Stability and convergence analysis of a fully discrete semi-implicit scheme for stochastic Allen-Cahn equations with multiplicative noise

IF 2.2 2区 数学 Q1 MATHEMATICS, APPLIED
Can Huang, Jie Shen
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引用次数: 0

Abstract

We consider a fully discrete scheme for stochastic Allen-Cahn equation in a multi-dimensional setting. Our method uses a polynomial based spectral method in space, so it does not require the elliptic operator A A and the covariance operator Q Q of noise in the equation commute, and thus successfully alleviates a restriction of Fourier spectral method for stochastic partial differential equations pointed out by Jentzen, Kloeden and Winkel [Ann. Appl. Probab. 21 (2011), pp. 908–950]. The discretization in time is a tamed semi-implicit scheme which treats the nonlinear term explicitly while being unconditionally stable. Under regular assumptions which are usually made for SPDEs, we establish strong convergence rates in the one spatial dimension for our fully discrete scheme. We also present numerical experiments which are consistent with our theoretical results.
含乘性噪声的随机Allen-Cahn方程的完全离散半隐式格式的稳定性和收敛性分析
我们考虑多维环境下随机Allen-Cahn方程的一个完全离散格式。我们的方法在空间中使用了基于多项式的谱方法,因此在方程通勤中不需要噪声的椭圆算子a和协方差算子Q Q,从而成功地缓解了Jentzen、Kloeden和Winkel[Ann.Appl.Probab.21(2011),pp.908–950]指出的随机偏微分方程的傅立叶谱方法的限制。时间离散化是一种驯服的半隐式格式,它在无条件稳定的同时显式处理非线性项。在通常对SPDE进行的规则假设下,我们在一个空间维度上为我们的完全离散方案建立了强收敛率。我们还介绍了与理论结果一致的数值实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Mathematics of Computation
Mathematics of Computation 数学-应用数学
CiteScore
3.90
自引率
5.00%
发文量
55
审稿时长
7.0 months
期刊介绍: All articles submitted to this journal are peer-reviewed. The AMS has a single blind peer-review process in which the reviewers know who the authors of the manuscript are, but the authors do not have access to the information on who the peer reviewers are. This journal is devoted to research articles of the highest quality in computational mathematics. Areas covered include numerical analysis, computational discrete mathematics, including number theory, algebra and combinatorics, and related fields such as stochastic numerical methods. Articles must be of significant computational interest and contain original and substantial mathematical analysis or development of computational methodology.
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