Jia Qi, Zhang Yanxia, Shi Bojian, Li Hang, Li Xiaoxin, Feng Rui, Sun Fangkui, Cao Yongyin, Wang Jian, Qiu Cheng-Wei, Ding Weiqiang
Institute of Advanced Photonics, School of Physics, Harbin Institute of Technology, Harbin 150001, China.
School of Physics, Harbin Institute of Technology, Harbin 150001, China.
Nanophotonics. 2023 Oct 4;12(20):3955-3962. doi: 10.1515/nanoph-2023-0482. eCollection 2023 Oct.
Polarization (), angular index (), and radius index () are three independent degrees of freedom (DoFs) of vector vortex beams, which have found extensive applications in various domains. While efficient sorting of a single DoF has been achieved successfully, simultaneous sorting of all these DoFs in a compact and efficient manner remains a challenge. In this study, we propose a beam sorter that simultaneously handles all the three DoFs using a diffractive deep neural network (DNN), and demonstrate the robust sorting of 120 Laguerre-Gaussian (LG) modes experimentally in the visible spectrum. Our proposed beam sorter underscores the considerable potential of DNN in optical field manipulation and promises to enhance the diverse applications of vector vortex beams.
偏振()、角指数()和径向指数()是矢量涡旋光束的三个独立自由度(DoFs),它们在各个领域都有广泛应用。虽然已经成功实现了单个自由度的高效分选,但以紧凑且高效的方式同时分选所有这些自由度仍然是一个挑战。在本研究中,我们提出了一种光束分选器,它使用衍射深度神经网络(DNN)同时处理所有三个自由度,并在可见光谱中通过实验证明了对120种拉盖尔 - 高斯(LG)模式的稳健分选。我们提出的光束分选器强调了DNN在光场操纵方面的巨大潜力,并有望增强矢量涡旋光束的各种应用。