Antiferromagnetic skyrmion based shape-configured leaky-integrate-fire neuron device

被引:15
|
作者
Bindal, Namita [1 ]
Raj, Ravish Kumar [1 ]
Kaushik, Brajesh Kumar [1 ]
机构
[1] Indian Inst Technol Roorkee, Dept Elect & Commun Engn, Roorkee 247667, Uttarakhand, India
关键词
leaky-integrate-fire (LIF) neuron; neuromorphic computing; antiferromagnetic skyrmion; edge-repulsive forces; CURRENT-DRIVEN DYNAMICS; MODEL;
D O I
10.1088/1361-6463/ac71e4
中图分类号
O59 [应用物理学];
学科分类号
摘要
Spintronic devices based on antiferromagnetic (AFM) skyrmion motion on the nanotracks have gained significant interest as a key component of neuromorphic data processing systems. AFM skyrmions are favorable over the ferromagnetic (FM) skyrmions as they follow the straight trajectories and prevent its annihilation at the nanotrack edges. In this paper, the AFM skyrmion-based neuron device that exhibits the leaky-integrate-fire functionality is proposed for the first time. It exploits the current-driven skyrmion dynamics on the shape-configured nanotracks that are linearly decreasing and exponentially decaying. The device structure creates the regions from lower to higher energy states for the AFM skyrmions during its motion from the wider to narrower region. This causes the repulsion force from the nanotrack edges to act on the AFM skyrmion thereby, drifting it in the backward direction in order to minimize the system energy. This provides the leaking functionality to the neuron device without any external stimuli and additional hardware cost. The average velocities during the integration and leaky processes are in the order of 10(3) and 10(2) m s(-1), respectively, for the linearly and exponentially tapered nanotracks. Moreover, the energy of the skyrmion is in the order 10(-20) J. Hence, the suggested device opens up the path for the development of high-speed and energy-efficient devices in AFM spintronics for neuromorphic computing.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] Leaky-Integrate-Fire Neuron Based on Antiferromagnetic Skyrmion Under Strain Gradient
    Raj, Ravish Kumar
    Verma, Ravi Shankar
    Saini, Shipra
    Kumar, Mohit
    Shukla, Alok Kumar
    Kaushik, Brajesh Kumar
    2024 IEEE 24TH INTERNATIONAL CONFERENCE ON NANOTECHNOLOGY, NANO 2024, 2024, : 331 - 336
  • [2] Synthetic Antiferromagnetic Skyrmion based Oscillator as Leaky Integrate and Fire Neuron Device
    Verma, Ravi Shankar
    Raj, Ravish Kumar
    Bindal, Namita
    Kaushik, Brajesh Kumar
    2023 IEEE 23RD INTERNATIONAL CONFERENCE ON NANOTECHNOLOGY, NANO, 2023, : 1025 - 1030
  • [3] Antiferromagnetic skyrmion-based energy-efficient leaky integrate and fire neuron device
    Bindal, Namita
    Rajib, Md Mahadi
    Raj, Ravish Kumar
    Atulasimha, Jayasimha
    Kaushik, Brajesh Kumar
    NANOTECHNOLOGY, 2025, 36 (16)
  • [4] A compact skyrmionic leaky-integrate-fire spiking neuron device
    Chen, Xing
    Kang, Wang
    Zhu, Daoqian
    Zhang, Xichao
    Lei, Na
    Zhang, Youguang
    Zhou, Yan
    Zhao, Weisheng
    NANOSCALE, 2018, 10 (13) : 6139 - 6146
  • [5] Antiferromagnetic Skyrmion Based Energy-Efficient Integrate-Fire Neuron Device
    Bindal, Namita
    Raj, Ravish Kumar
    Kaushik, Brajesh Kumar
    IEEE TRANSACTIONS ON ELECTRON DEVICES, 2024, 71 (01) : 280 - 286
  • [6] Proposal for a Leaky-Integrate-Fire Spiking Neuron Based on Magnetoelectric Switching of Ferromagnets
    Jaiswal, Akhilesh
    Roy, Sourjya
    Srinivasan, Gopalakrishnan
    Roy, Kaushik
    IEEE TRANSACTIONS ON ELECTRON DEVICES, 2017, 64 (04) : 1818 - 1824
  • [7] Leaky-integrate-fire neuron based on vertically extended drain Si 1-x Gex source TFET: and
    Priyanka
    Singh, Sangeeta
    Panchore, Meena
    MICROELECTRONICS JOURNAL, 2024, 148
  • [8] Skyrmionium-based Leaky Integrate and Fire Neuron
    Saini, Shipra
    Bindal, Namita
    Kaushik, Brajesh Kumar
    2023 IEEE 23RD INTERNATIONAL CONFERENCE ON NANOTECHNOLOGY, NANO, 2023, : 209 - 214
  • [9] Antiferromagnetic skyrmion repulsion based artificial neuron device
    Bindal, Namita
    Ian, Calvin Ang Chin
    Lew, Wen Siang
    Kaushik, Brajesh Kumar
    NANOTECHNOLOGY, 2021, 32 (21)
  • [10] Dzyaloshinskii-Moriya interaction gradient driven skyrmion based energy efficient leaky integrate fire neuron
    Raj, Ravish Kumar
    Saini, Shipra
    Verma, Ravi Shankar
    Kaushik, Brajesh Kumar
    Shreya, Sonal
    JOURNAL OF MAGNETISM AND MAGNETIC MATERIALS, 2025, 614