Practical Phase-Modulation Stabilization in Quantum Key Distribution via Machine Learning
Jing-Yang Liu, Hua-Jian Ding, Chunhui Zhang, Shi-Peng Xie, Qin Wang · Physical Review Applied · 2019
In secure communication, maintaining system stability is crucial for practical quantum key distribution (QKD). To date, ``scanning-and-transmitting'' programs have been adopted to stabilize all QKD systems, reducing efficiency in key transmission. For this reason, the authors turn to a machine-learning model to predict variations in physical parameters and actively exercise real-time control over corresponding QKD devices, dramatically increasing the efficiency of key transmission. This approach should also be applicable to other QKD systems using any coding scheme or QKD protocol, and thus should impact large-scale application of quantum communication networks in the near future.