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One- and multi-dimensional stochastic Maxwell equations with additive noise are considered in this paper. It is known that such system can be written in the multi-symplectic structure, and the stochastic energy increases linearly in time.…

Numerical Analysis · Mathematics 2022-05-04 Jiawei Sun , Chi-Wang Shu , Yulong Xing

In the pathwise stochastic calculus framework, the paper deals with the general study of equations driven by an additive Gaussian noise, with a drift function having an infinite limit at point zero. An ergodic theorem and the convergence of…

Probability · Mathematics 2019-01-16 Nicolas Marie

This paper proposes a fully discrete method called the symplectic dG full discretization for stochastic Maxwell equations driven by additive noises, based on a stochastic symplectic method in time and a discontinuous Galerkin (dG) method…

Numerical Analysis · Mathematics 2020-09-22 Chuchu Chen

In this article we present a way of treating stochastic partial differential equations with multiplicative noise by rewriting them as stochastically perturbed evolutionary equations in the sense of \cite{picardbook}, where a general…

Probability · Mathematics 2016-11-08 André Süß , Marcus Waurick

We study the stochastic nonlinear Schr\"odinger equations with additive stochastic forcing. By using the dispersive estimate, we present a simple argument, constructing a unique local-in-time solution with rougher stochastic forcing than…

Analysis of PDEs · Mathematics 2020-12-23 Tadahiro Oh , Oana Pocovnicu , Yuzhao Wang

In this paper, we present an energy-preserving exponentially integrable numerical method for stochastic wave equation with cubic nonlinearity and additive noise. We first apply the spectral Galerkin method to discretizing the original…

Numerical Analysis · Mathematics 2021-04-14 Jianbo Cui , Jialin Hong , Lihai Ji , Liying Sun

The paper concerns semidiscretizations in time of stochastic Maxwell equations driven by additive noise. We show that the equations admit physical properties and mathematical structures, including regularity, energy and divergence evolution…

Numerical Analysis · Mathematics 2018-06-07 Chuchu Chen , Jialin Hong , Lihai Ji

In this paper, we study a class of slow-fast stochastic partial differential equations with multiplicative Wiener noise. Under some appropriate conditions, we prove the slow component converges to the solution of the corresponding averaged…

Probability · Mathematics 2021-05-31 Yi Ge , Xiaobin Sun , Yingchao Xie

We propose two new classes of time integrators for stiff DEs: the implicit-explicit exponential (IMEXP) and the hybrid exponential methods. In contrast to the existing exponential schemes, the new methods offer significant computational…

Numerical Analysis · Mathematics 2016-05-11 Vu Thai Luan , Mayya Tokman , Greg Rainwater

In this paper, we consider the strong convergence order of the exponential integrator for the stochastic heat equation driven by an additive fractional Brownian motion with Hurst parameter $H\in(\frac12,1)$. By showing the strong order one…

Numerical Analysis · Mathematics 2020-07-07 Jialin Hong , Chuying Huang

We study the convergence of a Zakharov system driven by a time white noise, colored in space, to a multiplicative stochastic nonlinear Schr{\"o}dinger equation, as the ion-sound speed tends to infinity. In the absence of noise, the…

Analysis of PDEs · Mathematics 2024-09-24 Grégoire Barrué , Anne de Bouard , Arnaud Debussche

This paper is concerned with developing and analyzing two novel implicit temporal discretization methods for the stochastic semilinear wave equations with multiplicative noise. The proposed methods are natural extensions of well-known…

Numerical Analysis · Mathematics 2024-08-26 Xiaobing Feng , Yukun Li , Liet Vo

A numerical analysis for the fully discrete approximation of an operator Lyapunov equation related to linear SPDEs (stochastic partial differential equations) driven by multiplicative noise is considered. The discretization of the Lyapunov…

Numerical Analysis · Mathematics 2022-05-04 Adam Andersson , Annika Lang , Andreas Petersson , Leander Schroer

In the present paper, the effect of noise intensity on stochastic parabolic equations is discussed. We focus on the effect of noise on the energy solutions of the stochastic parabolic equations. By utilising It\^o's formula and the energy…

Probability · Mathematics 2018-02-14 Guangying Lv , Hongjun Gao , Jinlong Wei , Jiang-lun Wu

In this paper, we investigate a numerical approximation of a general second order semilinear parabolic non-autonomous stochastic partial differential equation (SPDE) driven by additive noise. Numerical approximations for autonomous SPDEs…

Numerical Analysis · Mathematics 2018-09-18 Jean Daniel Mukam , Antoine Tambue

We prove a weak error estimate for the approximation in space and time of a semilinear stochastic Volterra integro-differential equation driven by additive space-time Gaussian noise. We treat this equation in an abstract framework, in which…

Numerical Analysis · Mathematics 2016-03-15 Adam Andersson , Mihály Kovács , Stig Larsson

Stochastic approximation is a powerful class of algorithms with celebrated success. However, a large body of previous analysis focuses on stochastic approximations driven by contractive operators, which is not applicable in some important…

Machine Learning · Computer Science 2025-11-21 Ethan Blaser , Shangtong Zhang

We consider the stochastic nonlinear Schroedinger equation driven by a multiplicative noise in a semiclassical regime, where the Plank constant is small. In this regime, the solution of the equation exhibits high-frequency oscillations. We…

Numerical Analysis · Mathematics 2024-08-20 Lihai Ji , Zhihui Liu

This paper is concerned with exponentially ill-posed operator equations with additive impulsive noise on the right hand side, i.e. the noise is large on a small part of the domain and small or zero outside. It is well known that Tikhonov…

Numerical Analysis · Mathematics 2016-03-18 Claudia König , Frank Werner , Thorsten Hohage

Exponential integrators have been introduced as an efficient alternative to explicit and implicit methods for integrating large stiff systems of differential equations. Over the past decades these methods have been studied theoretically and…

Numerical Analysis · Mathematics 2018-04-03 Lukas Einkemmer , Mayya Tokman , John Loffeld