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Handwritten digit recognition by spin waves in a Skyrmion reservoir

Mu-Kun Lee, Masahito Mochizuki

2023Scientific Reports23 citationsDOIOpen Access PDF

Abstract

By performing numerical simulations for the handwritten digit recognition task, we demonstrate that a magnetic skyrmion lattice confined in a thin-plate magnet possesses high capability of reservoir computing. We obtain a high recognition rate of more than 88%, higher by about 10% than a baseline taken as the echo state network model. We find that this excellent performance arises from enhanced nonlinearity in the transformation which maps the input data onto an information space with higher dimensions, carried by interferences of spin waves in the skyrmion lattice. Because the skyrmions require only application of static magnetic field instead of nanofabrication for their creation in contrast to other spintronics reservoirs, our result consolidates the high potential of skyrmions for application to reservoir computing devices.

Topics & Concepts

SkyrmionReservoir computingSpintronicsLattice (music)Computer scienceMagnetNonlinear systemNumerical digitCondensed matter physicsPhysicsAcousticsArtificial intelligenceRecurrent neural networkArtificial neural networkMathematicsFerromagnetismQuantum mechanicsArithmeticNeural Networks and Reservoir ComputingAdvanced Memory and Neural ComputingMagnetic properties of thin films
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