On-chip phonon-magnon reservoir for neuromorphic computing.
Dmytro D Yaremkevich, Alexey V Scherbakov, Luke De Clerk, Serhii M Kukhtaruk, Achim Nadzeyka, Richard Campion, Andrew W Rushforth, Sergey Savel'ev, Alexander G Balanov, Manfred Bayer
Author Information
Dmytro D Yaremkevich: Experimentelle Physik 2, Technische Universität Dortmund, D-44227, Dortmund, Germany.
Alexey V Scherbakov: Experimentelle Physik 2, Technische Universität Dortmund, D-44227, Dortmund, Germany. alexey.shcherbakov@tu-dortmund.de. ORCID
Luke De Clerk: Department of Physics, Loughborough University, Loughborough, LE11 3TU, UK. ORCID
Serhii M Kukhtaruk: Department of Theoretical Physics, V. E. Lashkaryov Institute of Semiconductor Physics, 03028, Kyiv, Ukraine. ORCID
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.
