  Nonlinear phenomena in physical systems can be used for brain-inspired
computing with low energy consumption. Response from the dynamics of a
topological spin structure called skyrmion is one of the candidates for such a
neuromorphic computing. However, its ability has not been well explored
experimentally. Here, we experimentally demonstrate neuromorphic computing
using nonlinear response originating from magnetic-field induced dynamics of
skyrmions. We designed a simple-structured skyrmion-based neuromorphic device
and succeeded in handwritten digit recognition with the accuracy as large as
94.7 % and waveform recognition. Notably, there exists a positive correlation
between the recognition accuracy and the number of skyrmions in the devices.
The large degree of freedoms of skyrmion systems, such as the position and the
size, originate the more complex nonlinear mapping and the larger output
dimension, and thus high accuracy. Our results provide a guideline for
developing energy-saving and high-performance skyrmion neuromorphic computing
devices.
