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We present high-order numerical schemes for linear stochastic heat and wave equations with Dirichlet boundary conditions, driven by additive noise. Standard Euler schemes for SPDEs are limited to an order convergence between 1/2 and 1 due…

Numerical Analysis · Mathematics 2025-10-28 Abhishek Chaudhary , Andreas Prohl

By employing a suitable multiplicative It\^o noise with radial structure and with more than linear growth, we show the existence of a unique, global-in-time, strong solution for the stochastic Euler equations in two and three dimensions.…

Probability · Mathematics 2025-05-30 Marco Bagnara , Mario Maurelli , Fanhui Xu

This paper focuses on explicit approximations for nonlinear stochastic delay differential equations (SDDEs). Under the weakly local Lipschitz and some suitable conditions, a generic truncated Euler-Maruyama (TEM) scheme for SDDEs is…

Numerical Analysis · Mathematics 2020-08-20 Guoting Song , Junhao Hu , Shuaibin Gao , Xiaoyue Li

In order to approximate solutions of stochastic partial differential equations (SPDEs) that do not possess commutative noise, one has to simulate the involved iterated stochastic integrals. Recently, two approximation methods for iterated…

Probability · Mathematics 2019-10-09 Claudine von Hallern , Andreas Rößler

We consider strong approximations of $1+1$-dimensional stochastic PDEs driven by additive space-time white noise. It has been long proposed (Davie-Gaines '01, Jentzen-Kloeden '08), as well as observed in simulations, that approximation…

Probability · Mathematics 2026-04-17 Ana Djurdjevac , Máté Gerencsér , Helena Kremp

We discuss a system of stochastic differential equations with a stiff linear term and additive noise driven by fractional Brownian motions (fBms) with Hurst parameter H>1/2, which arise e. g., from spatial approximations of stochastic…

Probability · Mathematics 2024-05-10 Minoo Kamrani , Kristian Debrabant , Nahid Jamshidi

We obtain estimates on the first-order Malliavin derivative of mild solutions, evaluated at fixed points in time and space, to a class of parabolic dissipative stochastic PDEs on bounded domain of $\mathbb{R}^d$. In particular, such…

Probability · Mathematics 2022-01-04 Carlo Marinelli

This paper is concerned with the strong approximation of a semi-linear stochastic wave equation with strong damping, driven by additive noise. Based on a spatial discretization performed by a spectral Galerkin method, we introduce a kind of…

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

In the present work, we investigate the dynamics of the infinite-dimensional stochastic partial differential equation (SPDE) with multiplicative white noise. We derive the effective equation on the approximate slow manifold in detail by…

Dynamical Systems · Mathematics 2025-05-08 Shenglan Yuan , Dirk Blömker

We study the traditional backward Euler method for $m$-dimensional stochastic differential equations driven by fractional Brownian motion with Hurst parameter $H > 1/2$ whose drift coefficient satisfies the one-sided Lipschitz condition.…

Numerical Analysis · Mathematics 2022-05-30 Hao Zhou , Yaozhong Hu , Yanghui Liu

We consider the strong numerical approximation for a fourth-order stochastic nonlinear SPDE driven by space-time white noise on $2$-dimensional torus. We consider its full discretisation with a spectral Galerkin scheme in space and Euler…

Numerical Analysis · Mathematics 2025-10-14 Dirk Blömker , Chengcheng Ling , Johannes Rimmele

In this work we consider solutions to stochastic partial differential equations with transport noise, which are known to converge, in a suitable scaling limit, to solution of the corresponding deterministic PDE with an additional viscosity…

Probability · Mathematics 2023-05-04 Lucio Galeati , Dejun Luo

This paper is concerned with the adaptive numerical treatment of stochastic partial differential equations. Our method of choice is Rothe's method. We use the implicit Euler scheme for the time discretization. Consequently, in each step, an…

A class of Hamiltonian stochastic differential equations with multiplicative L\'{e}vy noise in the sense of Marcus, and the construction and numerical implementation methods of symplectic Euler scheme, are considered. A general symplectic…

Numerical Analysis · Mathematics 2020-10-16 Qingyi Zhan , Jinqiao Duan , Xiaofan Li , Yuhong Li

The strong numerical approximation of semilinear stochastic partial differential equations (SPDEs) driven by infinite dimensional Wiener processes is investigated. There are a number of results in the literature that show that Euler-type…

Numerical Analysis · Mathematics 2021-11-02 Sebastian Becker , Arnulf Jentzen , Peter E. Kloeden

The convergence of the first order Euler scheme and an approximative variant thereof, along with convergence rates, are established for rough differential equations driven by c\`adl\`ag paths satisfying a suitable criterion, namely the…

Probability · Mathematics 2025-09-16 Andrew L. Allan , Anna P. Kwossek , Chong Liu , David J. Prömel

We prove a maximum principle for local solutions of quasi-linear parabolic stochastic PDEs, with non-homogeneous second order operator on a bounded domain and driven by a space-time white noise. Our method based on an approximation of the…

Probability · Mathematics 2012-09-03 Laurent Denis , Anis Matoussi

We present and study an explicit exponential integrator for parabolic SPDEs in any dimension driven by a Gaussian noise which is white in time and with spatial correlation given by a Riesz kernel. Under assumptions on the coefficients of…

Numerical Analysis · Mathematics 2026-02-20 Charles-Edouard Bréhier , David Cohen , Lluís Quer-Sardanyons , Johan Ulander

In this paper, we study the numerical approximation of a general second order semilinear stochastic partial differential equation (SPDE) driven by a additive fractional Brownian motion (fBm) with Hurst parameter $H>\frac 12$ and Poisson…

Numerical Analysis · Mathematics 2020-01-01 Aurelien Junior Noupelah , Antoine Tambue

In this paper, we present new types of exponential integrators for Stochastic Differential Equations (SDEs) that take the advantage of the exact solution of (generalised) geometric Brownian motion. We examine both Euler and Milstein…

Numerical Analysis · Mathematics 2016-09-29 Utku Erdoğan , Gabriel J. Lord