Work

Parareal Algorithms for Stochastic Maxwell Equations with the Damping Term Driven by Additive Noise

Year: 2025

Type: article

Abstract: In this paper, we propose the parareal algorithms for stochastic Maxwell equations with the damping term driven by additive noise. The proposed algorithms proceed as two-level temporal parallelizable integrators with the stochastic exponential integrator as the coarse $\mathscr{G}$-propagator and both the exact solution integrator and the stochastic exponential integrator as the fine $\mathscr{F}$-propagator. The mean-square convergence order of the proposed algorithms consistently increases to $k,$ regardless of whether the exact solution integrator or the stochastic exponential integrator is chosen as the fine $\mathscr{F}$-propagator. Several numerical experiments are illustrated in order to verify our theoretical findings for different choices of the iteration number $k$ and the damping coefficient $σ.$

Source: Journal of Computational Mathematics

DOI: 10.4208/jcm.2505-m2024-0262

Authors: Liying Zhang, Qi Zhang

Institution: China University of Mining and Technology - Beijing

Language: English

Topic: Numerical methods for differential equations

Subfield: Numerical Analysis

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funders: National Natural Science Foundation of China, China University of Mining and Technology, Fundamental Research Funds for the Central Universities

Awards: G5015866142, G6211540165, G8818383366, G974497401