Wang Jiaqi, Fu Shiyao, Shang Zijun, Hai Lan, Gao Chunqing
Opt Lett. 2022 Mar 15;47(6):1419-1422. doi: 10.1364/OL.443726.
Orbital angular momentum (OAM) is one of multiple dimensions of beams. A beam can carry multiple OAM components, and their intensity weights form the OAM spectrum. The OAM spectrum determines complex amplitude distributions of a beam and features unique characteristics. Thus, measuring the OAM spectrum is of great significance, especially for OAM-based applications. Here we employ a deep neural network combined with a phase-only diffraction optical element to measure the OAM spectrum. The diffraction optical element is designed to diffract incident beams into distinct patterns corresponding to OAM distributions. Then, the EfficientNet, a kind of deep neural network, is adjusted to adapt and analyze the diffraction pattern to calculate the OAM spectrum. The favorable experimental results show that our proposal can reconstruct the OAM spectra with high precision and speed, works well for different numbers of OAM channels, and is also robust to Gaussian noise and random zooming. This work opens a new, to the best of our knowledge, ability for OAM spectrum recognition and will find applications in a number of advanced domains including large capacity optical communications, quantum key distribution, optical trapping, rotation detection, and so on.
轨道角动量（OAM）是光束的多个维度之一。一束光可以携带多个OAM分量，其强度权重构成OAM谱。OAM谱决定了光束的复振幅分布并具有独特的特性。因此，测量OAM谱具有重要意义，特别是对于基于OAM的应用。在这里，我们采用深度神经网络结合纯相位衍射光学元件来测量OAM谱。衍射光学元件被设计用于将入射光束衍射成与OAM分布相对应的不同图案。然后，对一种深度神经网络EfficientNet进行调整，以适应和分析衍射图案来计算OAM谱。良好的实验结果表明，我们的方案能够高精度、快速地重建OAM谱，对不同数量的OAM通道都能很好地工作，并且对高斯噪声和随机缩放也具有鲁棒性。据我们所知，这项工作开启了一种新的OAM谱识别能力，并将在包括大容量光通信、量子密钥分发、光镊、旋转检测等许多先进领域找到应用。
