大气湍流下高分辨率高带宽分数涡旋光束的探测

doi:10.3969/j.issn.1000-5641.2025.03.007

摘要/Abstract

摘要：

提出并产生了一种高分辨率的分数混合涡旋光束, 其具有混合比例参数$ n $, 可提供新的自由度以扩展轨道角动量的带宽. 结合深度学习中卷积神经网络的方法, 对大气湍流条件下轨道角动量分辨率$ \Delta l=0.1, $ 以及混合比例参数分辨率$\Delta n =0.01$的分数混合涡旋光束进行了精确识别, 研究了湍流强度和传输距离对识别准确率的影响. 结果表明, 对于150 m的传输距离, 即使在较强湍流($ C_n^2 $ = 5 × 10^–14 m^–2/3)下, 识别准确率仍达到了82.09%; 在中弱湍流($ C_n^2 $ = 1 × 10^–14, 5 × 10^–15 m^–2/3)下, 识别准确率均超过99%. 该方案可为湍流环境下准确识别分数轨道角动量提供参考.

关键词: 涡旋光束, 分数轨道角动量, 大气湍流, 深度学习

Abstract:

In this study, a high-resolution fractional hybrid vortex beam is proposed. The hybrid scaling parameter $n $ used to generate the fractional hybrid vortex beam provides new degrees of freedom, extending the bandwidth of orbital angular momentum. The convolutional neural network from deep learning was adopted to accurately recognize the fractional hybrid vortex beam with an orbital angular momentum resolution $\Delta l $ of 0.1 and hybrid scaling parameter resolution $\Delta n $ of 0.01 under atmospheric turbulence conditions. The study investigated the effects of turbulence intensity and transmission distance on recognition accuracy. The results indicate that at a transmission distance of 150 m, the recognition accuracy reaches 82.09%, even under strong turbulence ($C_n^2 $ = 5×10^–14 m^–2/3). The recognition accuracy exceeded 99% under the conditions of medium and weak turbulence ($C_n^2 $ = 1×10^–14 m^–2/3 and 5×10^–15 m^–2/3, respectively). This scheme provides a reference for the accurate identification of fractional orbital angular momentum in turbulent environments.

Key words: vortex beam, fractional orbital angular momentum, atmospheric turbulence, deep learning

中图分类号:

O436

曹鹭萍, 夏勇. 大气湍流下高分辨率高带宽分数涡旋光束的探测[J]. 华东师范大学学报（自然科学版）, 2025, 2025(3): 51-60.

Luping CAO, Yong XIA. Detection of high-resolution high-bandwidth fractional vortex beams under atmospheric turbulence[J]. J* E* C* N* U* N* S*, 2025, 2025(3): 51-60.

图/表 8

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