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Related papers: Moderate deviations of generalized $N$-urn Ehrenfe…

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The Moderate Deviations Principle (MDP) is well-understood for sums of independent random variables, worse understood for stationary random sequences, and scantily understood for random fields. Here it is established for some planary random…

Probability · Mathematics 2019-09-25 Boris Tsirelson

We introduce a modified Benamou-Brenier type approach leading to a Wasserstein type distance that allows global invariance, specifically, isometries, and we show that the problem can be summarized to orthogonal transformations. This…

Machine Learning · Statistics 2025-03-24 Kevine Meugang Toukam

The Wasserstein metric is introduced as a probabilistic method to enable quantitative evaluations of LES combustion models. The Wasserstein metric can directly be evaluated from scatter data or statistical results using probabilistic…

Data Analysis, Statistics and Probability · Physics 2017-06-06 Ross Johnson , Hao Wu , Matthias Ihme

We establish a moderate deviations principle (MDP) for the log-determinant $\log | \det (M_n) |$ of a Wigner matrix $M_n$ matching four moments with either the GUE or GOE ensemble. Further we establish Cram\'er--type moderate deviations and…

Probability · Mathematics 2013-01-16 Hanna Döring , Peter Eichelsbacher

The recently proposed Ehrenfest M-urn model with interactions on a ring is considered as a paradigm model which can exhibit a variety of distinct nonequilibrium steady states. Unlike the previous three-urn model on a ring which consists of…

Statistical Mechanics · Physics 2024-03-26 Chi-Ho Cheng , Pik-Yin Lai

We prove large deviation principles for the distribution of the empirical measure of the eigenvalues of Lax matrices following the Generalized Gibbs ensembles of the classical Toda chain introduced in [10]. We deduce the almost sure…

Probability · Mathematics 2025-10-23 Alice Guionnet , Ronan Memin

We provide explicit bounds on the Wasserstein distance between discrete time martingales and the standard normal distribution. The proofs are based on a combination of Lindeberg's and Stein's method.

Probability · Mathematics 2018-08-14 Adrian Röllin

The ultraconfined light of plasmonic modes put their effective wavelength close to the mean free path of electrons inside the metal electron gas. The Drude model, which can not take the repulsive interactions of electrons into account, then…

Optics · Physics 2021-06-23 Emilie Sakat , Antoine Moreau , Jean-Paul Hugonin

Large and moderate deviation principles are proved for Engel continued fractions, a new type of continued fraction expansion with non-decreasing partial quotients in number theory.

Probability · Mathematics 2016-08-29 Lulu Fang , Lei Shang

Several hydrodynamic models the atomic Bose-Einstein condensate beyond the mean-field approximation are discussed together from one point of view. All these models are derived from microscopic quantum description. The derivation is made…

Quantum Gases · Physics 2021-05-05 Pavel A. Andreev

This paper is focused on the moderate-deviations analysis of binary hypothesis testing. The analysis relies on a concentration inequality for discrete-parameter martingales with bounded jumps, where this inequality forms a refinement to the…

Information Theory · Computer Science 2016-11-17 Igal Sason

This article is dedicated to the estimation of Wasserstein distances and Wasserstein costs between two distinct continuous distributions $F$ and $G$ on $\mathbb R$. The estimator is based on the order statistics of (possibly dependent)…

Statistics Theory · Mathematics 2017-10-31 Philippe Berthet , Jean-Claude Fort , Thierry Klein

With the aid of simple analytical computations for the Ehrenfest model, we clarify some basic features of macroscopic irreversibility. The stochastic character of the model allows us to give a non-ambiguous interpretation of the general…

Statistical Mechanics · Physics 2019-05-07 Marco Baldovin , Lorenzo Caprini , Angelo Vulpiani

The purpose of this paper is to ensure the conditions of G\"artner-Ellis Theorem for evaluations of the empirical measure. We show that up-to-date conditions for ensuring the convergence to a quasi-stationary distribution can be applied…

Probability · Mathematics 2020-04-21 Aurélien Velleret

In this study, we analyzed urn models by solving the discrete-time master equation using an expansion in moments. This approach is a viable alternative to conventional methods, such as system-size expansion, allowing for the determination…

Statistical Mechanics · Physics 2024-08-22 Manuel Eduardo Hernández-García , Jorge Velázquez-Castro

We consider finite $\beta$-ensembles $\mathcal X_{n,\beta}^{\mathbb F}$ with $n$ points on $\mathbb F$, where $\mathbb F$ denotes either the real line or the complex plane. Let $U$ be a bounded subset of $ \mathbb F$ such that $\partial U$…

Probability · Mathematics 2026-05-19 Kartick Adhikari , Sitanath Majumder

We consider a class of tempered subordinators, namely a class of subordinators with one-dimensional marginal tempered distributions which belong to a family studied in [3]. The main contribution in this paper is a non-central moderate…

Probability · Mathematics 2020-11-05 Nikolai Leonenko , Claudio Macci , Barbara Pacchiarotti

The term moderate deviations is often used in the literature to mean a class of large deviation principles that, in some sense, fills the gap between a convergence in probability of some random variables to a constant and a weak convergence…

Probability · Mathematics 2024-11-20 Rita Giuliano , Claudio Macci , Barbara Pacchiarotti

We analytically demonstrate the emergence of surface non-Hermitian boundary contributions that appear in an extended form of the quantum Ehrenfest theorem and are crucial (although so far overlooked) in the calculation of optical matrix…

Mesoscale and Nanoscale Physics · Physics 2018-07-30 Georgios Konstantinou , Konstantinos Moulopoulos

We use Stein's method to bound the Wasserstein distance of order $2$ between a measure $\nu$ and the Gaussian measure using a stochastic process $(X_t)_{t \geq 0}$ such that $X_t$ is drawn from $\nu$ for any $t > 0$. If the stochastic…

Probability · Mathematics 2020-05-12 Thomas Bonis