant at
higher redshift out to z=2.3. As part of the online material accompanying this
article, we present source catalogs at 24um and 70um for both the GOODS-North
and -South fields.
|
We introduce a gauge invariant and string independent two-point fermion
correlator which is analyzed in the context of the Schwinger model (QED_2). We
also derive an effective infrared worldline action for this correlator, thus
enabling the computation of its infrared behavior. Finally, we briefly discuss
possible perspectives for the string independent correlator in the QED_3
effective models for the normal state of HTc superconductors.
|
We consider inverse curvature flows in $\Hh$ with star-shaped initial
hypersurfaces and prove that the flows exist for all time, and that the leaves
converge to infinity, become strongly convex exponentially fast and also more
and more totally umbilic. After an appropriate rescaling the leaves converge in
$C^\infty$ to a sphere.
|
In recent years, deep learning has made brilliant achievements in
Environmental Microorganism (EM) image classification. However, image
classification of small EM datasets has still not obtained good research
results. Therefore, researchers need to spend a lot of time searching for
models with good classification performance and suitable for the current
equipment working environment. To provide reliable references for researchers,
we conduct a series of comparison experiments on 21 deep learning models. The
experiment includes direct classification, imbalanced training, and
hyperparameter tuning experiments. During the experiments, we find
complementarities among the 21 models, which is the basis for feature fusion
related experiments. We also find that the data augmentation method of
geometric deformation is difficult to improve the performance of VTs (ViT,
DeiT, BotNet and T2T-ViT) series models. In terms of model performance,
Xception has the best classification performance, the ViT model consumes the
least time for training, and the ShuffleNet-V2 model has the least number of
parameters.
|
Within the interstellar medium, supernovae are thought to be the prevailing
agents in driving turbulence. Until recently, their effects on magnetic field
amplification in disk galaxies remained uncertain. Analytical models based on
the uncorrelated-ensemble approach predicted that any created field would be
expelled from the disk before it could be amplified significantly. By means of
direct simulations of supernova-driven turbulence, we demonstrate that this is
not the case. Accounting for galactic differential rotation and vertical
stratification, we find an exponential amplification of the mean field on
timescales of several hundred million years. We especially highlight the
importance of rotation in the generation of helicity by showing that a similar
mechanism based on Cartesian shear does not lead to a sustained amplification
of the mean magnetic field.
|
The Alexander dual of an arbitrary meet-semilattice is described explicitly.
Meet-distributive meet-semilattices whose Alexander dual is level are
characterized.
|
Let $(\xi(s))_{s\geq 0}$ be a standard Brownian motion in $d\geq 1$
dimensions and let $(D_s)_{s \geq 0}$ be a collection of open sets in $\R^d$.
For each $s$, let $B_s$ be a ball centered at 0 with $\vol(B_s) = \vol(D_s)$.
We show that $\E[\vol(\cup_{s \leq t}(\xi(s) + D_s))] \geq \E[\vol(\cup_{s \leq
t}(\xi(s) + B_s))]$, for all $t$. In particular, this implies that the expected
volume of the Wiener sausage increases when a drift is added to the Brownian
motion.
|
The deposition and intercalation of metal atoms can induce superconductivity
in monolayer and bilayer graphenes. For example, it has been experimentally
proved that Li-deposited graphene is a superconductor with critical temperature
$T_{c}$ of 5.9 K, Ca-intercalated bilayer graphene C$_{6}$CaC$_{6}$ and
K-intercalated epitaxial bilayer graphene C$_{8}$KC$_{8}$ are superconductors
with $T_{c}$ of 2-4 K and 3.6 K, respectively. However, the $T_{c}$ of them are
relatively low. To obtain higher $T_{c}$ in graphene-based superconductors,
here we predict a new Ca-intercalated bilayer graphene C$_{2}$CaC$_{2}$, which
shows higher Ca concentration than the C$_{6}$CaC$_{6}$. It is proved to be
thermodynamically and dynamically stable. The electronic structure,
electron-phonon coupling (EPC) and superconductivity of C$_{2}$CaC$_{2}$ are
investigated based on first-principles calculations. The EPC of
C$_{2}$CaC$_{2}$ mainly comes from the coupling between the electrons of
C-$p_{z}$ orbital and the high- and low-frequency vibration modes of C atoms.
The calculated EPC constant $\lambda$ of C$_{2}$CaC$_{2}$ is 0.75, and the
superconducting $T_{c}$ is 18.9 K, which is much higher than other
metal-intercalated bilayer graphenes. By further applying -4\% biaxial
compressive strain to C$_{2}$CaC$_{2}$, the $T_{c}$ can be boosted to 26.6 K.
