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2 August 2021 Deep learning to explain and design complex nanophotonic structures
Aaswath P. Raman
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Proceedings Volume 11795, Metamaterials, Metadevices, and Metasystems 2021; 117950D (2021) https://doi.org/10.1117/12.2595477
Event: SPIE Nanoscience + Engineering, 2021, San Diego, California, United States
Abstract
A central challenge in the development of nanophotonic structures and metamaterials is identifying the optimal design for a target functionality and understanding the physical mechanisms that enable the optimized device’s capabilities. In this talk, we will describe deep learning-driven strategies to both design complex nanophotonic structures, including across multiple device categories, as well as understand their behavior. We will highlight potential pathways to making deep learning a tool for global inverse design across multiple device categories, while also opening up the 'black box' of the machine learning algorithm to understand why a particular optimized design works well.
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Aaswath P. Raman "Deep learning to explain and design complex nanophotonic structures", Proc. SPIE 11795, Metamaterials, Metadevices, and Metasystems 2021, 117950D (2 August 2021); https://doi.org/10.1117/12.2595477
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KEYWORDS
Nanophotonics
Structural design
Metamaterials
Absorption
Artificial intelligence
Convolutional neural networks
Electromagnetism
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