Magnetic Skyrmion as a Nonlinear Resistive Element: A Potential Building Block for Reservoir Computing

Diana Prychynenko, Matthias Sitte, Kai Litzius, Benjamin Krüger, George Bourianoff, Mathias Kläui, Jairo Sinova, and Karin Everschor-Sitte
Phys. Rev. Applied 9, 014034 – Published 31 January 2018

Abstract

Inspired by the human brain, there is a strong effort to find alternative models of information processing capable of imitating the high energy efficiency of neuromorphic information processing. One possible realization of cognitive computing involves reservoir computing networks. These networks are built out of nonlinear resistive elements which are recursively connected. We propose that a Skyrmion network embedded in magnetic films may provide a suitable physical implementation for reservoir computing applications. The significant key ingredient of such a network is a two-terminal device with nonlinear voltage characteristics originating from magnetoresistive effects, such as the anisotropic magnetoresistance or the recently discovered noncollinear magnetoresistance. The most basic element for a reservoir computing network built from “Skyrmion fabrics” is a single Skyrmion embedded in a ferromagnetic ribbon. In order to pave the way towards reservoir computing systems based on Skyrmion fabrics, we simulate and analyze (i) the current flow through a single magnetic Skyrmion due to the anisotropic magnetoresistive effect and (ii) the combined physics of local pinning and the anisotropic magnetoresistive effect.

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  • Received 14 February 2017
  • Revised 27 June 2017

DOI:https://doi.org/10.1103/PhysRevApplied.9.014034

© 2018 American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied Physics

Authors & Affiliations

Diana Prychynenko1,2,*, Matthias Sitte1, Kai Litzius1,2,3, Benjamin Krüger4, George Bourianoff5,†, Mathias Kläui1, Jairo Sinova1,6, and Karin Everschor-Sitte1

  • 1Institute of Physics, Johannes Gutenberg University Mainz, 55099 Mainz, Germany
  • 2Graduate School of Excellence Material Science in Mainz, 55128 Mainz, Germany
  • 3Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
  • 4Institute for Laser Technologies in Medicine and Metrology, University of Ulm, 89081 Ulm, Germany
  • 5Intel Corporation, 1300 South MoPac Expressway, Austin, Texas 78746, USA
  • 6Institute of Physics ASCR, v.v.i, Cukrovarnicka 10, 162 00 Praha 6, Czech Republic

  • *Corresponding author. prychynenko@uni-mainz.de
  • Corresponding author. gibouria@gmail.com

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Vol. 9, Iss. 1 — January 2018

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