Iono–Magnonic Reservoir Computing With Chaotic Spin Wave Interference Manipulated by Ion‐Gating

• Published in: Advanced science Vol. 12; no. 3; pp. e2411777 - n/a
• Main Authors: Namiki, Wataru, Nishioka, Daiki, Nomura, Yuki, Tsuchiya, Takashi, Yamamoto, Kazuo, Terabe, Kazuya
• Format: Journal Article
• Language: English
• Published: Germany John Wiley & Sons, Inc 01.01.2025; John Wiley and Sons Inc; Wiley
• Subjects: Anisotropy; Electrolytes; Electrons; Fourier transforms; Magnetic fields; nonlinear interference; proton; redox; reservoir computing; Single crystals; solid‐state electrolyte; Spectrum analysis; spin wave; spin wave; reservoir computing; nonlinear interference; solid‐state electrolyte; proton; redox
• ISSN: 2198-3844; 2198-3844
• DOI: 10.1002/advs.202411777

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, 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 is reported. This study is the first to report the manipulation of the propagating spin wave property by ion‐gating and the application of the 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 shows 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. This work presents an iono–magnonic reservoir computing device that combines interfered spin wave multi‐detection and ion‐gating involving a protonation‐induced redox reaction. The iono–magnonic reservoir can generate various reservoir states by utilizing spin wave properties modulated by the ion‐gating. With the strong nonlinearity resulting from chaos, the reservoir performs the chaotic time‐series data prediction task with excellent computational performance.