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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

This paper considers a class of nonautonomous slow-fast stochastic partial differential equations driven by $\alpha$-stable processes for $\alpha\in (1,2)$. By introducing the evolution system of measures, we establish an averaging…

Probability · Mathematics 2025-07-11 Yueling Li , Xiaobin Sun , Zijuan Wang , Yingchao Xie

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 establish an averaging principle for a structural multiscale stochastic nonlinear fractional Schr\"odinger system on the one-dimensional torus driven by a multiplicative Wiener noise. The slow component is governed by a fractional…

Analysis of PDEs · Mathematics 2026-05-13 Manil T. Mohan , Debopriya Mukherjee , Sandip Roy

We prove strong rate resp. weak rate ${\mathcal O}(\tau)$ for a structure preserving temporal discretization (with $\tau$ the step size) of the stochastic Allen-Cahn equation with additive resp. multiplicative colored noise in $d=1,2,3$…

Numerical Analysis · Mathematics 2023-09-18 Dominic Breit , Andreas Prohl

Averaging is an important method to extract effective macroscopic dynamics from complex systems with slow modes and fast modes. This article derives an averaged equation for a class of stochastic partial differential equations without any…

Analysis of PDEs · Mathematics 2009-04-10 W. Wang , A. J. Roberts

In this paper, we investigate a class of multiscale McKean-Vlasov stochastic systems, where the entire system depends on the distributions of both fast and slow components. First of all, by applying the Poisson equation method, we prove…

Probability · Mathematics 2025-09-30 Jie Xiang , Huijie Qiao

By using the technique of the Zvonkin's transformation and the classical Khasminkii's time discretization method, we prove the averaging principle for slow-fast stochastic partial differential equations with bounded and H\"{o}lder…

Probability · Mathematics 2020-03-10 Xiaobin Sun , Longjie Xie , Yingchao Xie

In this paper, we consider a class of nonautonomous multi-scale stochastic partial differential equations with fully local monotone coefficients. By introducing the evolution system of measures for time-inhomogeneous Markov semigroups, we…

Probability · Mathematics 2025-09-03 Mengyu Cheng , Xiaobin Sun , Yingchao Xie

In this paper, we consider asymptotic behaviors of multiscale multivalued stochastic systems with small noises. First of all, for general, fully coupled systems for multivalued stochastic differential equations of slow and fast motions with…

Probability · Mathematics 2025-09-30 Huijie Qiao

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 first establish strong convergence rates for multiscale systems driven by $\alpha$-stable processes, with analyses constructed in two distinct scaling regimes. When addressing weak convergence rates of this system, we derive four…

Probability · Mathematics 2026-03-03 Kun Yin

The purpose of this paper is to establish asymptotic behaviors of time-inhomogeneous multi-scale stochastic differential equations (SDEs). To achieve them, we analyze the evolution system of measures for time-inhomogeneous Markov…

Probability · Mathematics 2024-12-16 Xiaobin Sun , Jian Wang , Yingchao Xie

This paper is devoted to studying the averaging principle for fast-slow system of rough differential equations driven by mixed fractional Brownian rough path. The fast component is driven by Brownian motion, while the slow component is…

Probability · Mathematics 2023-03-15 Bin Pei , Yuzuru Inahama , Yong Xu

In this paper we prove the strong averaging principle for a slow-fast system of rough differential equations. The slow and the fast component of the system are driven by a rather general random rough path and Brownian rough path,…

Probability · Mathematics 2025-04-28 Yuzuru Inahama

We consider a random process as a solution of stochastic differential equations with dependence of the coefficients on small parameter $\varepsilon$ and we suppose that the drift coefficients of these equations are unbounded on the…

Probability · Mathematics 2023-12-15 Ivan H. Krykun

In this work we establish weak convergence rates for temporal discretisations of stochastic wave equations with multiplicative noise, in particular, for the hyperbolic Anderson model. For this class of stochastic partial differential…

Probability · Mathematics 2024-05-24 Sonja Cox , Arnulf Jentzen , Felix Lindner

We study the asymptotic behavior of stochastic hyperbolic parabolic equations with slow and fast time scales. Both the strong and weak convergence in the averaging principe are established, which can be viewed as a functional law of large…

Probability · Mathematics 2020-11-12 Michael Röckner , Longjie Xie , Li Yang

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 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