Thus, the predicted C$_{2}$CaC$_{2}$ provides a new platform for realizing
superconductivity with the highest $T_{c}$ in bilayer graphenes.
|
Website fingerprinting (WF) is a well-know threat to users' web privacy. New
internet standards, such as QUIC, include padding to support defenses against
WF. Previous work only analyzes the effectiveness of defenses when users are
behind a VPN. Yet, this is not how most users browse the Internet. In this
paper, we provide a comprehensive evaluation of QUIC-padding-based defenses
against WF when users directly browse the web. We confirm previous claims that
network-layer padding cannot provide good protection against powerful
adversaries capable of observing all traffic traces. We further demonstrate
that such padding is ineffective even against adversaries with constraints on
traffic visibility and processing power. At the application layer, we show that
defenses need to be deployed by both first and third parties, and that they can
only thwart traffic analysis in limited situations. We identify challenges to
deploy effective WF defenses and provide recommendations to address them.
|
We study renormalization group flows among N=1 SCFTs realized on the
worldvolume of D3-branes probing toric Calabi-Yau singularities, thus admitting
a brane tiling description. The flows are triggered by masses for adjoint or
vector-like pairs of bifundamentals and are generalizations of the
Klebanov-Witten construction of the N=1 theory for the conifold starting from
the N=2 theory for the C^2/Z_2 orbifold. In order to preserve the toric
condition pairs of masses with opposite signs have to be switched on. We offer
a geometric interpretation of the flows as complex deformations of the
Calabi-Yau singularity preserving the toric condition. For orbifolds, we
support this interpretation by an explicit string amplitude computation of the
gauge invariant mass terms generated by imaginary self-dual 3-form fluxes in
the twisted sector. In agreement with the holographic a-theorem, the volume of
the Sasaki-Einstein 5-base of the Calabi-Yau cone always increases along the
flow.
|
Merging other branches into the current working branch is common in
collaborative software development. However, developers still heavily rely on
the textual merge tools to handle the complicated merge tasks. The latent
semantic merge conflicts may fail to be detected and degrade the software
quality. Regression testing is able to prevent regression faults and has been
widely used in real-world software development. However, the merged software
may fail to be well examined by rerunning the existing whole test suite.
Intuitively, if the test suite fails to cover the changes of different branches
at the same time, the merge conflicts would fail to be detected. Recently, it
has been proposed to conduct verification on 3-way merges, but this approach
does not support even some common cases such as different changes made to
different parts of the program. In this paper, we propose an approach of
regression unit test generation specifically for checking program merges
according to our proposed test oracles. And our general test oracles support us
to examine not only 3-way merges, but also 2-way and octopus merges.
Considering the conflicts may arise in other locations besides changed methods
of the project, we design an algorithm to select UUTs based on the dependency
analysis of the whole project. On this basis, we implement a tool called TOM to
generate unit tests for Java program merges. We also design the benchmark
MCon4J consisting of 389 conflict 3-way merges and 389 conflict octopus merges
to facilitate further studies on this topic. The experimental results show that
TOM finds 45 conflict 3- way merges and 87 conflicts octopus merges, while the
verification based tool fails to work on MCon4J.
|
A longstanding challenge for the Machine Learning community is the one of
developing models that are capable of processing and learning from very long
sequences of data. The outstanding results of Transformers-based networks
(e.g., Large Language Models) promotes the idea of parallel attention as the
key to succeed in such a challenge, obfuscating the role of classic sequential
processing of Recurrent Models. However, in the last few years, researchers who
were concerned by the quadratic complexity of self-attention have been
proposing a novel wave of neural models, which gets the best from the two
worlds, i.e., Transformers and Recurrent Nets. Meanwhile, Deep Space-State
Models emerged as robust approaches to function approximation over time, thus
opening a new perspective in learning from sequential data, followed by many
people in the field and exploited to implement a special class of (linear)
Recurrent Neural Networks. This survey is aimed at providing an overview of
these trends framed under the unifying umbrella of Recurrence. Moreover, it
emphasizes novel research opportunities that become prominent when abandoning
the idea of processing long sequences whose length is known-in-advance for the
more realistic setting of potentially infinite-length sequences, thus
intersecting the field of lifelong-online learning from streamed data.
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The anomalous Hall effect, a hallmark of broken time-reversal symmetry and
spin-orbit coupling, is frequently observed in magnetically polarized systems.
