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Computer Physics Communications
Article . 2020 . Peer-reviewed
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Computational micromagnetics with Commics

Authors: Carl-Martin Pfeiler; Michele Ruggeri; Bernhard Stiftner; Lukas Exl; Matthias Hochsteger; Gino Hrkac; Joachim Schöberl; +2 Authors

Computational micromagnetics with Commics

Abstract

We present our open-source Python module Commics for the study of the magnetization dynamics in ferromagnetic materials via micromagnetic simulations. It implements state-of-the-art unconditionally convergent finite element methods for the numerical integration of the Landau-Lifshitz-Gilbert equation. The implementation is based on the multiphysics finite element software Netgen/NGSolve. The simulation scripts are written in Python, which leads to very readable code and direct access to extensive post-processing. Together with documentation and example scripts, the code is freely available on GitLab.

Countries
Austria, Italy
Keywords

Finite elements; Hybrid FEM–BEM methods; Landau–Lifshitz–Gilbert equation; Micromagnetics; Time-stepping algorithms; Unconditional convergence, MOTION, FINITE-ELEMENT SCHEME, Hybrid FEM–BEM methods, Finite elements, micromagnetics, Landau–Lifshitz–Gilbert equation, Optics, electromagnetic theory, FOS: Physical sciences, FERROMAGNETIC-RESONANCE, 101014 Numerische Mathematik, 530, hybrid FEM-BEM methods, Statistical mechanics, structure of matter, Landau-Lifshitz-Gilbert equation, 103043 Computational physics, FOS: Mathematics, NUMERICS, Mathematics - Numerical Analysis, QA, 101014 Numerical mathematics, Time-stepping algorithms, CONVERGENT, Numerical Analysis (math.NA), Computational Physics (physics.comp-ph), Micromagnetics, Unconditional convergence, SIMULATIONS, 620, time-stepping algorithms, unconditional convergence, finite elements, LANDAU-LIFSHITZ EQUATION, Hybrid FEM-BEM methods, Physics - Computational Physics, Mathematics, 103043 Computational Physics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
Green
bronze