Reservoir Computing with Spin Waves in a Skyrmion Crystal

Magnetic skyrmions are nanometric spin textures characterized by a quantized topological invariant in magnets and often emerge in a crystallized form called a skyrmion crystal in an external magnetic field. We propose that magnets hosting a skyrmion crystal possess high potential for application to reservoir computing, which is one of the most successful information processing techniques inspired by functions of the human brain. Our skyrmion-based reservoir exploits precession dynamics of magnetizations, i.e., spin waves, propagating in the skyrmion crystal. Because of complex interferences and slow relaxations of the spin-wave dynamics, the skyrmion spin-wave reservoir attains several important characteristics required for reservoir computing, e.g., the generalization ability, nonlinearity, and short-term memory. We investigate these properties by imposing three standard tasks to test the performance of the reservoir, i.e., the duration-estimation task, short-term memory task, and parity-check task. Through these investigations, we demonstrate that magnetic skyrmion crystals are promising materials for spintronics reservoir devices. Because magnetic skyrmions emerge spontaneously in magnets via a self-organization process under application of a static magnetic field, the proposed skyrmion reservoir requires neither advanced nanofabrication nor complicated manufacturing for production, in contrast to other previously proposed magnetic reservoirs constructed with fabricated spintronics devices. Our proposal is expected to realize a breakthrough in the research of spintronics reservoirs of high performance.