Distinguishing artificial spin ice states using magnetoresistance effect for neuromorphic computing

Wenjie Hu; Zefeng Zhang; Yanghui Liao; Qiang Li; Yang Shi; Huanyu Zhang; Xumeng Zhang; Chang Niu; Yu Wu; Weichao Yu; Xiaodong Zhou; Hangwen Guo; Wenbin Wang; Jiang Xiao; Lifeng Yin; Qi Liu; Jian Shen

doi:10.1038/s41467-023-38286-y

Distinguishing artificial spin ice states using magnetoresistance effect for neuromorphic computing

Nat Commun. 2023 May 4;14(1):2562. doi: 10.1038/s41467-023-38286-y.

Authors

Wenjie Hu^{1

2}, Zefeng Zhang^{3

4}, Yanghui Liao^{1

2}, Qiang Li^{1

2}, Yang Shi^{1

2}, Huanyu Zhang^{1

2}, Xumeng Zhang³, Chang Niu^{1

2}, Yu Wu^{1

2}, Weichao Yu^{1

5}, Xiaodong Zhou^{1

2

5}, Hangwen Guo^{1

2

5}, Wenbin Wang^{1

2

5}, Jiang Xiao^{1

2

5

6

7}, Lifeng Yin^{8

9

10

11

12

13}, Qi Liu^{14

15}, Jian Shen^{16

17

18

19

20

21}

Affiliations

¹ State Key Laboratory of Surface Physics, Institute for Nanoelectronic Devices and Quantum Computing, and Department of Physics, Fudan University, Shanghai, China.
² Shanghai Qi Zhi Institute, Shanghai, China.
³ Frontier Institute of Chip and System, Fudan University, Shanghai, China.
⁴ Research Institute of Intelligent Complex Systems and ISTBI, Fudan University, Shanghai, China.
⁵ Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.
⁶ Shanghai Research Center for Quantum Sciences, Shanghai, China.
⁷ Collaborative Innovation Center of Advanced Microstructures, Nanjing, China.
⁸ State Key Laboratory of Surface Physics, Institute for Nanoelectronic Devices and Quantum Computing, and Department of Physics, Fudan University, Shanghai, China. lifengyin@fudan.edu.cn.
⁹ Shanghai Qi Zhi Institute, Shanghai, China. lifengyin@fudan.edu.cn.
¹⁰ Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China. lifengyin@fudan.edu.cn.
¹¹ Shanghai Research Center for Quantum Sciences, Shanghai, China. lifengyin@fudan.edu.cn.
¹² Collaborative Innovation Center of Advanced Microstructures, Nanjing, China. lifengyin@fudan.edu.cn.
¹³ State Key Laboratory of Integrated Chips and Systems, Fudan University, Shanghai, China. lifengyin@fudan.edu.cn.
¹⁴ Frontier Institute of Chip and System, Fudan University, Shanghai, China. qi_liu@fudan.edu.cn.
¹⁵ State Key Laboratory of Integrated Chips and Systems, Fudan University, Shanghai, China. qi_liu@fudan.edu.cn.
¹⁶ State Key Laboratory of Surface Physics, Institute for Nanoelectronic Devices and Quantum Computing, and Department of Physics, Fudan University, Shanghai, China. shenj5494@fudan.edu.cn.
¹⁷ Shanghai Qi Zhi Institute, Shanghai, China. shenj5494@fudan.edu.cn.
¹⁸ Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China. shenj5494@fudan.edu.cn.
¹⁹ Shanghai Research Center for Quantum Sciences, Shanghai, China. shenj5494@fudan.edu.cn.
²⁰ Collaborative Innovation Center of Advanced Microstructures, Nanjing, China. shenj5494@fudan.edu.cn.
²¹ Shanghai Branch, CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics, Shanghai, China. shenj5494@fudan.edu.cn.

Abstract

Artificial spin ice (ASI) consisting patterned array of nano-magnets with frustrated dipolar interactions offers an excellent platform to study frustrated physics using direct imaging methods. Moreover, ASI often hosts a large number of nearly degenerated and non-volatile spin states that can be used for multi-bit data storage and neuromorphic computing. The realization of the device potential of ASI, however, critically relies on the capability of transport characterization of ASI, which has not been demonstrated so far. Using a tri-axial ASI system as the model system, we demonstrate that transport measurements can be used to distinguish the different spin states of the ASI system. Specifically, by fabricating a tri-layer structure consisting a permalloy base layer, a Cu spacer layer and the tri-axial ASI layer, we clearly resolve different spin states in the tri-axial ASI system using lateral transport measurements. We have further demonstrated that the tri-axial ASI system has all necessary required properties for reservoir computing, including rich spin configurations to store input signals, nonlinear response to input signals, and fading memory effect. The successful transport characterization of ASI opens up the prospect for novel device applications of ASI in multi-bit data storage and neuromorphic computing.