Its realization in non-magnetic systems, however, remains elusive. Here, we
report on the observation of anomalous Hall effect in nominally non-magnetic
KTaO3. Anomalous Hall effect emerges in reduced KTaO3 and shows an extrinsic to
intrinsic crossover. A paramagnetic behavior is observed in reduced samples
using first principles calculations and quantitative magnetometry. The observed
anomalous Hall effect follows the oxygen vacancy-induced magnetization
response, suggesting that the localized magnetic moments of the oxygen
vacancies scatter conduction electrons asymmetrically and give rise to
anomalous Hall effect. The anomalous Hall conductivity becomes insensitive to
scattering rate in the low temperature limit (T<5 K), implying that the Berry
curvature of the electrons on the Fermi surface controls the anomalous Hall
effect. Our observations describe a detailed picture of many-body interactions,
triggering anomalous Hall effect in a non-magnetic system.
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We have implemented a universal quantum logic gate between qubits stored in
the spin state of a pair of trapped calcium 40 ions. An initial product state
was driven to a maximally entangled state deterministically, with 83% fidelity.
We present a general approach to quantum state tomography which achieves good
robustness to experimental noise and drift, and use it to measure the spin
state of the ions. We find the entanglement of formation is 0.54.
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Microcavity lasers based on erbium-doped lithium niobate on insulator (LNOI),
which are key devices for LNOI integrated photonics, have attracted much
attention recently. In this Letter, we report the realization of a C-band
single-mode laser using Vernier effect in two coupled Erbium-doped LNOI
microrings with different radii under the pump of a 980-nm continuous laser.
The laser, operating stably over a large range of pumping power, has a pump
threshold of ~200 {\mu}W and a side-mode suppression ratio exceeding 26 dB. The
high-performance LNOI single-mode laser will promote the development of lithium
niobate integrated photonics.
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In this work we present a numerical method for the Optimal Mass
Transportation problem. Optimal Mass Transportation (OT) is an active research
field in mathematics.It has recently led to significant theoretical results as
well as applications in diverse areas. Numerical solution techniques for the OT
problem remain underdeveloped. The solution is obtained by solving the second
boundary value problem for the MA equation, a fully nonlinear elliptic partial
differential equation (PDE). Instead of standard boundary conditions the
problem has global state constraints. These are reformulated as a tractable
local PDE. We give a proof of convergence of the numerical method, using the
theory of viscosity solutions. Details of the implementation and a fast
solution method are provided in the companion paper arXiv:1208.4870.
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The CCKS2019 shared task was devoted to inter-personal relationship
extraction. Given two person entities and at least one sentence containing
these two entities, participating teams are asked to predict the relationship
between the entities according to a given relation list. This year, 358 teams
from various universities and organizations participated in this task. In this
paper, we present the task definition, the description of data and the
evaluation methodology used during this shared task. We also present a brief
overview of the various methods adopted by the participating teams. Finally, we
present the evaluation results.
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We consider competing pair-density-wave (PDW) and $d$-wave superconducting
states in a magnetic field. We show that PDW order appears in the cores of
$d$-wave vortices, driving checkerboard charge-density-wave (CDW) order in the
vortex cores, which is consistent with experimental observations. Furthermore,
we find an additional CDW order that appears on a ring outside the vortex
cores. This CDW order varies with a period that is twice that of the
checkerboard CDW and it only appears where both PDW and $d$-wave order
co-exist. The observation of this additional CDW order would provide strong
evidence for PDW order in the pseudogap phase of the cuprates. We further argue
that the CDW seen by nuclear magnetic resonance at high fields is due to a PDW
state that emerges when a magnetic field is applied.
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We constrain the mass-to-light ratios, gas mass fractions, baryon mass
fractions and the ratios of total to luminous mass for a sample of eight nearby
relaxed galaxy groups and clusters: A262, A426, A478, A1795, A2052, A2063,
A2199 and MKW4s. We use ASCA spatially resolved spectroscopic X-ray
observations and ROSAT PSPC images to constrain the total and gas masses of
these clusters. To measure cluster luminosities we use galaxy catalogs
resulting from the digitization and automated processing of the second
generation Palomar Sky Survey plates calibrated with CCD images in the
Gunn-Thuan g, r, and i bands.
Under the assumption of hydrostatic equilibrium and spherical symmetry, we
can measure the total masses of clusters from their intra-cluster gas
temperature and density profiles. Spatially resolved ASCA spectra show that the
gas temperature decreases with increasing distance from the center. By
comparison, the assumption that the gas is isothermal results in an
underestimate of the total mass at small radii, and an overestimate at large
cluster radii.
