Convergence of the spectral Galerkin method for the stochastic reaction-diffusion-advection equation

被引:5
作者
Yang, Li [1 ]
Zhang, Yanzhi [2 ]
机构
[1] Inria Sophia Antipolis, EPI NeuroMathComp, F-06902 Sophia Antipolis, France
[2] Missouri Univ Sci & Technol, Dept Math & Stat, Rolla, MO 65409 USA
关键词
Stochastic; reaction-diffusion-advection equation; Galerkin approximation; Convergence rate; Allen-Cahn equation; Burgers' equation; PARTIAL-DIFFERENTIAL-EQUATIONS;
D O I
10.1016/j.jmaa.2016.09.028
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We study the convergence of the spectral Galerkin method in solving the stochastic reaction diffusion advection equation under different Lipschitz conditions of the reaction function f. When f is globally (locally) Lipschitz continuous, we prove that the spectral Galerkin approximation strongly (weakly) converges to the mild solution of the stochastic reaction diffusion advection equation, and the rate of convergence in H-r-normis (1/2 - r)(-), for any r is an element of [0, 1/2) (r is an element of (1/2 - 1/2d, 1/2). The convergence analysis in the local Lipschitz case is challenging, especially in the presence of an advection term. We propose a new approach based on the truncation techniques, which can be easily applied to study other stochastic partial differential equations. Numerical simulations are also provided to study the convergence of Galerkin approximations. (C) 2016 Elsevier Inc. All rights reserved.
引用
收藏
页码:1230 / 1254
页数:25
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