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Experimental demonstration of a skyrmion-enhanced strain-mediated physical reservoir computing system

Physical reservoirs holding intrinsic nonlinearity, high dimensionality, and memory effects have attracted considerable interest regarding solving complex tasks efficiently. Particularly, spintronic and strain-mediated electronic physical reservoirs are appealing due to their high speed, multi-param...

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Detalles Bibliográficos
Autores principales: Sun, Yiming, Lin, Tao, Lei, Na, Chen, Xing, Kang, Wang, Zhao, Zhiyuan, Wei, Dahai, Chen, Chao, Pang, Simin, Hu, Linglong, Yang, Liu, Dong, Enxuan, Zhao, Li, Liu, Lei, Yuan, Zhe, Ullrich, Aladin, Back, Christian H., Zhang, Jun, Pan, Dong, Zhao, Jianhua, Feng, Ming, Fert, Albert, Zhao, Weisheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10257712/
https://www.ncbi.nlm.nih.gov/pubmed/37301906
http://dx.doi.org/10.1038/s41467-023-39207-9
Descripción
Sumario:Physical reservoirs holding intrinsic nonlinearity, high dimensionality, and memory effects have attracted considerable interest regarding solving complex tasks efficiently. Particularly, spintronic and strain-mediated electronic physical reservoirs are appealing due to their high speed, multi-parameter fusion and low power consumption. Here, we experimentally realize a skyrmion-enhanced strain-mediated physical reservoir in a multiferroic heterostructure of Pt/Co/Gd multilayers on (001)-oriented 0.7PbMg(1/3)Nb(2/3)O(3)−0.3PbTiO(3) (PMN-PT). The enhancement is coming from the fusion of magnetic skyrmions and electro resistivity tuned by strain simultaneously. The functionality of the strain-mediated RC system is successfully achieved via a sequential waveform classification task with the recognition rate of 99.3% for the last waveform, and a Mackey-Glass time series prediction task with normalized root mean square error (NRMSE) of 0.2 for a 20-step prediction. Our work lays the foundations for low-power neuromorphic computing systems with magneto-electro-ferroelastic tunability, representing a further step towards developing future strain-mediated spintronic applications.