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arXiv 2512.04460physics.optics
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基于2.4公里自由空间光链路的相对波前误差校正:通过机器学习

Relative Wavefront Error Correction Over a 2.4 km Free-Space Optical Link via Machine Learning

School of Electrical Engineering and Telecommunications, University of New South Wales(新南威尔士大学电气与电信工程学院);Defence Science and Technology Group(国防科学与技术集团);International Centre for Radio Astronomy Research, University of Western Australia(西澳大利亚大学国际射电天文研究中心)

Nathan K. Long, Benjamin P. Dix-Matthews, Alex Frost, John Wallis, Ziqing Wang, Kenneth J. Grant, Robert Malaney

AI总结:

本文通过机器学习算法校正自由空间光链路中极化复用参考信标与信号间的波前误差,显著降低相位误差方差,并分析其对连续变量量子密钥分发的影响。

摘要:

在相干光学通信通过湍流大气信道时,参考信标可与包含信息的信号复用传输。通常假设两者波前畸变等同,但本文通过实验发现极化复用参考信标与信号在2.4公里大气链路中存在相对波前误差(WFE)。我们开发基于机器学习的波前校正算法,通过相位检索补偿观测到的WFE,使相对相位误差方差减少2/3。此外,我们分析了相对WFE在连续变量量子密钥分发(CV-QKD)中的额外噪声贡献,发现若未来CV-QKD实现采用类似本文报告的波前校正算法,安全密钥率可能增加一个数量级。

英文摘要:

In coherent optical communication across turbulent atmospheric channels, reference beacons can be multiplexed with information-encoded signals during transmission. In this case, it is commonly assumed that the wavefront distortion of the two is equivalent. In contrast to this assumption, we present experimental evidence of relative wavefront errors (WFEs) between polarization-multiplexed reference beacons and signals, after passing through a 2.4 km atmospheric link. We develop machine learning-based wavefront correction algorithms to compensate for observed WFEs, via phase retrieval, resulting in up to a 2/3 reduction in the relative phase error variance. Further, we analyze the excess noise contributions from relative WFEs in the context of continuous-variable quantum key distribution (CV-QKD), where our findings suggest that if future CV-QKD implementations employ wavefront correction algorithms similar to those reported here, an order of magnitude increase in secure key rates may be forthcoming.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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