3 papers
cs.ET2026
Power law scaling for classification accuracy in physical neural networks
Andrei V. Ermolaev, Mathilde Hary, Anas Skalli +7
Physical neural networks (PNNs) harness the intrinsic complexity of physical systems to perform neural computation, potentially at speeds and energy efficiencies inaccessible to co…
physics.optics2025
Principles and Metrics of Extreme Learning Machines Using a Highly Nonlinear Fiber
Mathilde Hary, Daniel Brunner, Lev Leybov +3
Optical computing offers potential for ultra high-speed and low latency computation by leveraging the intrinsic properties of light. Here, we explore the use of highly nonlinear op…
physics.optics2025
Limits of nonlinear and dispersive fiber propagation for an optical fiber-based extreme learning machine
Andrei V. Ermolaev, Mathilde Hary, Lev Leybov +5
We report a generalized nonlinear Schrödinger equation simulation model of an extreme learning machine (ELM) based on optical fiber propagation. Using the MNIST handwritten digit…