Abstract

We demonstrate associative memory operations reminiscent of the brain using nonvolatile spintronics devices. Antiferromagnet–ferromagnet bilayer-based Hall devices, which show analogue-like spin–orbit torque switching under zero magnetic fields and behave as artificial synapses, are used. An artificial neural network is used to associate memorized patterns from their noisy versions. We develop a network consisting of a field-programmable gate array and 36 spin–orbit torque devices. An effect of learning on associative memory operations is successfully confirmed for several 3 × 3-block patterns. A discussion on the present approach for realizing spintronics-based artificial intelligence is given.

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