Reservoir Computing with Spin Waves in a Skyrmion Crystal
Mu-Kun Lee, Masahito Mochizuki
Abstract
The application of spintronics to physical reservoir computing has great potential, but development still suffers from inevitable technical complications in nanofabrication. This numerical study considers spin waves excited in a self-organized skyrmion lattice under a magnetic field in a chiral magnet---which would not require advanced manufacturing in practice---to make progress on the problem. Such a skyrmion lattice offers great levels of generalizability, memory capacity, and nonlinearity, fulfilling the fundamental requirements of reservoir computing. The results will promote engineering solutions to pave the way toward reliable, energy-conserving reservoir computing.
Topics & Concepts
SkyrmionSpintronicsGeneralizability theoryNonlinear systemLattice (music)Excited stateMagnetMagnetic fieldComputer scienceFerromagnetismPhysicsCondensed matter physicsQuantum mechanicsMathematicsAcousticsStatisticsNeural Networks and Reservoir ComputingAdvanced Memory and Neural ComputingNeural Networks and Applications