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<p>A silicon photonic deep optical neural network integrating convolutional and fully connected layers with on-chip optoelectronic nonlinear activations operates with partially coherent light to achieve high-speed, energy-efficient, end-to-end inference. This demonstration establishes a functional and scalable platform for evaluating complete optical neural processing, representing another step toward specialised, ultrafast photonic architectures beyond electronics.</p>

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Demonstrating completeness in optical neural computing

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月3日

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  • Krzysztof Tyszka

摘要

A silicon photonic deep optical neural network integrating convolutional and fully connected layers with on-chip optoelectronic nonlinear activations operates with partially coherent light to achieve high-speed, energy-efficient, end-to-end inference. This demonstration establishes a functional and scalable platform for evaluating complete optical neural processing, representing another step toward specialised, ultrafast photonic architectures beyond electronics.