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In this paper, we characterize the topological support in Holder norm of the law of the solution to a stochastic wave equation with three-dimensional space variable is proved. This note is a continuation of [9] and [10]. The result is a…

Probability · Mathematics 2018-07-10 Francisco J. Delgado-Vences

This paper is a continuation of (Bernoulli 20 (2014) 2169-2216) where we prove a characterization of the support in H\"older norm of the law of the solution to a stochastic wave equation with three-dimensional space variable and null…

Probability · Mathematics 2016-03-24 Francisco J. Delgado-Vences , Marta Sanz-Solé

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

We consider a stochastic wave equation in spatial dimension three, driven by a Gaussian noise, white in time and with a stationary spatial covariance. The free terms are nonlinear with Lipschitz continuous coefficients. Under suitable…

Probability · Mathematics 2010-01-29 Víctor Ortiz-López , Marta Sanz-Solé

Solutions to the stochastic wave equation on the unit sphere are approximated by spectral methods. Strong, weak, and almost sure convergence rates for the proposed numerical schemes are provided and shown to depend only on the smoothness of…

Numerical Analysis · Mathematics 2023-12-06 David Cohen , Annika Lang

We study a family of nonlinear damped wave equations indexed by a parameter $\epsilon >0$ and forced by a space-time white noise on the two dimensional torus, with polynomial and sine nonlinearities. We show that as $\epsilon \to 0$, the…

Analysis of PDEs · Mathematics 2024-10-31 Younes Zine

In this paper, we study the stochastic wave equations in the spatial dimension 3 driven by a Gaussian noise which is white in time and correlated in space. Our main concern is the sample path H\"older continuity of the solution both in time…

Probability · Mathematics 2013-09-02 Yaozhong Hu , Jingyu Huang , David Nualart

The fundamental solution of the classical approximation of a three waves kinetic equation that happens in the kinetic theory of a condensed gas of bosons near the critical temperature is obtained. It is also proved to be unique in a…

Analysis of PDEs · Mathematics 2020-07-15 Miguel Escobedo

In this paper we study approximations to 3D Navier-Stokes (NS) equation driven by space-time white noise by paracontrolled distribution proposed in [GIP13]. A solution theory for this equation has been developed recently in [ZZ14] based on…

Probability · Mathematics 2014-09-18 Rongchan Zhu , Xiangchan Zhu

A fully discrete approximation of the semi-linear stochastic wave equation driven by multiplicative noise is presented. A standard linear finite element approximation is used in space and a stochastic trigonometric method for the temporal…

Numerical Analysis · Mathematics 2015-11-26 Rikard Anton , David Cohen , Stig Larsson , Xiaojie Wang

We show that the solutions to the damped stochastic wave equation converge pathwise to the solution of a stochastic heat equation. This is called the Smoluchowski-Kramers approximation. Cerrai and Freidlin have previously demonstrated that…

Probability · Mathematics 2018-02-01 Michael Salins

We prove that the density of the law of any finite dimensional projection of solutions of the Navier--Stokes equations with noise in dimension $3$ is H\"older continuous in time with values in the natural space $L^1$. When considered with…

Probability · Mathematics 2014-09-08 Marco Romito

In this paper, we investigate the wave solutions of a stochastic rotating shallow water model. This approximate model provides an interesting simple description of the interplay between waves and random forcing ensuing either from the wind…

Fluid Dynamics · Physics 2023-05-02 Etienne Mémin , Long Li , Noé Lahaye , Gilles Tissot , Bertrand Chapron

We study the sample path regularity of the solution of a stochastic wave equation in spatial dimension $d=3$. The driving noise is white in time and with a spatially homogeneous covariance defined as a product of a Riesz kernel and a smooth…

Probability · Mathematics 2007-05-23 Robert C. Dalang , Marta Sanz-Solé

In this article, we consider the stochastic wave equation in spatial dimension $d=1$, with linear term $\sigma(u)=u$ multiplying the noise. This equation is driven by a Gaussian noise which is white in time and fractional in space with…

Probability · Mathematics 2023-07-04 Raluca M. Balan , Jingyu Huang , Xiong Wang , Panqiu Xia , Wangjun Yuan

For a sequence $\dot{L}^{\varepsilon}$ of L\'evy noises with variance $\sigma^2(\varepsilon)$, we prove the Gaussian approximation of the solution $u^{\varepsilon}$ to the stochastic wave equation driven by $\sigma^{-1}(\varepsilon)…

Probability · Mathematics 2021-06-24 Thomas Delerue

Stochastic Navier--Stokes equations in a thin three-dimensional domain are considered, driven by additive noise. The convergence of martingale solution of the stochastic Navier--Stokes equations in a thin three-dimensional domain to the…

Probability · Mathematics 2020-08-18 Zdzisław Brzeźniak , Gaurav Dhariwal , Quoc Thong Le Gia

We consider stochastic wave equations in spatial dimensions $d \geq 4$. We assume that the driving noise is given by a Gaussian noise that is white in time and has some spatial correlation. When the spatial correlation is given by the Riesz…

Probability · Mathematics 2025-01-09 Masahisa Ebina

A one-dimensional stochastic wave equation driven by a general stochastic measure is studied in this paper. The Fourier series expansion of stochastic measures is considered. It is proved that changing the integrator by the corresponding…

Probability · Mathematics 2019-02-05 Vadym Radchenko , Nelia Stefans'ka

Stochastic approximation is a class of algorithms that update a vector iteratively, incrementally, and stochastically, including, e.g., stochastic gradient descent and temporal difference learning. One fundamental challenge in analyzing a…

Machine Learning · Computer Science 2025-11-06 Shuze Daniel Liu , Shuhang Chen , Shangtong Zhang
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