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
Citations
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Journal ArticleDOI
Deep learning enabled design of complex transmission matrices for universal optical components
Nicholas J. Dinsdale,Peter R. Wiecha,Peter R. Wiecha,Matthew Delaney,Jamie D. Reynolds,Martin Ebert,Ioannis Zeimpekis,David J. Thomson,Graham T. Reed,Philippe Lalanne,Kevin Vynck,Otto L. Muskens +11 more
TL;DR: An ultracompact platform for low-loss programmable elements using the complex transmission matrix of a multi-port multimode waveguide that allows control over both the intensity and phase in a multiport device at a four orders reduced device footprint compared to conventional technologies, thus opening the door for large-scale integrated universal networks.
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Spike-based information encoding in vertical cavity surface emitting lasers for neuromorphic photonic systems
TL;DR: The reported functionalities with the ultrafast spiking VCSEL-neurons provide a reliable, multifaceted approach for interfacing photonic neuromorphic platforms with existing computation and communication systems.
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Photonic (computational) memories: tunable nanophotonics for data storage and computing
TL;DR: In this article , the authors review emerging nanophotonic devices that possess memory capabilities by elaborating on their tunable mechanisms and evaluating them in terms of scalability and device performance, and discuss the progress on large-scale architectures for photonic memory arrays and optical computing primarily based on memory performance.
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Silicon photonics for telecom and data-com applications
TL;DR: This paper overviews the progresses of silicon photonics from four points reflecting the recent advances reflecting the CMOS-based silicon photonic platform technologies, applications to optical transceiver in the data-com network, Applications to multi-port optical switches in the telecom network and applications to OPA in LiDAR system.
Journal ArticleDOI
Photonic principal component analysis using an on-chip microring weight bank
Philip Y. Ma,Alexander N. Tait,Thomas Ferreira de Lima,Siamak Abbaslou,Bhavin J. Shastri,Paul R. Prucnal +5 more
TL;DR: This paper reports a photonic PCA approach using an on-chip microring (MRR) weight bank to perform weighted addition operations on correlated wavelength-division multiplexed (WDM) inputs, and proposes a novel PCA algorithm that is able to extract principal components solely based on the statistical information of the weighted addition output.
References
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