We have obtained luminosity functions for all clusters in our sample. After
correcting for background and foreground galaxies, we estimate the total
cluster luminosity using Schechter function fits to the galaxy catalogs. In the
three lowest redshift clusters where we can sample to fainter absolute
magnitudes, we have detected a flattening of the luminosity function at
intermediate magnitudes and a rise at the faint end. These clusters were fit
with a sum of two Schechter functions. The remaining clusters were well fit
with a single Schechter function.
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The goal of this paper is to develop a continuous optimization-based
refinement of the reference trajectory to 'push it out' of the
obstacle-occupied space in the global phase for Multi-rotor Aerial Vehicles in
unknown environments. Our proposed approach comprises two planners: a global
planner and a local planner. The global planner refines the initial reference
trajectory when the trajectory goes either through an obstacle or near an
obstacle and lets the local planner calculate a near-optimal control policy.
The global planner comprises two convex programming approaches: the first one
helps to refine the reference trajectory, and the second one helps to recover
the reference trajectory if the first approach fails to refine. The global
planner mainly focuses on real-time performance and obstacles avoidance,
whereas the proposed formulation of the constrained nonlinear model predictive
control-based local planner ensures safety, dynamic feasibility, and the
reference trajectory tracking accuracy for low-speed maneuvers, provided that
local and global planners have mean computation times 0.06s (15Hz) and 0.05s
(20Hz), respectively, on an NVIDIA Jetson Xavier NX computer. The results of
our experiment confirmed that, in cluttered environments, the proposed approach
outperformed three other approaches: sampling-based pathfinding followed by
trajectory generation, a local planner, and graph-based pathfinding followed by
trajectory generation.
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We consider the phase ordering dynamics of an isolated quasi-two-dimensional
spin-1 Bose gas quenched into an easy-plane ferromagnetic phase. Preparing the
initial system in an unmagnetized anti-ferromagnetic state the subsequent
ordering involves both polar core and Mermin-Ho spin vortices, with the ratio
between the different vortices controllable by the quench parameter.
Ferromagnetic domain growth occurs as these vortices annihilate. The distinct
dynamics of the two types of vortices means that the domain growth law is
determined by two macroscopic length scales, violating the standard dynamic
scaling hypothesis. Nevertheless we find that universality of the ordering
process manifests in the decay laws for the spin vortices.
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We introduce a spatially explicit model for the competition between type $a$
and type $b$ alleles. Each vertex of the $d$-dimensional integer lattice is
occupied by a diploid individual, which is in one of three possible states or
genotypes: $aa$, $ab$ or $bb$. We are interested in the long-term behavior of
the gene frequencies when Mendel's law of segregation does not hold. This
results in a voter type model depending on four parameters; each of these
parameters measures the strength of competition between genes during meiosis.
We prove that with or without a spatial structure, type $a$ and type $b$
alleles coexist at equilibrium when homozygotes are poor competitors. The
inclusion of a spatial structure, however, reduces the parameter region where
coexistence occurs.
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We investigate effective interactions between a colloidal particle, immersed
in a binary mixture of smaller spheres, and a semipermeable membrane. The
colloid is modeled as a big hard sphere and the membrane is represented as an
infinitely thin surface which is fully permeable to one of the smaller spheres
and impermeable to the other one. Within the framework of the density
functional theory we evaluate the depletion potentials, and we consider two
different approximate theories - the simple Asakura-Oosawa approximation and
the accurate White-Bear version of the fundamental measure theory. The
effective potentials are compared with the corresponding potentials for a hard,
nonpermeable wall. Using statistical-mechanical sum rules we argue that the
contact value of the depletion potential between a colloid and a semipermeable
membrane is smaller in magnitude than the potential between a colloid and a
hard wall. Explicit calculations confirm that the colloid-semipermeable
membrane effective interactions are generally weaker than these near a hard
nonpermeable wall. This effect is more pronounced for smaller osmotic
pressures. The depletion potential for a colloidal particle inside a
semipermeable vesicle is stronger than the potential for the colloidal particle
located outside of a vesicle. We find that the asymptotic decay of the
depletion potential for the semipermeable membrane is similar to that for the
nonpermeable wall and reflects the asymptotics of the total correlation
function of the corresponding binary mixture of smaller spheres. Our results
demonstrate that the ability of the membrane to change its shape constitutes an
important factor in determining the effective interactions between the
semipermeable membrane and the colloidal macroparticle.
