Inverse-designed optical metalements, metadevices, and metasystems

Alexander V. Kildishev; Zhaxylyk Kudyshev; Omer Yesilyurt

doi:10.1117/12.2677875

4 October 2023 Inverse-designed optical metalements, metadevices, and metasystems

Alexander V. Kildishev, Zhaxylyk Kudyshev, Omer Yesilyurt

Proceedings Volume PC12646, Metamaterials, Metadevices, and Metasystems 2023; PC126461I (2023) https://doi.org/10.1117/12.2677875
Event: SPIE Nanoscience + Engineering, 2023, San Diego, California, United States

Abstract

In the past decade, photonics and optoelectronics have significantly progressed in developing new nanofabrication techniques for optical metamaterials. However, the optimal design of such artificial nanostructures remains complex and resource-intensive, often relying on intuition-based models. In this context, machine learning-assisted optimization techniques emerged as a promising approach to achieving high-performance and practical solutions. We discuss diverse inverse design approaches that use machine learning algorithms to optimize the design of nanophotonic metadevices, including the high-efficiency coupling of single-photon sources with photonic waveguides, variable-index multilayer films, active nanophotonic devices and systems, other photonic metastructures with optimized complex topologies.

Conference Presentation

Citation Download Citation

Alexander V. Kildishev, Zhaxylyk Kudyshev, and Omer Yesilyurt "Inverse-designed optical metalements, metadevices, and metasystems", Proc. SPIE PC12646, Metamaterials, Metadevices, and Metasystems 2023, PC126461I (4 October 2023); https://doi.org/10.1117/12.2677875

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