Imperial College London
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ProfessorWillBranford

Faculty of Natural Sciences, Department of Physics

Professor of Solid State Physics
 
 
 
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Contact

 

+44 (0)20 7594 6674w.branford Website

 
 
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Location

 

912Blackett LaboratorySouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Lee:2024:10.1038/s41563-023-01698-8,
author = {Lee, O and Wei, T and Stenning, KD and Gartside, JC and Prestwood, D and Seki, S and Aqeel, A and Karube, K and Kanazawa, N and Taguchi, Y and Back, C and Tokura, Y and Branford, WR and Kurebayashi, H},
doi = {10.1038/s41563-023-01698-8},
journal = {Nature Materials},
pages = {79--87},
title = {Task-adaptive physical reservoir computing},
url = {http://dx.doi.org/10.1038/s41563-023-01698-8},
volume = {23},
year = {2024}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Reservoir computing is a neuromorphic architecture that may offer viable solutions to the growing energy costs of machine learning. In software-based machine learning, computing performance can be readily reconfigured to suit different computational tasks by tuning hyperparameters. This critical functionality is missing in 'physical' reservoir computing schemes that exploit nonlinear and history-dependent responses of physical systems for data processing. Here we overcome this issue with a 'task-adaptive' approach to physical reservoir computing. By leveraging a thermodynamical phase space to reconfigure key reservoir properties, we optimize computational performance across a diverse task set. We use the spin-wave spectra of the chiral magnet Cu2OSeO3 that hosts skyrmion, conical and helical magnetic phases, providing on-demand access to different computational reservoir responses. The task-adaptive approach is applicable to a wide variety of physical systems, which we show in other chiral magnets via above (and near) room-temperature demonstrations in Co8.5Zn8.5Mn3 (and FeGe).
AU  - Lee,O
AU  - Wei,T
AU  - Stenning,KD
AU  - Gartside,JC
AU  - Prestwood,D
AU  - Seki,S
AU  - Aqeel,A
AU  - Karube,K
AU  - Kanazawa,N
AU  - Taguchi,Y
AU  - Back,C
AU  - Tokura,Y
AU  - Branford,WR
AU  - Kurebayashi,H
DO  - 10.1038/s41563-023-01698-8
EP  - 87
PY  - 2024///
SN  - 1476-1122
SP  - 79
TI  - Task-adaptive physical reservoir computing
T2  - Nature Materials
UR  - http://dx.doi.org/10.1038/s41563-023-01698-8
UR  - https://www.ncbi.nlm.nih.gov/pubmed/37957266
UR  - https://www.nature.com/articles/s41563-023-01698-8
UR  - http://hdl.handle.net/10044/1/107818
VL  - 23
ER  -
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