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Consider a population of individuals belonging to an infinity number of types, and assume that type proportions follow the two-parameter Poisson-Dirichlet distribution. A sample of size n is selected from the population. The total number of…

Probability · Mathematics 2016-10-12 Stefano Favaro , Shui Feng , Fuqing Gao

In this paper, we study the Moderate Deviation Principle for a perturbed stochastic heat equation in the whole space $\rr^d, d\ge1$. This equation is driven by a Gaussian noise, white in time and correlated in space, and the differential…

Probability · Mathematics 2015-09-08 Yumeng Li , Ran Wang , Nian Yao , Shuguang Zhang

In these notes we give a simple proof of the second-order Boltzmann-Gibbs Principle, which is the main tool in order to prove that the equilibrium fluctuations of the WASEP are given, in the regime of the critical strength asymmetry, by the…

Probability · Mathematics 2014-08-05 Patrícia Gonçalves

This article is devoted to the numerical study of various finite difference approximations to the stochastic Burgers equation. Of particular interest in the one-dimensional case is the situation where the driving noise is white both in…

Probability · Mathematics 2013-09-20 Martin Hairer , Jochen Voss

In this article, we establish the Freidlin-Wentzell type large deviation principle and central limit theorem for stochastic fractional conservation laws with small multiplicative noise in kinetic formulation framework. The weak convergence…

Probability · Mathematics 2023-06-08 Soumya Ranjan Behera , Ananta K. Majee

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

The term "moderate deviations" is often used in the literature to mean a class of large deviation principles that, in some sense, fill the gap between a convergence in probability to zero (governed by a large deviation principle) and a weak…

Probability · Mathematics 2022-02-01 Luisa Beghin , Claudio Macci

This work is about the existence of martingale solutions and weak solutions for a stochastic nonlocal Burgers equation on bounded intervals. The existence of a martingale solution is shown by using a Galerkin approximation, Prokhorov's…

Probability · Mathematics 2014-10-29 Guangying Lv , Jinqiao Duan

We consider weakly asymmetric exclusion processes whose initial density profile is a small perturbation of a constant. We show that in the diffusive time-scale, in all dimensions, the density defect evolves as the solution of a viscous…

Probability · Mathematics 2020-06-05 M. Jara , C. Landim , K. Tsunoda

Large deviation principle by the weak convergence approach is established for the stochastic nonlinear Schrodinger equation in one-dimension and as an application the exit problem is investigated.

Analysis of PDEs · Mathematics 2019-11-04 Parisa Fatheddin , Zhaoyang Qiu

We study the small noise asymptotic for stochastic Burgers equations on $(0,1)$ with Dirichlet boundary condition. We consider the case that the noise is more singular than space-time white noise. We let the noise magnitude $\sqrt{\epsilon}…

Probability · Mathematics 2024-12-02 Rui Bai , Chunrong Feng , Huaizhong Zhao

This work concerns about stochastic Burgers type equations with reflection. First of all, by means of the equicontinuous uniform Laplace principle, we prove the Freidlin-Wentzell uniform large deviation principle for these equations…

Probability · Mathematics 2025-06-19 Huijie Qiao

Moderate deviation principles for empirical measure processes associated with weakly interacting Markov processes are established. Two families of models are considered: the first corresponds to a system of interacting diffusions whereas…

Probability · Mathematics 2015-10-09 Amarjit Budhiraja , Ruoyu Wu

The convergence of stochastic interacting particle systems in the mean-field limit to solutions of conservative stochastic partial differential equations is established, with optimal rate of convergence. As a second main result, a…

Probability · Mathematics 2022-12-15 Benjamin Gess , Rishabh S. Gvalani , Vitalii Konarovskyi

We prove large and moderate deviation principles for the distribution of an empirical mean conditioned by the value of the sum of discrete i.i.d. random variables. Some applications for combinatoric problems are discussed.

Probability · Mathematics 2007-07-11 Fabrice Gamboa , Thierry Klein , Clémentine Prieur

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 note provides a tool to infer moderate deviations principles for specific random variables from deviations principles for their Hubbard-Stratonovich transforms.

Probability · Mathematics 2012-10-03 Matthias Löwe , Raphael Meiners

In order to characterize the fluctuation between the ergodic limit and the time-averaging estimator of a full discretization in a quantitative way, we establish a central limit theorem for the full discretization of the parabolic stochastic…

Probability · Mathematics 2022-02-21 Chuchu Chen , Tonghe Dang , Jialin Hong , Tau Zhou

We study the asymptotic behavior of stochastic hyperbolic parabolic equations with slow and fast time scales. Both the strong and weak convergence in the averaging principe are established, which can be viewed as a functional law of large…

Probability · Mathematics 2020-11-12 Michael Röckner , Longjie Xie , Li Yang

We characterize the convergence in distribution to a standard normal law for a sequence of multiple stochastic integrals of a fixed order with variance converging to 1. Some applications are given, in particular to study the limiting…

Probability · Mathematics 2007-05-23 David Nualart , Giovanni Peccati