Perspective on unconventional computing using magnetic skyrmions

Abstract

Learning and pattern recognition inevitably requires memory of previous events, a feature that conventional CMOS hardware needs to artificially simulate. Dynamical systems naturally provide the memory, complexity, and nonlinearity needed for a plethora of different unconventional computing approaches. In this perspective article, we focus on the unconventional computing concept of reservoir computing and provide an overview of key physical reservoir works reported. We focus on the promising platform of magnetic structures and, in particular, skyrmions, which potentially allow for low-power applications. Moreover, we discuss skyrmion-based implementations of Brownian computing, which has recently been combined with reservoir computing. This computing paradigm leverages the thermal fluctuations present in many skyrmion systems. Finally, we provide an outlook on the most important challenges in this field.

19 pages and 3 figures

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• Imaging Topological Defect Dynamics Mediating 2D Skyrmion Lattice Melting
• Realizing Quantitative Quasiparticle Modeling of Skyrmion Dynamics in Arbitrary Potentials
• Artificial Spin Ice: A Tutorial on Design and Control of Geometry, Microstate, Magnon Dynamics & Neuromorphic Computing
• Skyrmion Lattice Order Controlled by Confinement Geometry
• Tunable Skyrmion-Antiskyrmion Dynamics in Co/Pt Nanocontacts for Spintronic Applications
• Correlating on-the-fly Electrical and Optical Skyrmion Readout
• Predicting the future with magnons
• Metrics for spin-based computing
• Ferromagnetic monolayer with interfacial Dzyaloshinskii-Moriya interaction: magnon spectrum and effect of quenched disorder
• Macroscopic entanglement between localized domain walls inside a cavity