On-chip phonon-magnon reservoir for neuromorphic computing

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

Giant photoelasticity of polaritons for detection of coherent phonons in a superlattice with quantum sensitivity

The functionality of phonon-based quantum devices largely depends on the efficiency of interaction of phonons with other excitations. For phonon frequencies above 20 GHz, generation and detection of the phonon quanta can be monitored through photons. The photon-phonon interaction can be enormously strengthened by involving an intermediate resonant quasiparticle, e.g. an exciton, with which a photon forms a polariton. In this work, we discover a giant photoelasticity of exciton-polaritons in a short-period superlattice and exploit it for detecting propagating acoustic phonons. We demonstrate that 42 GHz coherent phonons can be detected with extremely high sensitivity in the time domain Brillouin oscillations by probing with photons in the spectral vicinity of the polariton resonance.Comment: 6 pages, 3 figures, Supplemental Material

On-chip phonon-magnon reservoir for neuromorphic computing

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 ferro-magnetic 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 neuro-morphic architectures

Coherent Phononics of van der Waals Layers on Nanogratings

Strain engineering can be used to control the physical properties of two-dimensional van der Waals (2D-vdW) crystals. Coherent phonons, which carry dynamical strain, could push strain engineering to control classical and quantum phenomena in the unexplored picosecond temporal and nanometer spatial regimes. This intriguing approach requires the use of coherent GHz and sub-THz 2D phonons. Here, we report on nanostructures that combine nanometer thick vdW layers and nanogratings. Using an ultrafast pump-probe technique, we generate and detect in-plane coherent phonons with frequency up to 40 GHz and hybrid flexural phonons with frequency up to 10 GHz. The latter arises from the periodic modulation of the elastic coupling of the vdW layer at the grooves and ridges of the nanograting. This creates a new type of a tailorable 2D periodic phononic nanoobject, a flexural phononic crystal, offering exciting prospects for the ultrafast manipulation of states in 2D materials in emerging quantum technologies

Protected Long-Distance Guiding of Hypersound Underneath a Nanocorrugated Surface

In nanoscale communications, high-frequency surface acoustic waves are becoming effective data carriers and encoders. On-chip communications require acoustic wave propagation along nanocorrugated surfaces which strongly scatter traditional Rayleigh waves. Here, we propose the delivery of information using subsurface acoustic waves with hypersound frequencies of ∼20 GHz, which is a nanoscale analogue of subsurface sound waves in the ocean. A bunch of subsurface hypersound modes are generated by pulsed optical excitation in a multilayer semiconductor structure with a metallic nanograting on top. The guided hypersound modes propagate coherently beneath the nanograting, retaining the surface imprinted information, at a distance of more than 50 μm which essentially exceeds the propagation length of Rayleigh waves. The concept is suitable for interfacing single photon emitters, such as buried quantum dots, carrying coherent spin excitations in magnonic devices and encoding the signals for optical communications at the nanoscale

Supplementary information files for On-chip phonon-magnon reservoir for neuromorphic computing

© the authors, CC-BY 4.0Supplementary files for article On-chip phonon-magnon reservoir for neuromorphic computingReservoir 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.</p

On-chip phonon-magnon reservoir for neuromorphic computing

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.</p