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5 March 2021 Advancing photonics with machine learning
Alexandra Boltasseva, Vladimir Shalaev, Zhaxylyk Kudyshev
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Proceedings Volume 11694, Photonic and Phononic Properties of Engineered Nanostructures XI; 116940L (2021) https://doi.org/10.1117/12.2589478
Event: SPIE OPTO, 2021, Online Only
Abstract
Discovering unconventional optical designs via machine-learning promises to advance on-chip circuitry, imaging, sensing, energy, and quantum information technology. In this talk, photonic design approaches and emerging material platforms will be discussed showcasting machine-learning-assisted topology optimization for thermophotovoltaic metasurface designs and machine-learning-enabled quantum optical measurements.
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Alexandra Boltasseva, Vladimir Shalaev, and Zhaxylyk Kudyshev "Advancing photonics with machine learning", Proc. SPIE 11694, Photonic and Phononic Properties of Engineered Nanostructures XI, 116940L (5 March 2021); https://doi.org/10.1117/12.2589478
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KEYWORDS
Machine learning
Information technology
Optical design
Optical testing
Quantum information
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