Advancing photonic design and measurements with artificial intelligence

Zhaxylyk A. Kudyshev; Simeon Bogdanov; Zachariah Olson; Xiaohui Xu; Demid Sychev; Alexander Kildishev; Vladimir Shalaev; Alexandra Boltasseva

doi:10.1117/12.2594790

2 August 2021 Advancing photonic design and measurements with artificial intelligence

Zhaxylyk A. Kudyshev, Simeon Bogdanov, Zachariah Olson, Xiaohui Xu, Demid Sychev, Alexander Kildishev, Vladimir Shalaev, Alexandra Boltasseva

Author Affiliations +

Proceedings Volume 11795, Metamaterials, Metadevices, and Metasystems 2021; 1179506 (2021) https://doi.org/10.1117/12.2594790
Event: SPIE Nanoscience + Engineering, 2021, San Diego, California, United States

Abstract

Discovering novel, unconventional optical designs in combination with advanced machine-learning assisted data analysis techniques can uniquely enable new phenomena and breakthrough advances in many areas including imaging, sensing, energy, and quantum information technology. It demonstrated that compared to other inverse-design approaches that require extreme computation power to undertake a comprehensive search within a large parameter space, machine learning assisted topology optimization can expand the design space while improving the computational efficiency. This talk will highlight our most recent findings on 1) merging topology optimization with artificial-intelligence-assisted algorithms and 2) integrating machine-learning based analysis with photonic design and quantum optical measurements.

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Zhaxylyk A. Kudyshev, Simeon Bogdanov, Zachariah Olson, Xiaohui Xu, Demid Sychev, Alexander Kildishev, Vladimir Shalaev, and Alexandra Boltasseva "Advancing photonic design and measurements with artificial intelligence", Proc. SPIE 11795, Metamaterials, Metadevices, and Metasystems 2021, 1179506 (2 August 2021); https://doi.org/10.1117/12.2594790

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