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Integrating magnetic skyrmion properties into neuromorphic computing promisesadvancements in hardware efficiency and computational power. However, ascalable implementation of the weighted sum of neuron signals, a core operationin neural networks, has yet to be demonstrated. In this study, we exploit thenon-volatile and particle-like characteristics of magnetic skyrmions, akin tosynaptic vesicles and neurotransmitters, to perform this weighted sum operationin a compact, biologically-inspired manner. To this aim, skyrmions areelectrically generated in numbers proportional to the input with an efficiencygiven by a non-volatile weight. These chiral particles are then directed usinglocalized current injections to a location where their presence is quantifiedthrough non-perturbative electrical measurements. Our experimentaldemonstration, currently with two inputs, can be scaled to accommodate multipleinputs and outputs using a crossbar array design, potentially nearing theenergy efficiency observed in biological systems.

Neuromorphic weighted sum with magnetic skyrmions