光学
方位角
模式(计算机接口)
角动量
纤维
残余物
物理
计算机科学
模式音量
芯(光纤)
人工神经网络
混合动力系统
光纤
算法
人工智能
渐变折射率纤维
光纤传感器
量子力学
机器学习
操作系统
有机化学
化学
作者
Hua Zhao,Jiannan Xu,Yuanyuan Hao,Jiayang Xu,Huali Lu,Hui Hao,Ting Zhao,Pengfei Li,Peng Wang,Hongpu Li
出处
期刊:Optics Express
[Optica Publishing Group]
日期:2023-08-22
卷期号:31 (19): 30627-30627
被引量:1
摘要
In this study, we theoretically and experimentally demonstrate that the convolutional neural network (CNN) in combination with the residual blocks and the regression methods can be used to precisely and quickly reconstruct the OAM spectrum of a hybrid OAM mode no matter how the consistent OAM modes have the same or different order indices in both the azimuthal and the radial direction. For cases of the simulation testing, the mean errors of all recognized parameters for hybrid OAM modes in a four-mode fiber (4MF) and a six-mode fiber (6MF) are smaller than 0.003 and 0.008, respectively. To the best of our knowledge, this is the first time that all the OAM modes, probably existing in the core of 4MFs or 6MFs, can be precisely and quickly recognized from intensity distribution of the hybrid OAM mode itself via the deep learning method.
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