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Brownian reservoir computing realized using geometrically confined skyrmion dynamics

Reservoir computing (RC) has been considered as one of the key computational principles beyond von-Neumann computing. Magnetic skyrmions, topological particle-like spin textures in magnetic films are particularly promising for implementing RC, since they respond strongly nonlinearly to external stim...

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Autores principales: Raab, Klaus, Brems, Maarten A., Beneke, Grischa, Dohi, Takaaki, Rothörl, Jan, Kammerbauer, Fabian, Mentink, Johan H., Kläui, Mathias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9666653/
https://www.ncbi.nlm.nih.gov/pubmed/36379941
http://dx.doi.org/10.1038/s41467-022-34309-2
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author Raab, Klaus
Brems, Maarten A.
Beneke, Grischa
Dohi, Takaaki
Rothörl, Jan
Kammerbauer, Fabian
Mentink, Johan H.
Kläui, Mathias
author_facet Raab, Klaus
Brems, Maarten A.
Beneke, Grischa
Dohi, Takaaki
Rothörl, Jan
Kammerbauer, Fabian
Mentink, Johan H.
Kläui, Mathias
author_sort Raab, Klaus
collection PubMed
description Reservoir computing (RC) has been considered as one of the key computational principles beyond von-Neumann computing. Magnetic skyrmions, topological particle-like spin textures in magnetic films are particularly promising for implementing RC, since they respond strongly nonlinearly to external stimuli and feature inherent multiscale dynamics. However, despite several theoretical proposals that exist for skyrmion reservoir computing, experimental realizations have been elusive until now. Here, we propose and experimentally demonstrate a conceptually new approach to skyrmion RC that leverages the thermally activated diffusive motion of skyrmions. By confining the electrically gated and thermal skyrmion motion, we find that already a single skyrmion in a confined geometry suffices to realize nonlinearly separable functions, which we demonstrate for the XOR gate along with all other Boolean logic gate operations. Besides this universality, the reservoir computing concept ensures low training costs and ultra-low power operation with current densities orders of magnitude smaller than those used in existing spintronic reservoir computing demonstrations. Our proposed concept is robust against device imperfections and can be readily extended by linking multiple confined geometries and/or by including more skyrmions in the reservoir, suggesting high potential for scalable and low-energy reservoir computing.
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spelling pubmed-96666532022-11-17 Brownian reservoir computing realized using geometrically confined skyrmion dynamics Raab, Klaus Brems, Maarten A. Beneke, Grischa Dohi, Takaaki Rothörl, Jan Kammerbauer, Fabian Mentink, Johan H. Kläui, Mathias Nat Commun Article Reservoir computing (RC) has been considered as one of the key computational principles beyond von-Neumann computing. Magnetic skyrmions, topological particle-like spin textures in magnetic films are particularly promising for implementing RC, since they respond strongly nonlinearly to external stimuli and feature inherent multiscale dynamics. However, despite several theoretical proposals that exist for skyrmion reservoir computing, experimental realizations have been elusive until now. Here, we propose and experimentally demonstrate a conceptually new approach to skyrmion RC that leverages the thermally activated diffusive motion of skyrmions. By confining the electrically gated and thermal skyrmion motion, we find that already a single skyrmion in a confined geometry suffices to realize nonlinearly separable functions, which we demonstrate for the XOR gate along with all other Boolean logic gate operations. Besides this universality, the reservoir computing concept ensures low training costs and ultra-low power operation with current densities orders of magnitude smaller than those used in existing spintronic reservoir computing demonstrations. Our proposed concept is robust against device imperfections and can be readily extended by linking multiple confined geometries and/or by including more skyrmions in the reservoir, suggesting high potential for scalable and low-energy reservoir computing. Nature Publishing Group UK 2022-11-15 /pmc/articles/PMC9666653/ /pubmed/36379941 http://dx.doi.org/10.1038/s41467-022-34309-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Raab, Klaus
Brems, Maarten A.
Beneke, Grischa
Dohi, Takaaki
Rothörl, Jan
Kammerbauer, Fabian
Mentink, Johan H.
Kläui, Mathias
Brownian reservoir computing realized using geometrically confined skyrmion dynamics
title Brownian reservoir computing realized using geometrically confined skyrmion dynamics
title_full Brownian reservoir computing realized using geometrically confined skyrmion dynamics
title_fullStr Brownian reservoir computing realized using geometrically confined skyrmion dynamics
title_full_unstemmed Brownian reservoir computing realized using geometrically confined skyrmion dynamics
title_short Brownian reservoir computing realized using geometrically confined skyrmion dynamics
title_sort brownian reservoir computing realized using geometrically confined skyrmion dynamics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9666653/
https://www.ncbi.nlm.nih.gov/pubmed/36379941
http://dx.doi.org/10.1038/s41467-022-34309-2
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