4 papers
Graph-theoretic design of lasing networks for physical vision
Paul Obernolte, Jakub Dranczewski, Yixiu Yin +10
Physical neural networks perform learning through the intrinsic nonlinear dynamics of matter. Optimising their design presents a considerable challenge: complex many-body physics c…
Low-power analogue neural networks with trainable nonlinear connections for continuous control
Ian T. Vidamour, Fernando Aguirre, Thomas J. Hayward +13
Physical neural networks promise low-power machine learning by computing directly with analogue device physics, but most architectures force nonlinear device responses to act as sc…
Metrics for spin-based computing
Hidekazu Kurebayashi, Giovanni Finocchio, Karin Everschor-Sitte +10
Spin-based computing is emerging as a powerful approach for energy-efficient and high-performance solutions to future data processing hardware. Spintronic devices function by elect…
Light-Driven Skyrmion Crystal Generation in Plasmonic Metasurfaces Through the Inverse Faraday Effect
Xingyu Yang, Chantal Hareau, Tristan da Câmara Santa Clara Gomes +2
Skyrmions are topological structures defined by a winding vector configuration that yields a quantized topological charge. In magnetic materials, skyrmions manifest as stable, mobi…