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We discretize the stochastic Allen-Cahn equation with additive noise by means of a spectral Galerkin method in space and a tamed version of the exponential Euler method in time. The resulting error bounds are analyzed for the…

Numerical Analysis · Mathematics 2021-01-20 Meng Cai , Siqing Gan , Xiaojie Wang

We present an abstract framework to study weak convergence of numerical approximations of linear stochastic partial differential equations driven by additive L\'evy noise. We first derive a representation formula for the error which we then…

Probability · Mathematics 2016-02-25 Mihály Kovács , Felix Lindner , René L. Schilling

We study the error of the Euler scheme applied to a stochastic partial differential equation. We prove that as it is often the case, the weak order of convergence is twice the strong order. A key ingredient in our proof is Malliavin…

Numerical Analysis · Mathematics 2008-12-18 Arnaud Debussche

We consider the numerical approximation of the mild solution to a semilinear stochastic wave equation driven by additive noise. For the spatial approximation we consider a standard finite element method and for the temporal approximation, a…

Numerical Analysis · Mathematics 2023-12-06 Mihály Kovács , Annika Lang , Andreas Petersson

We prove a weak rate of convergence of a fully discrete scheme for stochastic Cahn--Hilliard equation with additive noise, where the spectral Galerkin method is used in space and the backward Euler method is used in time. Compared with the…

Numerical Analysis · Mathematics 2023-03-21 Meng Cai , Siqing Gan , Yaozhong Hu

In this paper we are interested in the numerical approximation of the marginal distributions of the Hilbert space valued solution of a stochastic Volterra equation driven by an additive Gaussian noise. This equation can be written in the…

Probability · Mathematics 2014-11-07 Mihály Kovács , Jacques Printems

We consider a finite element approximation of a general semi-linear stochastic partial differential equation (SPDE) driven by space-time multiplicative and additive noise. We examine the full weak convergence rate of the exponential Euler…

Numerical Analysis · Mathematics 2015-07-28 Antoine Tambue , Jean Medard T. Ngnotchouye

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 present an abstract framework for analyzing the weak error of fully discrete approximation schemes for linear evolution equations driven by additive Gaussian noise. First, an abstract representation formula is derived for sufficiently…

Numerical Analysis · Mathematics 2013-07-17 M. Kovács , S. Larsson , F. Lindgren

A standard finite element method discretizes the stochastic linear Schr\"{o}dinger equation driven by additive noise in the spatial variables. The weak convergence of the resulting approximate solution is analyzed, and it is established…

Probability · Mathematics 2025-03-18 Mangala Prasad

We find the weak rate of convergence of the spatially semidiscrete finite element approximation of the nonlinear stochastic heat equation. Both multiplicative and additive noise is considered under different assumptions. This extends an…

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

We study a class of fully-discrete schemes for the numerical approximation of solutions of stochastic Cahn--Hilliard equations with cubic nonlinearity and driven by additive noise. The spatial (resp. temporal) discretization is performed…

Numerical Analysis · Mathematics 2022-07-20 Charles-Edouard Bréhier , Jianbo Cui , Xiaojie Wang

The numerical approximation of the solution to a stochastic partial differential equation with additive spatial white noise on a bounded domain is considered. The differential operator is assumed to be a fractional power of an integer order…

Numerical Analysis · Mathematics 2018-12-12 David Bolin , Kristin Kirchner , Mihály Kovács

Stochastic wave equations appear in several models for evolutionary processes subject to random forces, such as the motion of a strand of DNA in a liquid or heat flow around a ring. Semilinear stochastic wave equations can typically not be…

Probability · Mathematics 2021-11-09 Ladislas Jacobe de Naurois , Arnulf Jentzen , Timo Welti

We introduce a new family of refined Sobolev-Malliavin spaces that capture the integrability in time of the Malliavin derivative. We consider duality in these spaces and derive a Burkholder type inequality in a dual norm. The theory we…

Probability · Mathematics 2016-02-23 Adam Andersson , Raphael Kruse , Stig Larsson

We investigate the weak order of convergence for space-time discrete approximations of semilinear parabolic stochastic evolution equations driven by additive square-integrable L\'evy noise. To this end, the Malliavin regularity of the…

Probability · Mathematics 2018-08-28 Adam Andersson , Felix Lindner

Motivated by fractional derivative models in viscoelasticity, a class of semilinear stochastic Volterra integro-differential equations, and their deterministic counterparts, are considered. A generalized exponential Euler method, named here…

Numerical Analysis · Mathematics 2020-01-17 Mihály Kovács , Stig Larsson , Fardin Saedpanah

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

This work is devoted to convergence analysis of an exponential integrator scheme for semi-discretization in time of nonlinear stochastic wave equation. A unified framework is first set forth, which covers important cases of additive and…

Numerical Analysis · Mathematics 2020-08-10 Xiaojie Wang

We establish weak convergence rates for spectral Galerkin approximations of the stochastic viscous Burgers equation driven by additive trace-class noise. Our results complement the known results regarding strong convergence; we obtain…

Probability · Mathematics 2024-12-25 Charles-Edouard Bréhier , Sonja Cox , Annie Millet
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