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A gradient boosting decision tree (GBDT), which aggregates a collection of
single weak learners (i.e. decision trees), is widely used for data mining
tasks. Because GBDT inherits the good performance from its ensemble essence,
much attention has been drawn to the optimization of this model. With its
popularization, an increasing need for model interpretation arises. Besides the
commonly used feature importance as a global interpretation, feature
contribution is a local measure that reveals the relationship between a
specific instance and the related output. This work focuses on the local
interpretation and proposes an unified computation mechanism to get the
instance-level feature contributions for GBDT in any version. Practicality of
this mechanism is validated by the listed experiments as well as applications
in real industry scenarios.
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In this paper, we present a statistical-mechanical analysis of deep learning.
We elucidate some of the essential components of deep learning---pre-training
by unsupervised learning and fine tuning by supervised learning. We formulate
the extraction of features from the training data as a margin criterion in a
high-dimensional feature-vector space. The self-organized classifier is then
supplied with small amounts of labelled data, as in deep learning. Although we
employ a simple single-layer perceptron model, rather than directly analyzing a
multi-layer neural network, we find a nontrivial phase transition that is
dependent on the number of unlabelled data in the generalization error of the
resultant classifier. In this sense, we evaluate the efficacy of the
unsupervised learning component of deep learning. The analysis is performed by
the replica method, which is a sophisticated tool in statistical mechanics. We
validate our result in the manner of deep learning, using a simple iterative
algorithm to learn the weight vector on the basis of belief propagation.
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Vanishing (and exploding) gradients effect is a common problem for recurrent
neural networks with nonlinear activation functions which use backpropagation
method for calculation of derivatives. Deep feedforward neural networks with
many hidden layers also suffer from this effect. In this paper we propose a
novel universal technique that makes the norm of the gradient stay in the
suitable range. We construct a way to estimate a contribution of each training
example to the norm of the long-term components of the target function s
gradient. Using this subroutine we can construct mini-batches for the
stochastic gradient descent (SGD) training that leads to high performance and
accuracy of the trained network even for very complex tasks. We provide a
straightforward mathematical estimation of minibatch s impact on for the
gradient norm and prove its correctness theoretically. To check our framework
experimentally we use some special synthetic benchmarks for testing RNNs on
ability to capture long-term dependencies. Our network can detect links between
events in the (temporal) sequence at the range approx. 100 and longer.
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Three steps in the development of the maximum likelihood (ML) method are
presented. At first, the application of the ML method and Fisher information
notion in the model selection analysis is described (Chapter 1). The
fundamentals of differential geometry in the construction of the statistical
space are introduced, illustrated also by examples of the estimation of the
exponential models. At second, the notions of the relative entropy and the
information channel capacity are introduced (Chapter 2). The observed and
expected structural information principle (IP) and the variational IP of the
modified extremal physical information (EPI) method of Frieden and Soffer are
presented and discussed (Chapter 3). The derivation of the structural IP based
on the analyticity of the logarithm of the likelihood function and on the
metricity of the statistical space of the system is given. At third, the use of
the EPI method is developed (Chapters 4-5). The information channel capacity is
used for the field theory models classification. Next, the modified Frieden and
Soffer EPI method, which is a nonparametric estimation that enables the
statistical selection of the equation of motions of various field theory models
(Chapter 4) or the distribution generating equations of statistical physics
models (Chapter 5) is discussed. The connection between entanglement of the
momentum degrees of freedom and the mass of a particle is analyzed. The
connection between the Rao-Cramer inequality, the causality property of the
processes in the Minkowski space-time and the nonexistence of tachions is
shown. The generalization of the Aoki-Yoshikawa sectoral productivity
econophysical model is also presented (Chapter 5). Finally, the Frieden EPI
method of the analysis of the EPR-Bhom experiment is presented. It differs from
the Frieden approach by the use of the information geometry methods.
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The recent experiments revealed a remarkable possibility for the absence of
the disparity between the phase diagrams of the electron- and hole-doped
cuprate superconductors, while such an aspect should be also reflected in the
dressing of the electrons. Here the phase diagram of the electron-doped cuprate
superconductors and the related exotic features of the anisotropic dressing of
the electrons are studied based on the kinetic-energy driven superconductivity.
