Image classification with a fully connected opto-electronic neural network

¹ Max Planck Institute for Medical Research, Jahnstraße 29, 69120 Heidelberg
² Institute for Molecular Systems Engineering and Advanced Materials, Universität Heidelberg, Neuenheimer Feld 225, 69120 Heidel-berg
^† Equal Contribution

^* e-mail: alexander.song@mr.mpg.de
^** e-mail: nikhilesh.kottapalli@mr.mpg.de
^*** e-mail: peer.fischer@mr.mpg.de

Published online: 18 October 2023

Abstract

Optical approaches have made great strides enabling high-speed, scalable computing necessary for modern deep learning and AI applications. In this study, we introduce a multilayer optoelectronic computing framework that alternates between optical and optoelectronic layers to implement matrix-vector multiplications and rectified linear functions, respectively. The system is designed to be real-time and parallelized, utilizing arrays of light emitters and detectors connected with independent analog electronics. We experimentally demonstrate the operation of our system and compare its performance to a single-layer analog through simulations.