Affiliation:
1. College of Information Science and Electronic Engineering Zhejiang University Hangzhou 310027 P. R. China
2. School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu 610054 P. R. China
3. Artificial Intelligence Institute China Electronics Technology Group Corporation Beijing 100086 P. R. China
4. School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 610054 P. R. China
Abstract
AbstractPhotonic neural networks (PNNs) show tremendous potential for artificial intelligence applications due to their higher computational rates than their traditional electronic counterpart. However, the scale‐up of PNN relies on the number of cascaded computing units, which is limited by the accumulated transmission attenuation. Here, a topology of PNN with Mach–Zehnder interferometers based on a single‐tuned phase shifter that implements arbitrary nonnegative or real‐valued matrices for vector‐matrix multiplication is proposed. Compared with the universal matrix mesh, the new configuration exhibits two orders of magnitude lower optical path loss and a twofold reduction in the number of the tunable phase shifter. An 8 × 8 reconfigurable chip is designed and fabricated, and it is experimentally verified that the 2 × 4 nonnegative‐valued matrix and the 2 × 2 real‐valued matrix are implemented in the proposed topology. Higher than 85% inference accuracies are obtained in the Modified National Institute of Standards and Technology handwritten digit recognition tasks with these matrices in the PNNs. Therefore, with much lower optical path loss and comparable computing accuracy, the proposed PNN configuration can be easily scaled up to tackle higher dimensional matrix multiplication, which is highly desired in tasks like voice and image recognition.
Funder
National Natural Science Foundation of China
Subject
Condensed Matter Physics,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials
Cited by
4 articles.
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