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We consider stochastic partial differential equations (SPDEs) on the one-dimensional torus, driven by space-time white noise, and with a time-periodic drift term, which vanishes on two stable and one unstable equilibrium branches. Each of…

Probability · Mathematics 2024-02-27 Nils Berglund , Rita Nader

This article is devoted to the analysis of the weak rates of convergence of schemes introduced by the authors in a recent work, for the temporal discretization of the stochastic Allen-Cahn equation driven by space-time white noise. The…

Numerical Analysis · Mathematics 2018-04-19 Charles-Edouard Bréhier , Ludovic Goudenège

In this work we are concerned with the study of the strong order of convergence in the averaging principle for slow-fast systems of stochastic evolution equations in Hilbert spaces with additive noise. In particular the stochastic…

Probability · Mathematics 2023-06-07 Filippo de Feo

In this paper we deal with pointwise approximation of solutions of stochastic differential equations (SDEs) driven by infinite dimensional Wiener process with additional jumps generated by Poisson random measure. The further investigations…

Probability · Mathematics 2022-05-04 Paweł Przybyłowicz , Michał Sobieraj , Łukasz Stȩpień

For semilinear stochastic evolution equations whose coefficients are more general than the classical global Lipschitz, we present results on the strong convergence rates of numerical discretizations. The proof of them provides a new…

Numerical Analysis · Mathematics 2019-06-11 Jialin Hong , Chuying Huang , Zhihui Liu

In this paper, we consider a system of $k$ second order non-linear stochastic partial differential equations with spatial dimension $d \geq 1$, driven by a $q$-dimensional Gaussian noise, which is white in time and with some spatially…

Probability · Mathematics 2011-02-17 Eulalia Nualart

We study the approximation of SPDEs on the whole real line near a change of stability via modulation or amplitude equations, which acts as a replacement for the lack of random invariant manifolds on extended domains. Due to the…

Probability · Mathematics 2017-11-20 Luigi Amedeo Bianchi , Dirk Blömker

The ODE method has been a workhorse for algorithm design and analysis since the introduction of the stochastic approximation. It is now understood that convergence theory amounts to establishing robustness of Euler approximations for ODEs,…

Optimization and Control · Mathematics 2020-10-02 Shuhang Chen , Adithya Devraj , Andrey Bernstein , Sean Meyn

In this article, we have analyzed semi-discrete finite element approximations of the Stochastic linear Schr\"{o}dinger equation in a bounded convex polygonal domain driven by additive Wiener noise. We use the finite element method for…

Numerical Analysis · Mathematics 2026-01-16 Suprio Bhar , Mrinmay Biswas , Mangala Prasad

We consider the approximation via modulation equations for nonlinear SPDEs on unbounded domains with additive space time white noise. Close to a bifurcation an infinite band of eigenvalues changes stability, and we study the impact of small…

Probability · Mathematics 2019-10-30 Luigi Amedeo Bianchi , Dirk Blömker , Guido Schneider

We deal with parameter estimation for a linear parabolic second-order stochastic partial differential equation in two space dimensions driven by two types of $Q$-Wiener processes based on high frequency data with respect to time and space.…

Statistics Theory · Mathematics 2023-04-20 Yozo Tonaki , Yusuke Kaino , Masayuki Uchida

We extend the taming techniques for explicit Euler approximations of stochastic differential equations (SDEs) driven by L\'evy noise with super-linearly growing drift coefficients. Strong convergence results are presented for the case of…

Probability · Mathematics 2015-01-23 Konstantinos Dareiotis , Chaman Kumar , Sotirios Sabanis

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

Strong convergence rates for numerical approximations of semilinear stochastic partial differential equations (SPDEs) with smooth and regular nonlinearities are well understood in the literature. Weak convergence rates for numerical…

Probability · Mathematics 2016-12-13 Mario Hefter , Arnulf Jentzen , Ryan Kurniawan

We introduce a time-integrator to sample with high order of accuracy the invariant distribution for a class of semilinear SPDEs driven by an additive space-time noise. Combined with a postprocessor, the new method is a modification with…

Numerical Analysis · Mathematics 2016-08-18 Charles-Edouard Bréhier , Gilles Vilmart

We study the bi-parameter local linearization of the one-dimensional nonlinear stochastic wave equation driven by a Gaussian noise, which is white in time and has a spatially homogeneous covariance structure of Riesz-kernel type. We…

Probability · Mathematics 2025-10-03 Guoping Liu , Ran Wang

We establish an optimal strong convergence rate of a fully discrete numerical scheme for second order parabolic stochastic partial differential equations with monotone drifts, including the stochastic Allen-Cahn equation, driven by an…

Numerical Analysis · Mathematics 2020-05-21 Zhihui Liu , Zhonghua Qiao

This article investigates time-discrete approximations of Allen-Cahn type SPDEs driven by space-time white noise near the sharp interface limit $\epsilon\to 0$, where the small parameter $\epsilon$ is the diffuse interface thickness. We…

Numerical Analysis · Mathematics 2026-01-06 Yingsong Jiang , Chenxu Pang , Xiaojie Wang

We propose a modification of the standard linear implicit Euler integrator for the weak approximation of parabolic semilinear stochastic PDEs driven by additive space-time white noise. The new method can easily be combined with a finite…

Numerical Analysis · Mathematics 2022-03-22 Charles-Edouard Bréhier

We consider the numerical approximation of general semilinear parabolic stochastic partial differential equations (SPDEs) driven by additive space-time noise. In contrast to the standard time stepping methods which uses basic increments of…

Numerical Analysis · Mathematics 2010-05-31 Gabriel J. Lord , Antoine Tambue