Wataru Namiki
(National Institute for Materials Science
)
;
Daiki Nishioka
(National Institute for Materials Science
)
;
Yuki Nomura
;
Takashi Tsuchiya
(National Institute for Materials Science
)
;
Kazuo Yamamoto
;
Kazuya Terabe
(National Institute for Materials Science
)
Description:
(abstract)Physical reservoirs are a promising approach for realizing high-performance artificial intelligence devices utilizing physical devices. Although nonlinear interfered spin-wave multi-detection exhibits high nonlinearity and the ability to map in high dimensional feature space, it does not have sufficient performance to process time-series data precisely. Herein, we report our development of an iono-magnonic reservoir by combining such interfered spin wave multi-detection and ion-gating involving protonation-induced redox reaction triggered by the application of voltage. This study is the first to report the manipulation of the propagating spin wave property by ion-gating and the application of same to physical reservoir computing. The subject iono-magnonic reservoir can generate various reservoir states in a single homogenous medium, by utilizing a spin wave property modulated by ion-gating. Utilizing the strong nonlinearity resulting from chaos, the reservoir showed good computational performance in completing the Mackey-Glass chaotic time-series prediction task, and the performance is comparable to that exhibited by simulated neural networks.
Rights:
Keyword: reservoir computing, spin wave, ion-gating
Date published: 2024-11-17
Publisher: Wiley
Journal:
Funding:
Manuscript type: Publisher's version (Version of record)
MDR DOI:
First published URL: https://doi.org/10.1002/advs.202411777
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Updated at: 2025-02-10 16:30:21 +0900
Published on MDR: 2025-02-10 16:30:21 +0900
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