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Perspective on 3D vertically-integrated photonic neural networks based on VCSEL arrays

Authors :
Gu, Min
Dong, Yibo
Yu, Haoyi
Luan, Haitao
Zhang, Qiming
Source :
Nano-photonics; October 2022, Vol. 12 Issue: 5 p827-832, 6p
Publication Year :
2022

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.

Details

Language :
English
ISSN :
21928606 and 21928614
Volume :
12
Issue :
5
Database :
Supplemental Index
Journal :
Nano-photonics
Publication Type :
Periodical
Accession number :
ejs62456257
Full Text :
https://doi.org/10.1515/nanoph-2022-0437