2020/06/30 by M. Leonetti, Marco Leonetti, Erik Hormann +7
Computer Science · Neuroscience · Physics and Astronomy · #Algorithm #Computation #Computer science #Neural Networks and Reservoir Computing #Neural dynamics and brain function #Optics #Phenomenology (philosophy) #Physics #Random lasers and scattering media #Relaxation (psychology) #Scattering #Spin (aerodynamics) #Statistical physics #cond-mat.dis-nn #msc:68W20 #msc:78-05 #physics.comp-ph #physics.optics
paper · pdf · doi:10.1073/pnas.2015207118
published as PNAS May 25, 2021 118 (21) e2015207118
arxiv created 2020/07/01 · openalex publication_date 2021/05/21 · arxiv updated 2021/07/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
segments of a wavefront-shaping device to play the role of the spin variables, combining the interference downstream of a scattering material to implement the random couplings between the spins (the [Formula: see text] matrix) and measuring the light intensity on a number P of targets to retrieve the energy of the system. By implementing a plain Metropolis algorithm, we are able to simulate the spin model dynamics, while the degree of complexity of the potential energy landscape and the region of phase diagram explored are user defined, acting on the ratio [Formula: see text] We study experimentally, numerically, and analytically this Hopfield-like system displaying a paramagnetic, ferromagnetic, and SG phase, and we demonstrate that the transition temperature [Formula: see text] to the glassy phase from the paramagnetic phase grows with α. We demonstrate the computational advantage of the optical SG where interaction terms are realized simultaneously when the independent light rays interfere on the detector's surface. This inherently parallel measurement of the energy provides a speedup with respect to purely in silico simulations scaling with N.