Yaremkevich, Dmytro D.Scherbakov, Alexey V.De Clerk, LukeKukhtaruk, Serhii M.Nadzeyka, AchimCampion, RichardRushforth, Andrew W.Savel'ev, SergeyBalanov, Alexander G.Bayer, Manfred2024-04-082024-04-082023-12-14http://hdl.handle.net/2003/42427http://dx.doi.org/10.17877/DE290R-24263Reservoir 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.enFerromagnetismInformation technologySurfaces, interfaces and thin films530Text