Voltage-Controlled Domain Wall Motion-Based Neuron and Stochastic Magnetic Tunnel Junction Synapse for Neuromorphic Computing Applications

Abstract

This work discusses the proposal of a spintronic neuromorphic system with spin orbit torque-driven domain wall motion (DWM)-based neurons and synapses. We propose a voltage-controlled magnetic anisotropy DWM-based magnetic tunnel junction (MTJ) neuron. We investigate how the electric field at the gate (pinning site), generated by the voltage signals from pre-neurons, modulates the DWM, which reflects in the nonlinear switching behavior of neuron magnetization. For the implementation of synaptic weights, we propose a 3-terminal MTJ with stochastic DWM in the free layer. We incorporate intrinsic pinning effects by creating triangular notches on the sides of the free layer. The pinning of the domain wall and intrinsic thermal noise of the device lead to the stochastic behavior of DWM. The control of this stochasticity by the spin orbit torque is shown to realize the potentiation and depression of the synaptic weight. The micromagnetics and spin transport studies in synapses and neurons are carried out by developing a coupled micromagnetic non-equilibrium Green’s function (MuMag-NEGF) model. The minimization of the writing current pulsewidth by leveraging the thermal noise and demagnetization energy is also presented. Finally, we discuss the implementation of digit recognition by the proposed system using a spike time-dependent algorithm.

Keywords

• Domain wall motion (DWM)
• magnetic tunnel junction (MTJ)
• neuromorphic computing
• pattern recognition
• spin orbit torque
• thermal effects