论文标题
基于机器学习的联合极化和CV-QKD相位补偿
Machine learning based joint polarization and phase compensation for CV-QKD
论文作者
论文摘要
我们研究了一种机器学习方法，用于在高斯调制的CV-QKD系统中使用极化和相位，该方法在以5.5 dB衰减的安装纤维上测量的18小时内。
We investigated a machine learning method for joint estimation of polarization and phase for use in a Gaussian modulated CV-QKD system, over an 18 hour period measured on a installed fiber with 5.5 dB attenuation.
