journal article·2018-05-01Open access

Efficient adaptive pseudo-symplectic numerical integration techniques for Landau-Lifshitz dynamics

M. d’Aquino, F. Capuano, G. Coppola, C. Serpico, I. D. Mayergoyz

AIP Advances· Volume 8· Issue 5

Abstract

Numerical time integration schemes for Landau-Lifshitz magnetization dynamics are considered. Such dynamics preserves the magnetization amplitude and, in the absence of dissipation, also implies the conservation of the free energy. This property is generally lost when time discretization is performed for the numerical solution. In this work, explicit numerical schemes based on Runge-Kutta methods are introduced. The schemes are termed pseudo-symplectic in that they are accurate to order p, but preserve magnetization amplitude and free energy to order q > p. An effective strategy for adaptive time-stepping control is discussed for schemes of this class. Numerical tests against analytical solutions for the simulation of fast precessional dynamics are performed in order to point out the effectiveness of the proposed methods.
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Research context

OpenAlex topics: Numerical methods for differential equations · Electromagnetic Simulation and Numerical Methods · Advanced Numerical Methods in Computational Mathematics

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Affiliations

Engineering Department, University of Naples “Parthenope” 1 , 80143 Naples, Italy

Department of Industrial Engineering, University of Naples Federico II 2 , 80125 Naples, Italy

DIETI, University of Naples Federico II 3 , 80125 Naples, Italy

ECE Department, University of Maryland 4 , College Park, MD 20742, USA

Funding

University of Naples Parthenope

References (22)

Show source-provided references
1. Nonlinearity · 1990 · 3 · 23110.1088/0951-7715/3/2/001 ↗
2. J. Comput. Phys. · 1993 · 107 · 10510.1006/jcph.1993.1128 ↗
3. Physica B · 2001 · 306 · 19510.1016/s0921-4526(01)01003-1 ↗
4. J. Appl. Phys. · 2001 · 89 · 699110.1063/1.1358818 ↗
5. 2009
6. Phys. Rev. B · 2002 · 65 · 10441210.1103/physrevb.65.104412 ↗
7. J. Comput. Phys. · 2005 · 209 · 73010.1016/j.jcp.2005.04.001 ↗
8. IEEE Trans. Magn. · 2007 · 43 · 291710.1109/tmag.2007.892534 ↗
9. Journal of Applied Physics · 2008 · 103 · 07D92010.1063/1.2838461 ↗
10. BIT Numer. Math. · 1998 · 38 · 43910.1007/bf02510253 ↗
11. J. Comput. Phys. · 2017 · 328 · 8610.1016/j.jcp.2016.10.040 ↗
12. IEEE Trans. Magn. · 2014 · 50 · 7100504
13. BIT Numer. Math. · 1988 · 28 · 87710.1007/bf01954907 ↗
14. 2010
15. 2016
16. 2017 · 2257
17. J. Math. Anal. Appl. · 1982 · 89 · 23310.1016/0022-247x(82)90100-7 ↗
18. IEEE Trans. Magn. · 2003 · 39 · 250110.1109/tmag.2003.816453 ↗
19. Phys. Rev. B · 2000 · 61 · 341010.1103/physrevb.61.3410 ↗
20. J. Appl. Phys. · 2004 · 95 · 705510.1063/1.1689910 ↗
21. IEEE Trans. Magn. · 2009 · 45 · 522410.1109/tmag.2009.2031067 ↗
22. Physica B · 2016 · 486 · 12610.1016/j.physb.2015.10.011 ↗