基于深度学习技术从散斑场中识别多多涡旋结构的轨道角动量  

Detection of orbital angular momentum of multiple vortices from speckle via deep learning

作　　者：王孝艳 王志远 陈子阳 蒲继雄 WANG Xiaoyan;WANG Zhiyuan;CHEN Ziyang;PU Jixioing(Fujian Provincial Key Laboratory of Light Propagation and Transformation,College of Information Science&Engineering,Huaqiao University,Xiamen 361021,China)

机构地区：[1]华侨大学信息科学与工程学院福建省光传输与变换重点实验室,福建厦门361021

出　　处：《量子电子学报》2022年第6期955-961,共7页Chinese Journal of Quantum Electronics

基　　金：国家自然科学基金,62005086。

摘　　要：涡旋光束的轨道角动量(OAM)可用于信息的编码,因此在自由空间光通讯等领域具有重要的应用价值。然而,实际的传输空间通常存在着各种随机介质,会造成传输涡旋光束的波面畸变,导致传统的方法无法准确测量涡旋光束的轨道角动量。针对此问题,以毛玻璃作为随机介质,基于深度学习技术,从涡旋光束经过毛玻璃所产生的散斑场中准确识别出了涡旋光束的轨道角动量。进一步,为提升光信息的编码与传输能力,还测试了多涡旋结构光束的轨道角动量识别。测试结果表明,对于五个涡旋结构的光束,所设计的网络也能从单帧散斑图中准确识别其轨道角动量。The orbital angular momentum(OAM)of vortex beams can be used for information coding,which has important applications in free space optical communications.Nevertheless,the propagation of beams may encounter various random media in actual transmission space,which will distort the wavefront of vortex beam,rendering the ineffectiveness of traditional methods in retrieving the OAM.To tackle this issue,by taking ground glass as a random medium,recognition of OAM of vortex beam from speckle pattern is realized based on deep learning.Moreover,to further upgrade the information coding and transmission capability,recognition of multiple OAMs is examined as well.The results show that the designed network is capable of simultaneously recognizing five OAMs from a single-shot speckle pattern generated by vortex beams through ground glass.

关 键 词：量子光学 轨道角动量 深度学习 涡旋光束 散斑 

分 类 号：O431.2[机械工程—光学工程]