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On-chip phonon-magnon reservoir for neuromorphic computing

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journal contribution
posted on 2023-12-15, 12:04 authored by Dmytro D Yaremkevich, Alexey V Scherbakov, Luke De Clerk, Serhii M Kukhtaruk, Achim Nadzeyka, Richard Campion, Andrew W Rushforth, Sergey SavelievSergey Saveliev, Alexander BalanovAlexander Balanov, Manfred Bayer

Reservoir computing is a concept involving mapping signals onto a high-dimensional phase space of a dynamical system called “reservoir” for subsequent recognition by an artificial neural network. We implement this concept in a nanodevice consisting of a sandwich of a semiconductor phonon waveguide and a patterned ferromagnetic layer. A pulsed write-laser encodes input signals into propagating phonon wavepackets, interacting with ferromagnetic magnons. The second laser reads the output signal reflecting a phase-sensitive mix of phonon and magnon modes, whose content is highly sensitive to the write- and read-laser positions. The reservoir efficiently separates the visual shapes drawn by the write-laser beam on the nanodevice surface in an area with a size comparable to a single pixel of a modern digital camera. Our finding suggests the phonon-magnon interaction as a promising hardware basis for realizing on-chip reservoir computing in future neuromorphic architectures.

History

School

  • Science

Department

  • Physics

Published in

Nature Communications

Volume

14

Publisher

Springer Nature

Version

  • VoR (Version of Record)

Rights holder

© The Author(s)

Publisher statement

This is an Open Access Article. It is published by Springer Nature under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/

Acceptance date

2023-11-22

Publication date

2023-12-14

Copyright date

2023

eISSN

2041-1723

Language

  • en

Depositor

Dr Alexander Balanov. Deposit date: 15 December 2023

Article number

8296

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