Spin-Transfer Torque Magnetic Tunnel Junction Model Based on Fokker-Planck Equation for Stochastic Circuit Simulations

Haoyan Liu, Takashi Ohsawa

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

A spin-transfer torque magnetic tunnel junction (STT-MTJ) model is proposed which is based on Fokker-Planck equation and described by Verilog-A for stochastic circuit simulations by SPICE. A new framework to calculate the magnetization angle makes the model usable widely in STT-MT J applications. The model can be applied to general situations in which the electrical current flowing through an MTJ changes its strength and direction in time. The CPU time for simulation of a large-scale circuit is shown to be much shorter than the model which is based on stochastic Landau-Lifshitz-Gilbert-Slonczewsky (s-LLGS) equation with a Langevin field. The model is applied to a leaky integrate-and-fire (LIF) neuron circuit for spiking neural networks (SNNs).

本文言語English
ホスト出版物のタイトル2022 IEEE 22nd International Conference on Nanotechnology, NANO 2022
出版社IEEE Computer Society
ページ287-290
ページ数4
ISBN(電子版)9781665452250
DOI
出版ステータスPublished - 2022
イベント22nd IEEE International Conference on Nanotechnology, NANO 2022 - Palma de Mallorca, Spain
継続期間: 2022 7月 42022 7月 8

出版物シリーズ

名前Proceedings of the IEEE Conference on Nanotechnology
2022-July
ISSN(印刷版)1944-9399
ISSN(電子版)1944-9380

Conference

Conference22nd IEEE International Conference on Nanotechnology, NANO 2022
国/地域Spain
CityPalma de Mallorca
Period22/7/422/7/8

ASJC Scopus subject areas

  • バイオエンジニアリング
  • 電子工学および電気工学
  • 材料化学
  • 凝縮系物理学

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