Detection of Orbital Angular Momentum of Light Based on Shear Interferometer and Residual Network Model

被引:2
作者
Liu, Guanhua [1 ]
Zhou, Jingwen [1 ]
Tang, Jihong [1 ]
Xia, Yong [1 ]
机构
[1] East China Normal Univ, Sch Phys & Elect Sci, State Key Lab Precis Spect, Joint Inst Adv Sci & Technol, Shanghai 200241, Peoples R China
关键词
vortex beam; orbital angular momentum; shear interferometer; spatial light modulator; machine learning; OPTICAL COMMUNICATIONS; INTERFERENCE; SPECTRUM;
D O I
10.3788/LOP240685
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The orbital angular momentum (OAM) of vortex beams has important application prospects in free-space optical communications. During the propagation of vortex beams, atmospheric turbulence can affect the accurate detection of OAM modes. We propose and demonstrate the accurate detection of OAM modes using a shear interferometer and residual network model (ResNet-50) under different atmospheric turbulence conditions. We first derive the optical field intensity distribution of OAM beams after passing them through a shearing interferometer. We then introduce atmospheric turbulence theory and a residual network model suitable for the proposed physical model. Finally, we investigate the effects of training sample size on OAM recognition accuracy and OAM recognition accuracy under different turbulence intensity conditions. Results show that during the propagation of OAM beams, within the range of topological charge l of -4 & horbar;4 and under weak atmospheric turbulence simulated by computers at C-n(2)=5x10(-16 )m(-2/3), the OAM recognition accuracy is 100%. Under strong atmospheric turbulence simulated at CCn2=5x10(-14) m(-2/3), the OAM recognition accuracy is 92%.
引用
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页数:8
相关论文
共 35 条
[1]   ORBITAL ANGULAR-MOMENTUM OF LIGHT AND THE TRANSFORMATION OF LAGUERRE-GAUSSIAN LASER MODES [J].
ALLEN, L ;
BEIJERSBERGEN, MW ;
SPREEUW, RJC ;
WOERDMAN, JP .
PHYSICAL REVIEW A, 1992, 45 (11) :8185-8189
[2]   AN ANALYTICAL MODEL FOR THE REFRACTIVE-INDEX POWER SPECTRUM AND ITS APPLICATION TO OPTICAL SCINTILLATIONS IN THE ATMOSPHERE [J].
ANDREWS, LC .
JOURNAL OF MODERN OPTICS, 1992, 39 (09) :1849-1853
[3]   Machine learning based accurate recognition of fractional optical vortex modes in atmospheric environment [J].
Cao, Meng ;
Yin, Yaling ;
Zhou, Jingwen ;
Tang, Jihong ;
Cao, Luping ;
Xia, Yong ;
Yin, Jianping .
APPLIED PHYSICS LETTERS, 2021, 119 (14)
[4]   Automated trapping, assembly, and sorting with holographic optical tweezers [J].
Chapin, Stephen C. ;
Germain, Vincent ;
Dufresne, Eric R. .
OPTICS EXPRESS, 2006, 14 (26) :13095-13100
[5]   Machine learning approach to OAM beam demultiplexing via convolutional neural networks [J].
Doster, Timothy ;
Watnik, Abbie T. .
APPLIED OPTICS, 2017, 56 (12) :3386-3396
[6]   Recognition of Orbital Angular Momentum of Fractional Perfect Optical Vortex Beam Based on Convolutional Neural Network and Multiaperture Interferometer [J].
Du Haobo ;
Chen Jun ;
Fu Gangkun ;
Li Yansong ;
Wang Hailong ;
Shi Yan ;
Zhao Chunliu ;
Jin Shangzhong .
ACTA OPTICA SINICA, 2023, 43 (04)
[7]   Twisted photons: new quantum perspectives in high dimensions [J].
Erhard, Manuel ;
Fickler, Robert ;
Krenn, Mario ;
Zeilinger, Anton .
LIGHT-SCIENCE & APPLICATIONS, 2018, 7 :17146-17146
[8]   Creation and detection of optical modes with spatial light modulators [J].
Forbes, Andrew ;
Dudley, Angela ;
McLaren, Melanie .
ADVANCES IN OPTICS AND PHOTONICS, 2016, 8 (02) :200-227
[9]  
Gao C Q, 2019, Vortex beams, P143
[10]  
Guo Z Y, 2020, Opto-Electronic Engineering, V47