Analyzing OAM mode purity in optical fibers with CNN-based deep learning  

作　　者：Tianying Lin Ang Liu Xiaopei Zhang He Li Liping Wang Hailong Han Ze Chen Xiaoping Liu Haibin Lü 林天营;刘昂;张笑裴;李鹤;汪利平;韩海龙;陈泽;刘晓平;吕海斌(National Laboratory of Solid State Microstructures and College of Engineering and Applied Sciences,Nanjing University,Nanjing 210093,China;Collaborative Innovation Center of Advanced Microstructures,Nanjing University,Nanjing 210093,China)

机构地区：[1]National Laboratory of Solid State Microstructures and College of Engineering and Applied Sciences,Nanjing University,Nanjing 210093,China [2]Collaborative Innovation Center of Advanced Microstructures,Nanjing University,Nanjing 210093,China

出　　处：《Chinese Optics Letters》2019年第10期108-113,共6页中国光学快报（英文版）

基　　金：supported by the National Basic Research Program of China(No.2015CB659400);the Natural Science Foundation of Jiangsu Province(No.BK20150057);the Fundamental Research Funds for the Central Universities(No.021314380100)

摘　　要：Inspired by recent rapid deep learning development,we present a convolutional-neural-network(CNN)-based algorithm to predict orbital angular momentum(OAM)mode purity in optical fibers using far-field patterns.It is found that this image-processing-based technique has an excellent ability in predicting the OAM mode purity,potentially eliminating the need of using bulk optic devices to project light into different polarization states in traditional methods.The excellent performance of our algorithm can be characterized by a prediction accuracy of 99.8%and correlation coefficient of 0.99994.Furthermore,the robustness of this technique against different sizes of testing sets and different phases between different fiber modes is also verified.Hence,such a technique has a great potential in simplifying the measuring process of OAM purity.Inspired by recent rapid deep learning development, we present a convolutional-neural-network(CNN)-based algorithm to predict orbital angular momentum(OAM) mode purity in optical fibers using far-field patterns.It is found that this image-processing-based technique has an excellent ability in predicting the OAM mode purity, potentially eliminating the need of using bulk optic devices to project light into different polarization states in traditional methods. The excellent performance of our algorithm can be characterized by a prediction accuracy of 99.8% and correlation coefficient of 0.99994. Furthermore, the robustness of this technique against different sizes of testing sets and different phases between different fiber modes is also verified. Hence, such a technique has a great potential in simplifying the measuring process of OAM purity.

关 键 词：OAM POLARIZATION mode 

分 类 号：TN9[电子电信—信息与通信工程]