Reconfigurable reservoir computing in a magnetic metamaterial

Abstract

In-materia reservoir computing (RC) leverages the intrinsic physical responses of functional materials to perform complex computational tasks. Magnetic metamaterials are exciting candidates for RC due to their huge state space, nonlinear emergent dynamics, and non-volatile memory. However, to be suitable for a broad range of tasks, the material system is required to exhibit a broad range of properties, and isolating these behaviours experimentally can often prove difficult. By using an electrically accessible device consisting of an array of interconnected magnetic nanorings- a system shown to exhibit complex emergent dynamics- here we show how reconfiguring the reservoir architecture allows exploitation of different aspects the system’s dynamical behaviours. This is evidenced through state-of-the-art performance in diverse benchmark tasks with very different computational requirements, highlighting the additional computational configurability that can be obtained by altering the input/output architecture around the material system.

Metadata

Item Type:	Article
Authors/Creators:	Vidamour, I.T. https://orcid.org/0000-0002-6909-2711 Swindells, C. Venkat, G. Manneschi, L. Fry, P.W. Welbourne, A. https://orcid.org/0000-0002-9089-9712 Rowan-Robinson, R.M. Backes, D. https://orcid.org/0000-0002-1019-3323 Maccherozzi, F. Dhesi, S.S. https://orcid.org/0000-0003-4966-0002 Vasilaki, E. https://orcid.org/0000-0003-3705-7070 Allwood, D.A. Hayward, T.J. https://orcid.org/0000-0002-3732-3095
Copyright, Publisher and Additional Information:	© 2023 The Author(s). 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/ licenses/by/4.0/.
Keywords:	Magnetic devices; Spintronics
Dates:	Published: 26 August 2023 Published (online): 26 August 2023 Accepted: 17 August 2023
Institution:	The University of Sheffield
Academic Units:	The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Materials Science and Engineering (Sheffield) The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Funding Information:	Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/S009647/1 ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/V006339/1
Depositing User:	Symplectic Sheffield
Date Deposited:	04 Sep 2023 15:00
Last Modified:	22 Nov 2023 14:23
Status:	Published
Publisher:	Springer Science and Business Media LLC
Refereed:	Yes
Identification Number:	10.1038/s42005-023-01352-4
Related URLs:	Dataset Software or Code
Open Archives Initiative ID (OAI ID):	oai:eprints.whiterose.ac.uk:202961

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Reconfigurable reservoir computing in a magnetic metamaterial

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Reconfigurable reservoir computing in a magnetic metamaterial

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