Chaos and relaxation oscillations in spin-torque windmill neurons
Rie Matsumoto, Steven Lequeux, Hiroshi Imamura, and Julie Grollier

TL;DR
This paper introduces a novel spintronic neuron design that mimics biological spiking behavior and exhibits tunable chaotic oscillations, advancing hardware neuromorphic computing with nanoscale magnetic devices.
Contribution
It proposes a simple method to generate neuron-like spikes and chaos in spin-torque nano-oscillators using windmill motion in spin valves, enabling neuromorphic hardware applications.
Findings
Spin-torque windmill motion produces tunable voltage spikes.
Chaotic oscillations can be controlled via magnetic stack engineering.
Device behavior is adjustable through dc current and magnetic anisotropies.
Abstract
Spintronic neurons which emit sharp voltage spikes are required for the realization of hardware neural networks enabling fast data processing with low-power consumption. In many neuroscience and computer science models, neurons are abstracted as non-linear oscillators. Magnetic nano-oscillators called spin-torque nano-oscillators are interesting candidates for imitating neurons at nanoscale. These oscillators, however, emit sinusoidal waveforms without spiking while biological neurons are relaxation oscillators that emit sharp voltage spikes. Here we propose a simple way to imitate neuron spiking in high-magnetoresistance nanoscale spin valves where both magnetic layers are free and thin enough to be switched by spin torque. Our numerical-simulation results show that the windmill motion induced by spin torque in the proposed spintronic neurons gives rise to spikes whose shape and…
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