Get started
Work

Multidimensional reconciliation scheme using deep learning in continuous-variable quantum key distribution

Year: 2025
Type: article
Abstract: Information reconciliation is a significant stage in continuous-variable quantum key distribution (CV-QKD) systems as it directly affects the performance of the CV-QKD systems including secret key rate and secure transmission distance. This paper proposes a multidimensional reconciliation scheme using deep learning in CV-QKD systems. Firstly, different neural networks are constructed to obtain the norm information. Secondly, a multidimensional reconciliation scheme with deep learning assisted norm information is proposed which no longer needs to transmit the norm information through the authenticated classical public channel. Finally, simulation results and performance analysis show that, compared with the traditional multidimensional reconciliation scheme, the multidimensional reconciliation scheme with deep learning assisted norm information can decrease the communication traffic to a certain extent.
DOI: 10.1088/1367-2630/adcf45
Authors: Yan Feng, Jiangliang Jin, Kun Zhang, Zhipeng Chen, Xue-Qin Jiang, Peng Huang, Guihua Zeng
Institutions: Shanghai Dianji University, Donghua University, Soochow University, Shanghai Jiao Tong University, State Key Laboratory of Advanced Optical Communication Systems and Networks, State Key Laboratory of Advanced Optical Communication Systems and Networks
Language: English
Open Access status: gold
Estimated APC paid: $2,610
OpenAlex ID: W4409671555
FWCI: 1.278
Cites: 49
Cited by: 3
Related to: 10