Intelligent nanophotonics: when machine learning sheds light
Ministry of Industry and Information Technology · Chinese University of Hong Kong, Shenzhen · +2 more institutions
Abstract
Abstract The synergistic development of nanophotonics and machine learning has inspired tremendous innovations in both fields in the past decade. In diverse photonics research, deep-learning methods using artificial neural networks become the key game changer that greatly facilitates rapid nanophotonics design and the versatile processing of optical information. Moreover, optical computing platforms that perform calculations through light propagation are receiving tremendous interest as next-generation machine-learning hardware with advantages in computing speed, energy efficiency, and parallelism. This review summarizes the current state-of-the-art nanophotonic devices enabled by machine learning and analyzes…
Citation impact
- FWCI
- 87.66
- Percentile
- 100%
- References
- 291
Authors
14- NWNanfan WuCorresponding
Ministry of Industry and Information Technology
- YSYuxiang Sun
Chinese University of Hong Kong, Shenzhen, Ministry of Industry and Information Technology
- JHJingtian Hu
Shenzhen Bay Laboratory, Ministry of Industry and Information Technology
- CYChuang Yang
Ministry of Industry and Information Technology
- ZBZichun Bai
Chinese University of Hong Kong, Shenzhen
Topics & keywords
- Nanophotonics
- Computer science
- Artificial intelligence
- Nanotechnology
- Materials science
Funding
- NNNational Natural Science Foundation of ChinaAwards: 12334016, 12261131500, 62125501, 62335005, 62405076, 12404442, 12025402, 92250302
- NSNatural Science Foundation of Hebei ProvinceAward: 12261131500
- NKNational Key Research and Development Program of ChinaAwards: 2021YFA1400802, 2022YFA1404700, 2024YFB2809200
- FRFundamental Research Funds for the Central UniversitiesAward: 2022FRFK01013
- BABasic and Applied Basic Research Foundation of Guangdong ProvinceAward: 2023A1515110685