  Spin waves propagating through a stripe domain structure and reservoir
computing with their spin dynamics have been numerically studied with focusing
on the relation between physical phenomena and computing capabilities. Our
system utilizes a spin-wave-based device that has a continuous magnetic garnet
film and 1-input/72-output electrodes on the top. To control
spatially-distributed spin dynamics, a stripe magnetic domain structure and
amplitude-modulated triangular input waves were used. The spatially-arranged
electrodes detected spin vector outputs with various nonlinear characteristics
that were leveraged for reservoir computing. By moderately suppressing
nonlinear phenomena, our system achieves 100$\%$ prediction accuracy in
temporal exclusive-OR (XOR) problems with a delay step up to 5. At the same
time, it shows perfect inference in delay tasks with a delay step more than 7
and its memory capacity has a maximum value of 21. This study demonstrated that
our spin-wave-based reservoir computing has a high potential for edge-computing
applications and also can offer a rich opportunity for further understanding of
the underlying nonlinear physics.
