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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Peer ReviewDOI
Computation at the speed of light: metamaterials for all-optical calculations and neural networks
TL;DR: In this article , the physical implementation of basic optical calculations, such as differentiation and integration, using metamaterials, and the realization of all-optical artificial neural networks are reviewed.
Posted Content
Fiber-based photonic feed-forward with 99% fidelity
G. L. Zanin,Maxime Jacquet,Michele Spagnolo,Peter Schiansky,Irati Alonso Calafell,Lee A. Rozema,Philip Walther +6 more
TL;DR: A fiber-compatible scheme for measurement and feed-forward, whose performance is benchmarked by carrying out remote preparation of single-photon polarization states at telecom-wavelengths, whose methods are useful for photonic quantum experiments including computing, communication, and teleportation.
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Dynamic Precision Analog Computing for Neural Networks.
TL;DR: In this paper, the authors derive a relationship between analog precision, which is limited by noise, and digital bit precision, and derive a method for learning the precision of each layer of a pre-trained model without retraining network weights.
Proceedings ArticleDOI
3D photo-responsive optical devices manufactured by advanced printing technologies
Adam Szukalski,Sureeporn Uttiya,Francesca D'Elia,Alberto Portone,Dario Pisignano,Dario Pisignano,Luana Persano,Andrea Camposeo +7 more
TL;DR: In this paper, the authors report on advanced additive manufacturing technologies, specifically designed to embed photo-responsive compounds in 3D optical devices, which can be controlled by external UV and visible light beams, with characteristic switching times in the range 1-10 s.
Proceedings ArticleDOI
Digital Optical Neural Networks for Large-Scale Machine Learning
TL;DR: A digital incoherent optical neural network architecture using the passive data routing and copying capabilities of optics for artificial neural network acceleration is proposed.
References
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