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

Author

Listed:
  • Yiming Sun

    (Beihang University)

  • Tao Lin

    (Beihang University)

  • Na Lei

    (Beihang University)

  • Xing Chen

    (Beihang University)

  • Wang Kang

    (Beihang University)

  • Zhiyuan Zhao

    (Chinese Academy of Sciences)

  • Dahai Wei

    (Chinese Academy of Sciences)

  • Chao Chen

    (Beihang University)

  • Simin Pang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Linglong Hu

    (Jilin Normal University)

  • Liu Yang

    (Beihang University)

  • Enxuan Dong

    (Beihang University)

  • Li Zhao

    (Beijing Normal University)

  • Lei Liu

    (Chinese Academy of Sciences)

  • Zhe Yuan

    (Beijing Normal University)

  • Aladin Ullrich

    (University of Augsburg)

  • Christian H. Back

    (Technical University of Munich
    Munich Center for Quantum Science and Technology (MCQST)
    Technical University of Munich)

  • Jun Zhang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Dong Pan

    (Chinese Academy of Sciences)

  • Jianhua Zhao

    (Chinese Academy of Sciences)

  • Ming Feng

    (Jilin Normal University)

  • Albert Fert

    (Beihang University
    Université Paris-Saclay)

  • Weisheng Zhao

    (Beihang University)

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 0.7PbMg1/3Nb2/3O3−0.3PbTiO3 (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.

Suggested Citation

  • Yiming Sun & Tao Lin & Na Lei & Xing Chen & Wang Kang & Zhiyuan Zhao & Dahai Wei & Chao Chen & Simin Pang & Linglong Hu & Liu Yang & Enxuan Dong & Li Zhao & Lei Liu & Zhe Yuan & Aladin Ullrich & Chris, 2023. "Experimental demonstration of a skyrmion-enhanced strain-mediated physical reservoir computing system," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39207-9
    DOI: 10.1038/s41467-023-39207-9
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    References listed on IDEAS

    as
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    1. Yong Xu & Fan Zhang & Albert Fert & Henri-Yves Jaffres & Yongshan Liu & Renyou Xu & Yuhao Jiang & Houyi Cheng & Weisheng Zhao, 2024. "Orbitronics: light-induced orbital currents in Ni studied by terahertz emission experiments," Nature Communications, Nature, vol. 15(1), pages 1-7, December.

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