Vol. 54, Issue 1, pp. 5-13

Vol. 54 Issue 1 pp. 5-13

Design of a photonic unitary neural network based on MZI arrays

Ye Zhang, Ruiting Wang, Yejin Zhang, Yanmei Su, Pengfei Wang, Guangzhen Luo, Xuliang Zhou, Jiaoqing Pan

Keywords

optical neural network, unitary matrix, Mach–Zehnder interferometer

Abstract

In recent years, optical neural networks have attracted widespread attention, due to their advantages of high speed, high parallelism, high bandwidth, and low power consumption. Photonic unitary neural network is a kind of neural networks that utilize the principles of unitary matrices and photonics to perform computations. In this paper, we design a photonic unitary neural network based on Mach–Zehnder interferometer arrays. The results show that the network has a good performance on both triangular and circular binary classification datasets, where most of the data points are correctly classified. The accuracies achieve 97% and 95% for triangular and circular datasets, with the loss function values of 0.023 and 0.046, respectively.

Vol. 54
Issue 1
pp. 5-13

0.9 MB
OPTICA APPLICATA - a quarterly of the Wrocław University of Science and Technology, Faculty of Fundamental Problems of Technology