Passive frustrated nanomagnet reservoir computing

no code implementations • 16 Mar 2021 • Alexander J. Edwards, Dhritiman Bhattacharya, Peng Zhou, Nathan R. McDonald, Walid Al Misba, Lisa Loomis, Felipe Garcia-Sanchez, Naimul Hassan, Xuan Hu, Md. Fahim Chowdhury, Clare D. Thiem, Jayasimha Atulasimha, Joseph S. Friedman

We therefore propose a reservoir that meets all of these criteria by leveraging the passive interactions of dipole-coupled, frustrated nanomagnets.

Edge-computing

Reservoir Computing with Planar Nanomagnet Arrays

no code implementations • 24 Mar 2020 • Peng Zhou, Nathan R. McDonald, Alexander J. Edwards, Lisa Loomis, Clare D. Thiem, Joseph S. Friedman

Reservoir computing is an emerging methodology for neuromorphic computing that is especially well-suited for hardware implementations in size, weight, and power (SWaP) constrained environments.