Litcius/Paper detail

Spintronic reservoir computing without driving current or magnetic field

Tomohiro Taniguchi, Amon Ogihara, Yasuhiro Utsumi, Sumito Tsunegi

2022Scientific Reports42 citationsDOIOpen Access PDF

Abstract

Recent studies have shown that nonlinear magnetization dynamics excited in nanostructured ferromagnets are applicable to brain-inspired computing such as physical reservoir computing. The previous works have utilized the magnetization dynamics driven by electric current and/or magnetic field. This work proposes a method to apply the magnetization dynamics driven by voltage control of magnetic anisotropy to physical reservoir computing, which will be preferable from the viewpoint of low-power consumption. The computational capabilities of benchmark tasks in single MTJ are evaluated by numerical simulation of the magnetization dynamics and found to be comparable to those of echo-state networks with more than 10 nodes.

Topics & Concepts

Magnetization dynamicsMagnetizationSpintronicsComputer scienceCondensed matter physicsBenchmark (surveying)Nonlinear systemMagnetic fieldMagnetic anisotropyFerromagnetismPhysicsStatistical physicsGeologyQuantum mechanicsGeodesyNeural Networks and Reservoir ComputingAdvanced Memory and Neural ComputingNeural Networks and Applications