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Empowering neuromorphic computing with topological states

Faisal Ahmed and Zhipei Sun

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 Corresponding author: Zhipei Sun, zhipei.sun@aalto.fi

DOI: 10.1088/1674-4926/24080029

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[1]
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Fig. 1.  (Color online) Schematic diagram of neuromorphic computing with ferroelectric Chern insulators. (a) Topologically protected edge states in magic-angle twisted bilayer graphene with spontaneous ferroelectricity. Delicately controlled back gate voltage pulse (Vbg) can change the ferroelectric polarization (Pr), enabling selective and non-volatile switching between Chern insulating states with distinct Chern numbers. (b) Schematic of neuromorphic computing with ferroelectric Chern insulators. The weights of the trained kernel are distributed on the quantized resistance values corresponding to these topological edge states, facilitating robust and efficient computation. The figure is provided courtesy of Prof. Feng Miao.

[1]
Klitzing K v, Dorda G, Pepper M. New method for high-accuracy determination of the fine-structure constant based on quantized Hall resistance. Phys Rev Lett, 1980, 45, 494 doi: 10.1103/PhysRevLett.45.494
[2]
Chang C Z, Zhang J S, Feng X, et al. Experimental observation of the quantum anomalous Hall effect in a magnetic topological insulator. Science, 2013, 340, 167 doi: 10.1126/science.1234414
[3]
König M, Wiedmann S, Brüne C, et al. Quantum spin Hall insulator state in HgTe quantum wells. Science, 2007, 318, 766 doi: 10.1126/science.1148047
[4]
Andrei E Y, MacDonald A H. Graphene bilayers with a twist. Nat Mater, 2020, 19, 1265 doi: 10.1038/s41563-020-00840-0
[5]
Chen M, Xie Y, Cheng B, et al. Selective and quasi-continuous switching of ferroelectric Chern insulator devices for neuromorphic computing. Nat Nanotechnol, 2024, 19, 962 doi: 10.1038/s41565-024-01698-y
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    Received: 22 July 2024 Revised: Online: Accepted Manuscript: 03 September 2024Uncorrected proof: 04 September 2024Published: 15 November 2024

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      Faisal Ahmed, Zhipei Sun. Empowering neuromorphic computing with topological states[J]. Journal of Semiconductors, 2024, 45(11): 110401. doi: 10.1088/1674-4926/24080029 ****F Ahmed and Z P Sun, Empowering neuromorphic computing with topological states[J]. J. Semicond., 2024, 45(11), 110401 doi: 10.1088/1674-4926/24080029
      Citation:
      Faisal Ahmed, Zhipei Sun. Empowering neuromorphic computing with topological states[J]. Journal of Semiconductors, 2024, 45(11): 110401. doi: 10.1088/1674-4926/24080029 ****
      F Ahmed and Z P Sun, Empowering neuromorphic computing with topological states[J]. J. Semicond., 2024, 45(11), 110401 doi: 10.1088/1674-4926/24080029

      Empowering neuromorphic computing with topological states

      DOI: 10.1088/1674-4926/24080029
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      • Faisal Ahmed received his doctoral degree from Sungkyunkwan University, South Korea in 2018. He is currently working as Staff scientist at Aalto University Finland. His research interests include emerging nanomaterials, and their applications in electronics, optoelectronics, and photonics
      • Zhipei Sun is a Professor of Photonics and the head of the Photonics Research Group at the Department of Electronics and Nanoengineering of Aalto University, Finland. He earned his PhD from the Institute of Physics, Chinese Academy of Sciences, in 2005. His research interests include nonlinear optics, nanophotonics, and ultrafast photonics
      • Corresponding author: zhipei.sun@aalto.fi
      • Received Date: 2024-07-22
        Available Online: 2024-09-03

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