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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Highly Sensitive Integrated Photonic Sensor and Interrogator Using Cascaded Silicon Microring Resonators
TL;DR: In this paper , a monolithic silicon refractive index sensor and interrogator was proposed by utilizing the cascaded microring resonators for high-performance, compactness, and large-scale integration capability.
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Large-Scale Crosstalk-Corrected Thermo-Optic Phase Shifter Arrays in Silicon Photonics
TL;DR: In this article , the authors introduce a thermo-optic phase shifter (TOPS) array architecture with independent phase control for large-scale and high-density photonic integrated circuits with two different control schemes: PAM and PWM.
Full-wave solver for massively multi-channel optics using augmented partial factorization
TL;DR: This work proposes an approach where all simulations are solved jointly and e-ciently by augmenting the Maxwell operator with the source and the projection profiles, followed by a single partial factorization, and opens the door to previously inaccessible studies across disciplines involving multi-channel wave transport.
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A topological nonlinear parametric amplifier
Byoung-Uk Sohn,Yue-Xin Huang,Ju Won Choi,George F. R. Chen,Doris K. T. Ng,Shengyuan A. Yang,Dawn T. H. Tan +6 more
TL;DR: In this article , the topological nonlinear parametric amplification of light in a dimerized coupled waveguide system based on the Su-Schrieffer-Heeger model with a domain wall is demonstrated.
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Real-time multi-task diffractive deep neural networks via hardware-software co-design.
TL;DR: In this paper, the authors proposed a hardware-software co-design method that enables first-of-its-like real-time multi-task learning in D2NNs that automatically recognizes which task is being deployed in real time.
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