It is shown that although the optimized Tc in the electron-doped side is much
smaller than that in the hole-doped case, the electron- and hole-doped cuprate
superconductors rather resemble each other in the doping range of the
superconducting dome, indicating an absence of the disparity between the phase
diagrams of the electron- and hole-doped cuprate superconductors. In
particular, the anisotropic dressing of the electrons due to the strong
electron's coupling to a strongly dispersive spin excitation leads to that the
electron Fermi surface is truncated to form the disconnected Fermi arcs
centered around the nodal region. Concomitantly, the dip in the peak-dip-hump
structure of the quasiparticle excitation spectrum is directly associated with
the corresponding peak in the quasiparticle scattering rate, while the
dispersion kink is always accompanied by the corresponding inflection point in
the total self-energy, as the dip in the peak-dip-hump structure and dispersion
kink in the hole-doped counterparts. The theory also predicts that both the
normal and anomalous self-energies exhibit the well-pronounced low-energy
peak-structures.
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Let $X$ be a fine and saturated log scheme, and let $G$ be a commutative
finite flat group scheme over the underlying scheme of $X$. If $G$-torsors for
the fppf topology can be thought of as being unramified objects by nature, then
$G$-torsors for the log flat topology allow us to consider tame ramification.
Using the results of Kato, we define a concept of Galois structure for these
torsors, then we generalize the author's previous constructions
(class-invariant homomorphism for semi-stable abelian varieties) in this new
setting, thus dropping some restrictions.
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Let $A$ be any commutative unital ring and let $\operatorname{GL}_{2,A}$ be
the general linear group scheme on $A$ of rank $2$. We study the representation
theory of $\operatorname{GL}_{2,A}$ and the symmetric powers
$\operatorname{Sym}^d(V)$, where $(V, \Delta)$ is the standard right comodule
on $\operatorname{GL}_{2,A}$. We prove a refined Weyl character formula for
$\operatorname{Sym}^d(V)$. There is for any integer $d \geq 1$ a (canonical)
refined weight space decomposition $\operatorname{Sym}^d(V) \cong \oplus_i
\operatorname{Sym}^d(V)^i$ where each direct summand
$\operatorname{Sym}^d(V)^i$ is a comodule on $N \subseteq
\operatorname{GL}_{2,A}$. Here $N$ is the schematic normalizer of the diagonal
torus $T \subseteq \operatorname{GL}_{2,A}$. We prove a character formula for
the direct summands of $\operatorname{Sym}^d(V)$ for any integer $d \geq 1$.
This refined Weyl character formula implies the classical Weyl character
formula. As a Corollary we get a refined Weyl character formula for the pull
back $\operatorname{Sym}^d(V \otimes K)$ as a comodule on
$\operatorname{GL}_{2,K}$ where $K$ is any field. We also calculate explicit
examples involving the symmetric powers, symmetric tensors and their duals. The
refined weight space decomposition exists in general for group schemes such as
$\operatorname{GL}_{2,A}$ and $\operatorname{SL}_{2,A}$. The study may have
applications to the study of groups $G$ such as $\operatorname{SL}(n,k)$ and
$\operatorname{GL}(n,k)$ and quotients $G/H$ where $k$ is an arbitrary field
(or a Dedekind domain) and $H \subseteq G$ is a closed subgroup. The refined
weight space decomposition of $S_{\lambda}(V)$ has a relation with irreducible
module over a field of positive characteristic. In an example I prove it
recovers the irreducible module $V(\lambda) \subsetneq S_{\lambda}(V)$.
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Observations of young stars hosting transition disks show that several of
them have high accretion rates, despite their disks presenting extended
cavities in their dust component. This represents a challenge for theoretical
models, which struggle to reproduce both features. We explore if a disk
evolution model, including a dead zone and disk dispersal by X-ray
photoevaporation, can explain the high accretion rates and large gaps (or
cavities) measured in transition disks. We implement a dead zone turbulence
profile and a photoevaporative mass loss profile into numerical simulations of
gas and dust. We perform a population synthesis study of the gas component, and
obtain synthetic images and SED of the dust component through radiative
transfer calculations. This model results in long lived inner disks and fast
dispersing outer disks, that can reproduce both the accretion rates and gap
sizes observed in transition disks. For a dead zone of turbulence $\alpha_{dz}
= 10^{-4}$ and extent $r_{dz}$ = 10 AU, our population synthesis study shows
that $63\%$ of our transition disks are accreting with $\dot{M}_g > 10^{-11}
M_\odot/yr$ after opening a gap. Among those accreting transition disks, half
display accretion rates higher than $5\times10^{-10} M_\odot/yr$ . The dust
component in these disks is distributed in two regions: in a compact inner disk
inside the dead zone, and in a ring at the outer edge of the photoevaporative
gap, which can be located between 20 AU and 100 AU. Our radiative transfer
calculations show that the disk displays an inner disk and an outer ring in the
millimeter continuum, a feature observed in some transition disks. A disk model
considering X-ray photoevaporative dispersal in combination with dead zones can
explain several of the observed properties in transition disks including: the
high accretion rates, the large gaps, and long-lived inner disks at
mm-emission.
