190 citations · 687 across the 27 of their papers we have counts for
29 papers
Enhanced Magneto-Optical Kerr Effect in Nano-Magnetic Metamaterials with Near-Perfect Coherent Absorption
Xiaofei Xiao, Tingjun Zheng, Alex Vanstone +6
The ability to control magnetic systems without external magnetic fields has attracted attention recently, with all-optical magnetic switching showing increasing promise. Gaining f…
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…
Magnetoelastic coupling in stripe-domain states of yttrium iron garnet
Nimisha Arora, Daniel Prestwood, Takashi Kikkawa +4
We study magnetoelastic coupling in stripe-domain magnetic states of -thick YIG thin films grown on a GGG substrate. Broadband ferromagnetic resonance reveals low-f…
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…
Learning Nonlinear Heterogeneity in Physical Kolmogorov-Arnold Networks
Fabiana Taglietti, Andrea Pulici, Maxwell Roxburgh +10
Physical neural networks typically train linear synaptic weights while treating device nonlinearities as fixed. We show the opposite - by training the synaptic nonlinearity itself,…
Spin wave resonance in yttrium iron garnet stripe domains
Daniel Prestwood, Chris E. A. Barker, Kilian D. Stenning +15
We study a thin film yttrium iron garnet sample that exhibits magnetic stripe domains due to a small perpendicular magnetic anisotropy. Using wide-field magneto-optic Kerr effect m…