一个硅光子神经网络的演示

2016 IEEE Photonics Society Summer Topical Meeting Series (SUM) Pub Date : 2016-07-11 DOI:10.1109/PHOSST.2016.7548726

A. Tait, E. Zhou, A. Wu, M. Nahmias, T. F. de Lima, B. Shastri, P. Prucnal

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引用次数: 5

摘要

硅光子集成可以实现高性能的脑启发光子处理器。我们展示了一个3节点循环光子神经网络。由突触重构引起的尖分岔和Hopf分岔显示为概念证明。该原型代表了集成光子学的基于网络的物理计算模型的早期步骤。

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Demonstration of a silicon photonic neural network

Silicon photonic integration could enable high-performance brain-inspired photonic processors. We demonstrate a 3 node recurrent photonic neural network. Cusp and Hopf bifurcations induced by synaptic reconfiguration are shown as proof-of-concept. The prototype represents an early step towards network-based models of physical computing with integrated photonics.

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2016 IEEE Photonics Society Summer Topical Meeting Series (SUM)

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