Intrinsic Spike Timing Dependent Plasticity in Stochastic Magnetic Tunnel Junctions Mediated by Heat Dynamics

TL;DR

This paper demonstrates how stochastic magnetic tunnel junctions can emulate spike timing dependent plasticity (STDP) by leveraging heat dynamics and voltage waveforms, advancing neuromorphic computing hardware.

Contribution

It introduces a novel method to implement STDP in MTJ devices using heat dynamics and voltage waveforms, bridging device physics with neuromorphic functionality.

Findings

STDP behavior can be simulated in MTJs using heat dynamics.

Voltage waveforms effectively induce STDP in stochastic MTJs.

Simulation results validate the proposed approach.

Abstract

The quest for highly efficient cognitive computing has led to extensive research interest for the field of neuromorphic computing. Neuromorphic computing aims to mimic the behavior of biological neurons and synapses using solid-state devices and circuits. Among various approaches, emerging non-volatile memory technologies are of special interest for mimicking neuro-synaptic behavior. These devices allow the mapping of the rich dynamics of biological neurons and synapses onto their intrinsic device physics. In this letter, we focus on Spike Timing Dependent Plasticity (STDP) behavior of biological synapses and propose a method to implement the STDP behavior in Magnetic Tunnel Junction (MTJ) devices. Specifically, we exploit the time-dependent heat dynamics and the response of an MTJ to the instantaneous temperature to imitate the STDP behavior. Our simulations, based on a macro-spin model for magnetization dynamics, show that, STDP can be imitated in stochastic magnetic tunnel junctions by applying simple voltage waveforms as the spiking response of pre- and post-neurons across an MTJ device.