A Gauss-Seidel projection method with the minimal number of updates for the stray field in micromagnetics simulations

Author:

Li Panchi1,Ma Zetao1,Du Rui12,Chen Jingrun1234

Affiliation:

1. School of Mathematical Sciences, Soochow University, Suzhou, 215006, China

2. Mathematical Center for Interdisciplinary Research, Soochow University, Suzhou, 215006, China

3. School of Mathematical Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China

4. Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, Jiangsu 215123, China

Abstract

<p style='text-indent:20px;'>Magnetization dynamics in magnetic materials is often modeled by the Landau-Lifshitz equation, which is solved numerically in general. In micromagnetics simulations, the computational cost relies heavily on the time-marching scheme and the evaluation of the stray field. In this work, we propose a new method, dubbed as GSPM-BDF2, by combining the advantages of the Gauss-Seidel projection method (GSPM) and the second-order backward differentiation formula scheme (BDF2). Like GSPM, this method is first-order accurate in time and second-order accurate in space, and it is unconditionally stable with respect to the damping parameter. Remarkably, GSPM-BDF2 updates the stray field only once per time step, leading to an efficiency improvement of about <inline-formula><tex-math id="M1">\begin{document}$ 60\% $\end{document}</tex-math></inline-formula> compared with the state-of-the-art of GSPM for micromagnetics simulations. For Standard Problems #4 and #5 from National Institute of Standards and Technology, GSPM-BDF2 reduces the computational time over the popular software OOMMF by <inline-formula><tex-math id="M2">\begin{document}$ 82\% $\end{document}</tex-math></inline-formula> and <inline-formula><tex-math id="M3">\begin{document}$ 96\% $\end{document}</tex-math></inline-formula>, respectively. Thus, the proposed method provides a more efficient choice for micromagnetics simulations.</p>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Discrete Mathematics and Combinatorics

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