Back to Search Start Over

Intelligent metaphotonics empowered by machine learning

Authors :
Sergey Krasikov
Aaron Tranter
Andrey Bogdanov
Yuri Kivshar
Source :
Opto-Electronic Advances, Vol 5, Iss 3, Pp 1-24 (2022)
Publication Year :
2022
Publisher :
Institue of Optics and Electronics, Chinese Academy of Sciences, 2022.

Abstract

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.

Details

Language :
English
ISSN :
20964579
Volume :
5
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Opto-Electronic Advances
Publication Type :
Academic Journal
Accession number :
edsdoj.1365dd7b3da9419396856b829878e0ed
Document Type :
article
Full Text :
https://doi.org/10.29026/oea.2022.210147