Intelligent metaphotonics empowered by machine learning

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 lightmatter 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.

Automated summary

In recent years, the intersection of photonics, machine learning, and artificial intelligence has seen a significant boost in research. A new methodology has been developed to describe various photonic systems, enabling intelligent design of photonic devices. Artificial intelligence and machine learning have rapidly penetrated the fundamental physics of light and provide effective tools for studying the field of metaphotonics. This article provides an overview of the evaluation of metaphotonics induced by artificial intelligence and summarizes the concepts of machine learning with specific examples in metasystems and metasurfaces.