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We present a way to use Stein's method in order to bound the Wasserstein distance of order $2$ between two measures $\nu$ and $\mu$ supported on $\mathbb{R}^d$ such that $\mu$ is the reversible measure of a diffusion process. In order to…

Probability · Mathematics 2018-06-25 Thomas Bonis

We develop several results on hitting probabilities of random fields which highlight the role of the dimension of the parameter space. This yields upper and lower bounds in terms of Hausdorff measure and Bessel--Riesz capacity,…

Probability · Mathematics 2010-11-30 Robert C. Dalang , Marta Sanz-Solé

In this paper, we establish a central limit theorem (CLT) and the moderate deviation principles (MDP) for a class of semilinear stochastic partial differential equations driven by multiplicative noise on a bounded domain. The main results…

Probability · Mathematics 2019-04-02 Rangrang Zhang , Jie Xiong

We give a new proof of the classical Central Limit Theorem, in the Mallows ($L^r$-Wasserstein) distance. Our proof is elementary in the sense that it does not require complex analysis, but rather makes use of a simple subadditive inequality…

Probability · Mathematics 2007-06-13 Oliver Johnson , Richard Samworth

The semilinear stochastic wave equation on the sphere driven by multiplicative Gaussian noise is discretized by a stochastic trigonometric integrator in time and a spectral Galerkin approximation in space based on the spherical harmonic…

Numerical Analysis · Mathematics 2026-02-03 David Cohen , Stefano Di Giovacchino , Annika Lang

An efficient algorithm to simulate dynamics of open quantum system is presented. The method describes the dynamics by unraveling stochastic wave functions converging to a density operator description. The stochastic techniques are based on…

Quantum Physics · Physics 2022-09-21 Ronnie Kosloff Uriel Shafir

We review and present some known results for non-linear functionals of Gaussian variables in the context of discrete Gaussian fields defined on the $d$ dimensional lattice. Our main result is a Central Limit Theorem in the spirit of the…

Probability · Mathematics 2025-12-16 Fabio Coppini , Wioletta M. Ruszel

In this work, we study the normal approximation and almost sure central limit theorems for some functionals of an independent sequence of Rademacher random variables. In particular, we provide a new chain rule that improves the one derived…

Probability · Mathematics 2018-10-16 Guangqu Zheng

We prove a priori bounds for solutions of stochastic reaction diffusion equations with super-linear damping in the reaction term. These bounds provide a control on the supremum of solutions on any compact space-time set which only depends…

Analysis of PDEs · Mathematics 2018-09-24 Augustin Moinat , Hendrik Weber

In this paper, we consider a semi-linear stochastic strongly damped wave equation driven by additive Gaussian noise. Following a semigroup framework, we establish existence, uniqueness and space-time regularity of a mild solution to such…

Numerical Analysis · Mathematics 2020-08-10 Ruisheng Qi , Xiaojie Wang

We study the long-range one-dimensional Riesz gas on the circle, a continuous system of particles interacting through a Riesz kernel. We establish near-optimal rigidity estimates on gaps valid at any scale. Leveraging these local laws…

Probability · Mathematics 2025-07-22 Jeanne Boursier

In this study we consider limit theorems for microscopic stochastic models of neural fields. We show that the Wilson-Cowan equation can be obtained as the limit in probability on compacts for a sequence of microscopic models when the number…

Probability · Mathematics 2012-06-28 Evelyn Buckwar , Martin G. Riedler

Let $X_1,\dots,X_n$ be i.i.d. log-concave random vectors in $\mathbb R^d$ with mean 0 and covariance matrix $\Sigma$. We study the problem of quantifying the normal approximation error for $W=n^{-1/2}\sum_{i=1}^nX_i$ with explicit…

Probability · Mathematics 2023-05-30 Xiao Fang , Yuta Koike

We obtain explicit error bounds for the $d$-dimensional normal approximation on hyperrectangles for a random vector that has a Stein kernel, or admits an exchangeable pair coupling, or is a non-linear statistic of independent random…

Probability · Mathematics 2020-09-08 Xiao Fang , Yuta Koike

We prove a characterization of the support of the law of the solution for a stochastic wave equation with two-dimensional space variable, driven by a noise white in time and correlated in space. The result is a consequence of an…

Probability · Mathematics 2016-09-07 Annie Millet , Marta Sanz-Solé

In this paper, we study the asymptotic behavior of a fully-coupled slow-fast McKean-Vlasov stochastic system. Using the non-linear Poisson equation on Wasserstein space, we first establish the strong convergence in the averaging principle…

Probability · Mathematics 2022-07-14 Yun Li , Longjie Xie

The central object in the theory of semiclassical stochastic gravity is the noise kernel which is the symmetric two point correlation function of the stress-energy tensor. Using the corresponding Wightman functions in Minkowski, Einstein…

High Energy Physics - Theory · Physics 2016-03-23 H. T. Cho , B. L. Hu

In this paper, we extend Walsh's stochastic integral with respect to a Gaussian noise, white in time and with some homogeneous spatial correlation, in order to be able to integrate some random measure-valued processes. This extension turns…

Probability · Mathematics 2007-05-23 David Nualart , Lluis Quer-Sardanyons

Motivated by the central limit problem for convex bodies, we study normal approximation of linear functionals of high-dimensional random vectors with various types of symmetries. In particular, we obtain results for distributions which are…

Probability · Mathematics 2016-09-07 Elizabeth S. Meckes , Mark W. Meckes

In this paper, we consider the one-dimensional stochastic heat equation driven by a space time white noise. In two different scenarios: {\it (i)} initial condition $u_0=1$ and general nonlinear coefficient $\sigma$ and {\it (ii)}: initial…

Probability · Mathematics 2021-08-24 Sefika Kuzgun , David Nualart