Experimental demonstration of a skyrmion-enhanced strain-mediated physical reservoir computing system
Yiming Sun, Tao Lin, Na Lei, Xing Chen, Wang Kang, Zhiyuan Zhao, Dahai Wei, Chao Chen, Simin Pang, Linglong Hu, Yang Liu, Enxuan Dong, Li Zhao, Lei Liu, Zhe Yuan, Aladin Ullrich, C. H. Back, Jun Zhang, Dong Pan, Jianhua Zhao, Ming Feng, A. Fert, Weisheng Zhao
Abstract
Abstract 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.