中国光学（中英文）2024，Vol.17Issue(4)：834-841,8.DOI:10.37188/CO.2023-0198
插损鲁棒性的全复值光学神经网络
Fully complex optical neural network with insertion-loss robustness
摘要
Abstract
Linear optical processors based on the cascaded topology of Mach-Zehnder Interferometer(MZI)have been demonstrated to be an important way of implementing Optical Neural Networks(ONN),but sever-al practical challenges still need resolution.Concerning issues arising from chip manufacturing and testing processes that could lead to phase errors and insertion losses,we conducted experiments and theoretical sim-ulations for various reconfigurable optical processors.We found that the weights of any arbitrary unitary mat-rix can be realized through some single N×N Clements units,that can substantially reduce the optical depth and enhance robustness against insertion losses.This approach allows for the construction of fully complex optical neural networks.Additionally,In multi-layer ONN,due to the limited degrees of freedom in con-structing this arbitrary matrix,we introduced a phase-shift layer before each layer of the Clements unit.This design aids in mapping classification data to higher-dimensional spaces,facilitating faster neural network convergence.关键词
光学神经网络/MZI阵列/可重构光学处理器Key words
optical neural network/Mach-Zehnder interferometer array/reconfigurable optical processor分类
信息技术与安全科学引用本文复制引用
陈慧彬,汤凯飞,游振宇..插损鲁棒性的全复值光学神经网络[J].中国光学（中英文）,2024,17(4):834-841,8.基金项目
国家自然科学基金(No.61705119)Supported by the National Natural Science Foundation of China(No.61705119) （No.61705119）
