3D Spin Textures for Reconfigurable Magnonics and Neuromorphic Computing

SPICE Workshop on Nanomagnetism in 3D, April 30th - May 2nd 2024

Will Branford

Strongly-interacting nanomagnetic textures are ideal for exploring reconfigurable magnonics and neuromorphic computing using the spin-wave spectrum as a readout1. These systems may be broadly assessed by their range of reliably accessible states and the strength of magnon coupling phenomena and nonlinearities. Increasingly, nanomagnetic systems are expanding into three-dimensional architectures. This has enhanced the range of available magnetic microstates and functional behaviours, but engineering control over 3D states and dynamics remains challenging.
Our initial studies were in planar artificial spin ice nanostructures2. Here, we will show how going into 3D can increase the richness of the GHz spectrum and the strength of the coupling effects, using two systems as case studies, a multilayered ASI and a Skyrmion thin film.
The 3D-ASI Comprises two magnetic layers separated by a non-magnetic spacer, each nanoisland may assume four macrospin or vortex states per magnetic layer. This creates a system with a rich 16N microstate space and intense static and dynamic dipolar magnetic coupling3.
The Skyrmion films are the chiral magnets Cu2OSeO3 and Co8.5Zn8.5Mn3, that hosts Skyrmion, conical and helical magnetic phases. Crossing the phase boundaries provides on-demand access to different computational reservoir responses4.

1 Vanstone, A., Gartside, J. C., Stenning, K. D., Dion, T., Arroo, D. M. & Branford, W. R. Spectral fingerprinting: microstate readout via remanence ferromagnetic resonance in artificial spin ice. New Journal of Physics 24, 043017 (2022).
2 Gartside, J. C., Stenning, K. D., Vanstone, A., Holder, H. H., Arroo, D. M., Dion, T., Caravelli, F., Kurebayashi, H. & Branford, W. R. Reconfigurable training and reservoir computing in an artificial spin-vortex ice via spin-wave fingerprinting. Nat Nanotechnol 17, 460-+ (2022).
3 Troy Dion, K. D. S., Alex Vanstone, Holly H. Holder, Rawnak Sultana, Ghanem Alatteili, Victoria Martinez, Mojtaba Taghipour Kaffash, Takashi Kimura, Rupert Oulton, Hidekazu Kurebayashi, Will R. Branford, Ezio Iacocca, Benjamin M. Jungfleisch, Jack C. Gartside. Dipolar Ultrastrong Magnon-Magnon Coupling in a 3D Multilayered Artificial Spin-Vortex Ice. arXiv:2306.16159 (2024).
4 Lee, O., Wei, T., Stenning, K. D., Gartside, J. C., Prestwood, D., Seki, S., Aqeel, A., Karube, K., Kanazawa, N., Taguchi, Y., Back, C., Tokura, Y., Branford, W. R. & Kurebayashi, H. Task-adaptive physical reservoir computing. Nat. Mater. 23, 79-87 (2024).