1. A spintronic Huxley-Hodgkin-analogue neuron implemented with a single magnetic tunnel junction
- Author
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Rodrigues, Davi R., Moukhader, Rayan, Luo, Yanxiang, Fang, Bin, Pontlevy, Adrien, Hamadeh, Abbas, Zeng, Zhongming, Carpentieri, Mario, and Finocchio, Giovanni
- Subjects
Condensed Matter - Mesoscale and Nanoscale Physics - Abstract
Spiking neural networks aim to emulate the brain's properties to achieve similar parallelism and high-processing power. A caveat of these neural networks is the high computational cost to emulate, while current proposals for analogue implementations are energy inefficient and not scalable. We propose a device based on a single magnetic tunnel junction to perform neuron firing for spiking neural networks without the need of any resetting procedure. We leverage two physics, magnetism and thermal effects, to obtain a bio-realistic spiking behavior analogous to the Huxley-Hodgkin model of the neuron. The device is also able to emulate the simpler Leaky-Integrate and Fire model. Numerical simulations using experimental-based parameters demonstrate firing frequency in the MHz to GHz range under constant input at room temperature. The compactness, scalability, low cost, CMOS-compatibility, and power efficiency of magnetic tunnel junctions advocate for their broad use in hardware implementations of spiking neural networks., Comment: 23 pages, 6 figures, 2 tables
- Published
- 2023