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Interleaved Reed-Solomon codes admit efficient decoding algorithms which
correct burst errors far beyond half the minimum distance in the random errors
regime, e.g., by computing a common solution to the Key Equation for each
Reed-Solomon code, as described by Schmidt et al. If this decoder does not
succeed, it may either fail to return a codeword or miscorrect to an incorrect
codeword, and good upper bounds on the fraction of error matrices for which
these events occur are known. The decoding algorithm immediately applies to
interleaved alternant codes as well, i.e., the subfield subcodes of interleaved
Reed-Solomon codes, but the fraction of decodable error matrices differs, since
the error is now restricted to a subfield. In this paper, we present new
general lower and upper bounds on the fraction of error matrices decodable by
Schmidt et al.'s decoding algorithm, thereby making it the only decoding
algorithm for interleaved alternant codes for which such bounds are known.
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We analyze systematics in the asteroseismological mass determination methods
in pulsating PG 1159 stars. We compare the seismic masses resulting from the
comparison of the observed mean period spacings with the usually adopted
asymptotic period spacings, and the average of the computed period spacings.
Computations are based on full PG1159 evolutionary models with stellar masses
ranging from 0.530 to 0.741 Mo that take into account the complete evolution of
progenitor stars. We conclude that asteroseismology is a precise and powerful
technique that determines the masses to a high internal accuracy, but it
depends on the adopted mass determination method. In particular, we find that
in the case of pulsating PG 1159 stars characterized by short pulsation
periods, like PG 2131+066 and PG 0122+200, the employment of the asymptotic
period spacings overestimates the stellar mass by about 0.06 Mo as compared
with inferences from the average of the period spacings. In this case, the
discrepancy between asteroseismological and spectroscopical masses is markedly
reduced when use is made of the mean period spacing instead of the asymptotic
period spacing.
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The ice Ansatz on matrix solutions of the Yang-Baxter equation is weakened to
a condition which we call rime. Generic rime solutions of the Yang-Baxter
equation are described. We prove that the rime non-unitary (respectively,
unitary) R-matrix is equivalent to the Cremmer-Gervais (respectively, boundary
Cremmer-Gervais) solution. Generic rime classical r-matices satisfy the
(non-)homogeneous associative classical Yang-Baxter equation.
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We consider a composite convex minimization problem associated with
regularized empirical risk minimization, which often arises in machine
learning. We propose two new stochastic gradient methods that are based on
stochastic dual averaging method with variance reduction. Our methods generate
a sparser solution than the existing methods because we do not need to take the
average of the history of the solutions. This is favorable in terms of both
interpretability and generalization. Moreover, our methods have theoretical
support for both a strongly and a non-strongly convex regularizer and achieve
the best known convergence rates among existing nonaccelerated stochastic
gradient methods.
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We study atom-ion scattering in the ultracold regime. To this aim, an
analytical model based on the multichannel quantum defect formalism is
developed and compared to close-coupled numerical calculations. We investigate
the occurrence of magnetic Feshbach resonances focusing on the specific 40Ca+ -
Na system. The presence of several resonances at experimentally accessible
magnetic fields should allow the atom-ion interaction to be precisely tuned. A
fully quantum-mechanical study of charge exchange processes shows that
charge-exchange rates should remain small even in the presence of resonance
effects. Most of our results can be cast in a system-independent form and are
important for the realization of the charge-neutral ultracold systems.
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The emergence of online enterprises spread across continents have given rise
to the need for expert identification in this domain. Scenarios that includes
the intention of the employer to find tacit expertise and knowledge of an
employee that is not documented or self-disclosed has been addressed in this
article. The existing reputation based approaches towards expertise ranking in
enterprises utilize PageRank, normal distribution, and hidden Markov model for
expertise ranking. These models suffer issue of negative referral, collusion,
reputation inflation, and dynamism. The authors have however proposed a
Bayesian approach utilizing beta probability distribution based reputation
model for employee ranking in enterprises. The experimental results reveal
improved performance compared to previous techniques in terms of Precision and
Mean Average Error (MAE) with almost 7% improvement in precision on average for
the three data sets. The proposed technique is able to differentiate categories
of interactions in a dynamic context. The results reveal that the technique is
independent of the rating pattern and density of data.
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Kontsevich and Soibelman defined the notion of Donaldson-Thomas invariants of
a 3d Calabi-Yau category with a stability condition. A family of examples of
such categories can be constructed from an arbitrary cluster variety. The
corresponding Donaldson-Thomas invariants are encoded by a special formal
automorphism of the cluster variety, known as Donaldson-Thomas transformation.
