随机 Landau-Lifshitz-Bloch 方程的数值方法和误差估计

IF 2.3 2区 数学 Q1 MATHEMATICS, APPLIED
Beniamin Goldys, Chunxi Jiao, Kim-Ngan Le
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引用次数: 0

摘要

本文研究了求解在 ${mathbb{R}}^{d}$d=1,2$ 条件下 ${mathbb{R}}^{d}$ 有界域上的准线性随机偏微分方程系(即随机 Landau-Lifshitz-Bloch (LLB) 方程)的数值方法。我们的主要结果是有限元法对随机 LLB 解的收敛速率的估计。为了克服解在 $d=2$ 情况下缺乏正则性的问题,我们为方程的正则化版本提出了有限元方案。然后,我们获得了数值解和正则化方程解的误差估计,以及该解向随机 LLB 方程解的收敛速度。因此,我们得出了近似解对随机 LLB 方程解的收敛概率。由于 LLB 方程的新正则性结果使我们可以避免正则化,因此在 $d=1$ 的情况下会得到更强的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Numerical method and error estimate for stochastic Landau–Lifshitz–Bloch equation
In this paper we study numerical methods for solving a system of quasilinear stochastic partial differential equations known as the stochastic Landau–Lifshitz–Bloch (LLB) equation on a bounded domain in ${\mathbb{R}}^{d}$ for $d=1,2$. Our main results are estimates of the rate of convergence of the Finite Element Method to the solutions of stochastic LLB. To overcome the lack of regularity of the solution in the case $d=2$, we propose a Finite Element scheme for a regularized version of the equation. We then obtain error estimates of numerical solutions and for the solution of the regularized equation as well as the rate of convergence of this solution to the solution of the stochastic LLB equation. As a consequence, the convergence in probability of the approximate solutions to the solution of the stochastic LLB equation is derived. A stronger result is obtained in the case $d=1$ due to a new regularity result for the LLB equation which allows us to avoid regularization.
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来源期刊
IMA Journal of Numerical Analysis
IMA Journal of Numerical Analysis 数学-应用数学
CiteScore
5.30
自引率
4.80%
发文量
79
审稿时长
6-12 weeks
期刊介绍: The IMA Journal of Numerical Analysis (IMAJNA) publishes original contributions to all fields of numerical analysis; articles will be accepted which treat the theory, development or use of practical algorithms and interactions between these aspects. Occasional survey articles are also published.
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