使用多模光学芯片的简单非线性分类器

IF 3.7 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY Advanced Photonics Research Pub Date : 2024-02-02 DOI:10.1002/adpr.202470004
Zhangqi Dang, Zeyu Deng, Tao Chen, Zhenming Ding, Ziyang Zhang
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引用次数: 0

摘要

光子神经网络正在成为一种前景广阔的快速、高能效计算技术。迄今为止,光学主要执行线性变换,而集成非线性激活函数仍是一项挑战。封面图片显示的是一个只有一个多模波导和几个电极的光神经芯片。虽然极其简单,但这种芯片却能构建一个具有线性和非线性变换的模块化网络。这项工作(见张子扬及其合作者的文章编号 2300253)为利用调制多模干涉进行光子计算应用提供了另一条途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A Simple Nonlinear Classifier Using a Multimode Optical Chip

The photonic neural network is emerging as a promising technology for fast and power-efficient computing. So far, optics mainly perform linear transformations, and it remains challenging to integrate nonlinear activation function. The cover image shows an optical neural chip with only one multimode waveguide and a few electrodes. Though extremely simple, this chip constructs a modular network with both linear and nonlinear transformations. This work (see article number 2300253 by Ziyang Zhang and co-workers) offers an alternative route to exploiting the modulated multimode interference for photonic computing applications.

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