Artificial Intelligence in Classical and Quantum Photonics

被引:22
|
作者
Vernuccio, Federico [1 ]
Bresci, Arianna [1 ]
Cimini, Valeria [3 ]
Giuseppi, Alessandro [4 ]
Cerullo, Giulio [1 ,2 ]
Polli, Dario [1 ,2 ]
Valensise, Carlo Michele [5 ]
机构
[1] Politecn Milan, Dept Phys, Pzza Leonardo da Vinci 32, I-20133 Milan, Italy
[2] CNR, Ist Foton & Nanotecnol IFN, I-20133 Milan, Italy
[3] Sapienza Univ Roma, Dept Phys, Ple Aldo Moro 5, I-00185 Rome, Italy
[4] Sapienza Univ Roma, Dept Comp Control & Management Engn, Via Ariosto 25, I-00185 Rome, Italy
[5] Enrico Fermi Res Ctr, Piazza Viminale 1, I-00184 Rome, Italy
基金
欧盟地平线“2020”;
关键词
artificial intelligence; computational imaging; multi-modal fibers; neural networks; photonics; quantum optics; spectroscopy; CONVOLUTIONAL NEURAL-NETWORKS; EXTREME LEARNING-MACHINE; MULTIMODE FIBER; HIGH-RESOLUTION; IMAGE CLASSIFICATION; OBJECT RECOGNITION; LIGHT; TIME; TRANSMISSION; INFORMATION;
D O I
10.1002/lpor.202100399
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
The last decades saw a huge rise of artificial intelligence (AI) as a powerful tool to boost industrial and scientific research in a broad range of fields. AI and photonics are developing a promising two-way synergy: on the one hand, AI approaches can be used to control a number of complex linear and nonlinear photonic processes, both in the classical and quantum regimes; on the other hand, photonics can pave the way for a new class of platforms to accelerate AI-tasks. This review provides the reader with the fundamental notions of machine learning (ML) and neural networks (NNs) and presents the main AI applications in the fields of spectroscopy and chemometrics, computational imaging (CI), wavefront shaping and quantum optics. The review concludes with an overview of future developments of the promising synergy between AI and photonics.
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页数:30
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