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We investigate the behavior of the Gibbs-Shannon entropy of the stationary nonequilibrium measure describing a one-dimensional lattice gas, of L sites, with symmetric exclusion dynamics and in contact with particle reservoirs at different…

Statistical Mechanics · Physics 2015-05-13 B. Derrida , J. L. Lebowitz , E. R. Speer

This work focuses on the temporal average of the backward Euler--Maruyama (BEM) method, which is used to approximate the ergodic limit of stochastic ordinary differential equations with super-linearly growing drift coefficients. We give the…

Numerical Analysis · Mathematics 2026-03-06 Diancong Jin

We provide rates of convergence in the central limit theorem in terms of projective criteria for adapted stationary sequences of centered random variables taking values in Banach spaces, with finite moment of order $p \in ]2,3]$ as soon as…

Probability · Mathematics 2025-02-21 Aurélie Bigot

In this article we review recent generalisations of the central limit theorem for the sum of specially correlated (or q-independent) variables, focusing on q greater or equal than 1. Specifically, this kind of correlation turns the…

Statistical Mechanics · Physics 2007-12-16 Silvio M. Duarte Queiros , Constantino Tsallis

We prove the central limit theorem (CLT) for a sequence of independent zero-mean random variables $\xi_j$, perturbed by predictable multiplicative factors $\lambda_j$ with values in intervals $[\underline\lambda_j,\overline\lambda_j]$. It…

Probability · Mathematics 2015-08-31 Dmitry B. Rokhlin

We give an overview of various results and methods related to information-theoretic distances of R\'enyi type in the light of their applications to the central limit theorem (CLT). The first part (Sections 1-9) is devoted to the total…

Information Theory · Computer Science 2025-03-07 S. G. Bobkov , G. P. Chistyakov , F. Götze

We introduce a family of scale-invariant entropy statistics derived from logarithmically aggregated distance distributions of point processes, with prime numbers serving as a motivating example. The construction associates to each finite…

Methodology · Statistics 2026-04-06 Mohamed Gewily

Contrastive representation learning (CRL) underpins many modern foundation models. Despite recent theoretical progress, existing analyses suffer from several key limitations: (i) the statistical consistency of CRL remains poorly understood;…

Machine Learning · Computer Science 2026-05-29 Yuanfan Li , Xiyuan Wei , Tianbao Yang , Yiming Ying

Under certain conditions, the rate of increase of the statistical entropy of a simple, fully chaotic, conservative system is known to be given by a single number, characteristic of this system, the Kolmogorov-Sinai entropy rate. This…

Statistical Mechanics · Physics 2019-08-17 V. Latora , M. Baranger , A. Rapisarda , C. Tsallis

Consider a random vector $\mathbf{y}=\mathbf{\Sigma}^{1/2}\mathbf{x}$, where the $p$ elements of the vector $\mathbf{x}$ are i.i.d. real-valued random variables with zero mean and finite fourth moment, and $\mathbf{\Sigma}^{1/2}$ is a…

Statistics Theory · Mathematics 2023-02-27 Nestor Parolya , Johannes Heiny , Dorota Kurowicka

A class of probability distributions is characterized via equalities in law between two order statistics shifted by independent exponential variables. An explicit formula for the quintile function of the identified family of distributions…

Probability · Mathematics 2011-07-26 M. Ahsanullah , V. B. Nevzorov , George P. Yanev

We consider the existence of the integrated density of states (IDS) of the Anderson model on the Hilbert space $\ell^2(\mathbb{Z}^d)$ as analogues to the law of large numbers (LLN). In this work, we prove the analogues central limit theorem…

Mathematical Physics · Physics 2024-12-04 Dhriti Ranjan Dolai

A local convergence rate is established for a Gauss orthogonal collocation method applied to optimal control problems with control constraints. If the Hamiltonian possesses a strong convexity property, then the theory yields convergence for…

Numerical Analysis · Mathematics 2018-09-17 William W. Hager , Jun Liu , Subhashree Mohapatra , Anil V. Rao , Xiang-Sheng Wang

We apply the methods of modern analytic bootstrap to the critical $O(N)$ model in a $1/N$ expansion. At infinite $N$ the model possesses higher spin symmetry which is weakly broken as we turn on $1/N$. By studying consistency conditions for…

High Energy Physics - Theory · Physics 2020-01-29 Luis F. Alday , Johan Henriksson , Mark van Loon

In this article, we try to give an answer to the simple question: ``\textit{What is the critical growth rate of the dimension $p$ as a function of the sample size $n$ for which the Central Limit Theorem holds uniformly over the collection…

Probability · Mathematics 2020-08-12 Debraj Das , Soumendra Lahiri

We consider $n\times n$ real symmetric and Hermitian Wigner random matrices $n^{-1/2}W$ with independent (modulo symmetry condition) entries and the (null) sample covariance matrices $n^{-1}X^*X$ with independent entries of $m\times n$…

Probability · Mathematics 2009-09-25 A. Lytova , L. Pastur

In this work, we provide a refinement of the selective CLT result of Tian and Taylor (2015), which allows for selective inference in non-parametric settings by adjusting for the asymptotic Gaussian limit for selection. Under some regularity…

Methodology · Statistics 2017-09-29 Jelena Markovic , Jonathan Taylor

We determine the asymptotic distribution of the sum of correlated variables described by a matrix product ansatz with finite matrices, considering variables with finite variances. In cases when the correlation length is finite, the law of…

Statistical Mechanics · Physics 2014-01-08 Florian Angeletti , Eric Bertin , Patrice Abry

Entanglement entropies have revealed, in the last years, to be a powerful tool to extract information about the physics of condensed-matter systems. In the first part of this thesis, we show how to extract essential details about the…

Strongly Correlated Electrons · Physics 2013-09-17 Luca Taddia

Threshold methods are popular for ordinal regression problems, which are classification problems for data with a natural ordinal relation. They learn a one-dimensional transformation (1DT) of observations of the explanatory variable, and…

Machine Learning · Computer Science 2024-05-24 Ryoya Yamasaki , Toshiyuki Tanaka