Perspective on 3D vertically-integrated photonic neural networks based on VCSEL arrays
Author:
Gu Min12ORCID, Dong Yibo12, Yu Haoyi12, Luan Haitao12, Zhang Qiming12
Affiliation:
1. Institute of Photonic Chips, University of Shanghai for Science and Technology , Shanghai 200093 China 2. Centre for Artificial-Intelligence Nanophotonics, School of Optical-Electrical and Computer Engineering , University of Shanghai for Science and Technology , Shanghai 200093 China
Abstract
Abstract
The rapid development of artificial intelligence has stimulated the interest in the novel designs of photonic neural networks. As three-dimensional (3D) neural networks, the diffractive neural networks (DNNs) relying on the diffractive phenomena of light, has demonstrated their superb performance in the direct parallel processing of two-dimensional (2D) optical data at the speed of light. Despite the outstanding achievements, DNNs utilize centimeter-scale devices to generate the input data passively, making the miniaturization and on-chip integration of DNNs a challenging task. Here, we provide our perspective on utilizing addressable vertical-cavity surface-emitting laser (VCSEL) arrays as a promising data input device and integrated platform to achieve compact, active DNNs for next-generation on-chip vertical-stacked photonic neural networks. Based on the VCSEL array, micron-scale 3D photonic chip with a modulation bandwidth at tens of GHz can be available. The possible future directions and challenges of the 3D photonic chip are analyzed.
Funder
Shanghai Municipal Science and Technology Major Project, Shanghai Frontiers Science Center Program National Key Research and Development program of China Science and Technology Commission of Shanghai Municipality National Natural Science Foundation of China
Publisher
Walter de Gruyter GmbH
Subject
Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials,Biotechnology
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