Quantifying the computational capability of a nanomagnetic reservoir computing platform with emergent magnetisation dynamics

Vidamour, I. orcid.org/0000-0002-6909-2711, Ellis, M.O.A. orcid.org/0000-0003-0338-8920, Griffin, D. et al. (12 more authors) (2022) Quantifying the computational capability of a nanomagnetic reservoir computing platform with emergent magnetisation dynamics. Nanotechnology, 33 (48). 485203. ISSN 0957-4484

Abstract

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Copyright, Publisher and Additional Information: © 2022 IOP Publishing Ltd. As the Version of Record of this article is going to be / has been published on a gold open access basis under a CC BY 3.0 licence, this Accepted Manuscript is available for reuse under a CC BY 3.0 licence immediately. Everyone is permitted to use all or part of the original content in this article, provided that they adhere to all the terms of the licence https://creativecommons.org/licences/by/3.0.
Keywords: Domain Wall Devices; Machine Learning; Nanomagnetism; Patterned Magnetic Films; Reservoir Computing
Dates:
  • Accepted: 8 August 2022
  • Published (online): 8 September 2022
  • Published: November 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Materials Science and Engineering (Sheffield)
Funding Information:
FunderGrant number
Engineering and Physical Sciences Research CouncilEP/S009647/1; EP/V006339/1; 2276907
European Commission - HORIZON 2020828985
Depositing User: Symplectic Sheffield
Date Deposited: 26 Aug 2022 08:18
Last Modified: 06 Feb 2023 16:51
Status: Published
Publisher: IOP Publishing
Refereed: Yes
Identification Number: https://doi.org/10.1088/1361-6528/ac87b5
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