Deep learning with coherent nanophotonic circuits
Yichen Shen,Nicholas C. Harris,Scott Skirlo,Dirk Englund,Marin Soljacic +4 more
- Vol. 11, Iss: 7, pp 441-446
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TLDR
A new architecture for a fully optical neural network is demonstrated that enables a computational speed enhancement of at least two orders of magnitude and three order of magnitude in power efficiency over state-of-the-art electronics.Abstract:
Artificial Neural Networks have dramatically improved performance for many machine learning tasks. We demonstrate a new architecture for a fully optical neural network that enables a computational speed enhancement of at least two orders of magnitude and three orders of magnitude in power efficiency over state-of-the-art electronics.read more
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Responsive materials architected in space and time
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An Optical Frontend for a Convolutional Neural Network
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Residual D 2 NN: training diffractive deep neural networks via learnable light shortcuts
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Nanophotonic spin-glass for realization of a coherent Ising machine.
Yoshitomo Okawachi,Mengjie Yu,Jae K. Jang,Xingchen Ji,Yun Zhao,Bok Young Kim,Michal Lipson,Alexander L. Gaeta +7 more
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An optical neural network using less than 1 photon per multiplication
TL;DR: In this article , the authors demonstrate an optical neural network based on optical dot products that achieves 99% accuracy on handwritten-digit classification using 3.1 detected photons per weight multiplication and 90% accuracy using 0.66 photons (~2.5 × 10-19 J of optical energy).
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