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arXiv 1702.03027math.NAcs.NA
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随机Maxwell-Landau-Lifshitz-Gilbert系统的有限元近似

A finite element approximation for the stochastic Maxwell--Landau--Lifshitz--Gilbert system

The University of Sydney(悉尼大学);The University of New South Wales(新南威尔士大学)

Beniamin Goldys, Kim-Ngan Le, Thanh Tran

AI总结:

本文提出一种收敛的θ线性方案,用于近似随机Maxwell-Landau-Lifshitz-Gilbert系统的解,并证明了在不同时间步长条件下解的收敛性及弱鞅解的存在性。

摘要:

随机Landau-Lifshitz-Gilbert方程与Maxwell方程耦合(称为随机MLLG系统)描述了磁性纳米结构存储器中域墙和涡旋的形成。我们首先将随机LLG方程转化为具有时间可导解的方程。然后提出一种收敛的θ线性方案来近似改写系统的解。作为结果,我们证明了近似解的收敛性,时间步长和空间步长的条件取决于θ的值。因此,我们证明了随机MLLG系统的弱鞅解的存在性。数值结果展示了该方法的应用性。

英文摘要:

The stochastic Landau--Lifshitz--Gilbert (LLG) equation coupled with the Maxwell equations (the so called stochastic MLLG system) describes the creation of domain walls and vortices (fundamental objects for the novel nanostructured magnetic memories). We first reformulate the stochastic LLG equation into an equation with time-differentiable solutions. We then propose a convergent $θ$-linear scheme to approximate the solutions of the reformulated system. As a consequence, we prove convergence of the approximate solutions, with no or minor conditions on time and space steps (depending on the value of $θ$). Hence, we prove the existence of weak martingale solutions of the stochastic MLLG system. Numerical results are presented to show applicability of the method.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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