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The quest for highly efficient cognitive computing has led to extensiveresearch interest for the field of neuromorphic computing. Neuromorphiccomputing aims to mimic the behavior of biological neurons and synapses usingsolid-state devices and circuits. Among various approaches, emergingnon-volatile memory technologies are of special interest for mimickingneuro-synaptic behavior. These devices allow the mapping of the rich dynamicsof biological neurons and synapses onto their intrinsic device physics. In thisletter, we focus on Spike Timing Dependent Plasticity (STDP) behavior ofbiological synapses and propose a method to implement the STDP behavior inMagnetic Tunnel Junction (MTJ) devices. Specifically, we exploit thetime-dependent heat dynamics and the response of an MTJ to the instantaneoustemperature to imitate the STDP behavior. Our simulations, based on amacro-spin model for magnetization dynamics, show that, STDP can be imitated instochastic magnetic tunnel junctions by applying simple voltage waveforms asthe spiking response of pre- and post-neurons across an MTJ device.

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