Fix two integers $m$ and $n$ with $1<m<m+1<n$. It is known that the
configuration space $\mathrm{Conf}_n(\mathbb{P}^{m-1})$, closely related to
Grassmannian $\mathrm{Gr}_m(n)$, is a cluster Poisson variety. In this paper we
determine the Donaldson-Thomas transformation of
$\mathrm{Conf}_n(\mathbb{P}^{m-1})$ as an explicitly defined birational
automorphism of $\mathrm{Conf}_n(\mathbb{P}^{m-1})$. Its variant acts on the
Grassmannian by a birational automorphism.
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We introduce a novel network-adaptive algorithm that is suitable for
alleviating network packet losses for low-latency interactive communications
between a source and a destination. Our network-adaptive algorithm estimates in
real-time the best parameters of a recently proposed streaming code that uses
forward error correction (FEC) to correct both arbitrary and burst losses,
which cause a crackling noise and undesirable jitters, respectively in audio.
In particular, the destination estimates appropriate coding parameters based on
its observed packet loss pattern and sends them back to the source for updating
the underlying code. Besides, a new explicit construction of practical
low-latency streaming codes that achieve the optimal tradeoff between the
capability of correcting arbitrary losses and the capability of correcting
burst losses is provided. Simulation evaluations based on statistical losses
and real-world packet loss traces reveal the following: (i) Our proposed
network-adaptive algorithm combined with our optimal streaming codes can
achieve significantly higher performance compared to uncoded and non-adaptive
FEC schemes over UDP (User Datagram Protocol); (ii) Our explicit streaming
codes can significantly outperform traditional MDS (maximum-distance separable)
streaming schemes when they are used along with our network-adaptive algorithm.
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The XX model with uniform couplings represents the most natural choice for
quantum state transfer through spin chains. Given that it has long been
established that single-qubit states cannot be transferred with perfect
fidelity in this model, the notion of pretty good state transfer has been
recently introduced as a relaxation of the constraints on fidelity. In this
paper, we study the transfer of multi-qubit entangled and unentangled states
through unmodulated spin chains, and we prove that it is possible to have
pretty good state transfer of any multi-particle state. This significantly
generalizes the previous results on single-qubit state transfer, and opens way
to using uniformly coupled spin chains as quantum channels for the transfer of
arbitrary states of any dimension. Our results could be tested with current
technology.
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This is the first of two papers devoted to connections between asymptotic
functions of groups and computational complexity. One of the main results of
this paper states that if for every $m$ the first $m$ digits of a real number
$\alpha\ge 4$ are computable in time $\le C2^{2^{Cm}}$ for some constant $C>0$
then $n^\alpha$ is equivalent (``big O'') to the Dehn function of a finitely
presented group. The smallest isodiametric function of this group is
$n^{3/4\alpha}$. On the other hand if $n^\alpha$ is equivalent to the Dehn
function of a finitely presented group then the first $m$ digits of $\alpha$
are computable in time $\le C2^{2^{2^{Cm}}}$ for some constant $C$. This
implies that, say, functions $n^{\pi+1}$, $n^{e^2}$ and $n^\alpha$ for all
rational numbers $\alpha\ge 4$ are equivalent to the Dehn functions of some
finitely presented group and that $n^\pi$ and $n^\alpha$ for all rational
numbers $\alpha\ge 3$ are equivalent to the smallest isodiametric functions of
finitely presented groups.
Moreover we describe all Dehn functions of finitely presented groups $\succ
n^4$ as time functions of Turing machines modulo two conjectures:
\begin{enumerate} \item Every Dehn function is equivalent to a superadditive
function. \item The square root of the time function of a Turing machine is
equivalent to the time function of a Turing machine. \end{enumerate}
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We study the behavior of non-Markovianity with respect to the localization of
the initial environmental state. The "amount" of non-Markovianity is measured
using divisibility and distinguishability as indicators, employing several
schemes to construct the measures. The system used is a qubit coupled to an
environment modeled by an Ising spin chain kicked by ultra-short pulses of a
magnetic field. In the integrable regime, non-Markovianity and localization do
not have a simple relation, but as the chaotic regime is approached, simple
relations emerge, which we explore in detail. We also study the
non-Markovianity measures in the space of the parameters of the spin coherent
states and point out that the pattern that appears is robust under the choice
of the interaction Hamiltonian but does not have a KAM-like phase-space
structure.
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Subsets and Splits