Photonic neuromorphic computing using symmetry-protected zero modes in coupled nanolaser arrays.

ABSTRACT: Photonic neuromorphic computing has emerged as a promising approach toward energy-efficient artificial neural networks (ANN). Nanolasers, in particular, have become attractive candidates due to their ultra-low power consumption and intrinsic nonlinear characteristics. In this work, we propose a photonic neuromorphic computing architecture based on symmetry-protected robust zero modes at the center of the optical spectrum in coupled semiconductor nanolaser arrays. We experimentally demonstrate that even a small set of coupled nanolasers inherently provides non-convex classification capabilities, enabling it to solve non-trivial classification tasks. As a benchmark, we show that a 2 × 2 nanolaser array, acting as a hidden nonlinear layer with recurrent coupling is able to solve the XNOR logi

SUBMITTER: Ji K 

PROVIDER: S-EPMC12533018 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature