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Nonlinear phenomena in physical systems can be used for brain-inspiredcomputing with low energy consumption. Response from the dynamics of atopological spin structure called skyrmion is one of the candidates for such aneuromorphic computing. However, its ability has not been well exploredexperimentally. Here, we experimentally demonstrate neuromorphic computingusing nonlinear response originating from magnetic-field induced dynamics ofskyrmions. We designed a simple-structured skyrmion-based neuromorphic deviceand succeeded in handwritten digit recognition with the accuracy as large as94.7 % and waveform recognition. Notably, there exists a positive correlationbetween the recognition accuracy and the number of skyrmions in the devices.The large degree of freedoms of skyrmion systems, such as the position and thesize, originate the more complex nonlinear mapping and the larger outputdimension, and thus high accuracy. Our results provide a guideline fordeveloping energy-saving and high-performance skyrmion neuromorphic computingdevices.

Pattern recognition with neuromorphic computing using magnetic-field induced dynamics of skyrmions