光子学
计算机科学
领域(数学)
人工智能
多样性(控制论)
光学现象
物理
光学
光电子学
数学
纯数学
作者
Sergey Krasikov,Aaron D. Tranter,Andrey Bogdanov,Yuri S. Kivshar
标识
DOI:10.29026/oea.2022.210147
摘要
In the recent years, a dramatic boost of the research is observed at the junction of photonics, machine learning and artificial intelligence. A new methodology can be applied to the description of a variety of photonic systems including optical waveguides, nanoantennas, and metasurfaces. These novel approaches underpin the fundamental principles of light-matter interaction developed for a smart design of intelligent photonic devices. Artificial intelligence and machine learning penetrate rapidly into the fundamental physics of light, and they provide effective tools for the study of the field of metaphotonics driven by optically induced electric and magnetic resonances. Here we overview the evaluation of metaphotonics induced by artificial intelligence and present a summary of the concepts of machine learning with some specific examples developed and demonstrated for metasystems and metasurfaces.
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