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SPIE Conference on Quantum and Nonlinear Optics

A feasible two-step optimization method for continuous-variable quantum key distribution

Li Ma, Yang Li, Jie Yang, Yun Feng Shao, Yujie Luo, Wei Huang, Heng Wang, Chuang Zhou, Jinlong Hu, Shuai Zhang, Bingjie Xu

Published Nov 27, 2022• 0 citations
Publisher

Abstract

Continuous-variable quantum key distribution (CV-QKD) offers the advantages of high secret key rates in metropolitan areas. Optimization of modulation variance is an efficient method to improve the secret key rate of CVQKD system. However, in practical CV-QKD system, inevitable slight parameter fluctuation could occur after the modification of modulation variance, and controlling the modulation variance with arbitrary accuracy is also difficult. In this paper, we propose a two-step optimization for practical CV-QKD. The first step is to determine the optimal working state by combining the modulation variance optimization with error correction matrix optimization. The second step is to optimize the rate-adaptive reconciliation parameters to compensate the loss of secret key rate caused by inaccuracy modulation variance. Our results show that the secret key rate can be improved by 17.8% in comparison to one-step optimization method. Our method can be conveniently applied to CV-QKD protocol with homodyne and heterodyne detection, which will pave the way to the deployment of high stable and high performance for CV-QKD.

DOI
10.1117/12.2643892

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Continuous-variable quantum key distribution (CV-QKD) offers the advantages of high secret key rates in metropolitan areas. Optimization of modulation variance is an efficient method to improve the secret key rate of CVQKD system. However, in practical CV-QKD system, inevitable slight parameter fluctuation could occur after the modification of modulation variance, and controlling the modulation variance with arbitrary accuracy is also difficult. In this paper, we propose a two-step optimization for practical CV-QKD. The first step is to determine the optimal working state by combining the modulation variance optimization with error correction matrix optimization. The second step is to optimize the rate-adaptive reconciliation parameters to compensate the loss of secret key rate caused by inaccuracy modulation variance. Our results show that the secret key rate can be improved by 17.8% in comparison to one-step optimization method. Our method can be conveniently applied to CV-QKD protocol with homodyne and heterodyne detection, which will pave the way to the deployment of high stable and high performance for CV-QKD.
The distribution of symmetric keys over optical networks is possible through the implementation of continuous variables quantum key distribution (CV-QKD) systems. Despite the rate of key extraction in CV-QKD being maximized for Gaussian modulation (GM), its practical implementation is demanding due to the finite extinction ratio of the electro-optic modulators. The use of discrete modulation (DM) allows for a simpler practical implementation. Provided that higher-order constellations can be used, DM can approximate the performances of GM. Higher-order DM has been shown to be feasible experimentally in CV-QKD. Notwithstanding, such implementations are usually obtained in offline without applying all the post-processing steps, particularly the information reconciliation, turning the validity of the results dependent on a null frame error rate after information reconciliation. Besides that, a fixed value is typically assumed for the reconciliation efficiency value, being the modulation variance optimized under such assumptions. This disregarding the dependency of the reconciliation efficiency parameter on the method for information reconciliation and on the modulation variance. In this work we study the impact that such assumptions have on the optimization of the modulation variance in a CV-QKD system using probabilistic shaped higher-order DM. Moreover, we analyse how optimizing the modulation variance can affect the extraction key rates of symmetric keys at the output of the CV-QKD system. Besides the assumptions of null frame error rate and of the reconciliation efficiency, we study how different code rates may also affect the optimization of the modulation variance. This considering M-symbol quadrature amplitude modulation and multidimensional reconciliation.
Continuous-variable quantum key distribution (CV-QKD) is a promising quantum-safe alternative to classical asymmetric cryptography that enables two authenticated parties to establish a shared secret over a potentially eavesdropped quantum channel. A key step in CV-QKD post-processing is information reconciliation, which leverages forward error correction (FEC) techniques to extract identical bit strings from noisy correlated data. In this work, we analyze the strict limitations on operating distance that are imposed by constant-rate FEC, severely limiting the practicability of CV-QKD systems in deployed optical networks. To overcome the distance limitations, we evaluate three strategies: (i) tuning modulation variance, (ii) adding controlled amounts of trusted detector loss, and (iii) the use of rate-adaptive FEC. All approaches are validated experimentally, compared in terms of performance, and we discuss implementation aspects. Our results show that while methods (i) and (ii) extend the operational distance of constant-rate FEC without the need for additional hardware components, they incur a significant penalty in secret key rate (SKR). In contrast, rate-adaptive FEC enables CV-QKD operation with performance close to the asymptotic SKR over a wide range of distances, provided that the reconciliation efficiency is chosen appropriately.
Continuous-variable quantum key distribution (CV-QKD) has been proposed as a method for securely exchanging keys to protect against the security concerns caused by potential advancements in quantum computing. In addition to optical fibre transmission, the free-space optical (FSO) channel is an interesting channel for CV-QKD, as it is possible to share keys over this channel wirelessly. The instability of the FSO channel caused by turbulence-induced fading, however, can cause a degradation in the system's performance. One of the most important aspects of CV-QKD is the reconciliation step, which significantly impacts the performance of the CV-QKD system. Hence, rate-adaptive reconciliation is necessary for CV-QKD over FSO to combat the fluctuations in the channel and improve secret key rates (SKRs). Therefore, in this paper, we simulate the impact of discrete modulation on the reconciliation efficiency and consider the use ofddd-dimensional reconciliation withd>8d > 8d>8to mitigate this impact, improving reconciliation efficiencies by up to 3.4%. We validate our results by experimentally demonstrating CV-QKD over a turbulent FSO link and demonstrate SKR gains by up to 165%. Furthermore, we optimise the reconciliation efficiency for FSO links, achieving additional SKR gains of up to 7.6%.
In the continuous-variable quantum key distribution (CV-QKD) system, the secret key rate (SKR) and transmission distance are important factors to evaluate the quality of system. Numerical methods are commonly employed to compute SKR of QKD systems in practice, but it is difficult to find the optimal parameter to enhance SKR. In this paper, we propose a machine learning-based parameter optimization scheme of CV-QKD. The proposed scheme applies the genetic algorithm-back propagation neural network (GA-BPNN) to CV-QKD to learn the mapping relationship between SKR and modulation variance. According to the property that the mapping relationship is a concave function, the optimal modulation variance can be determined by bisection, and then SKR can be enhanced. Simulation results demonstrate that the proposed scheme can enhance SKR and transmission distance.
Continuous-variable quantum key distribution (CV-QKD) provides an effective way to obtain the high secret key rate, but is limited by practical techniques. To overcome this limitation, we investigate the performance of CV-QKD protocols when non-Gaussian operations are applied to both sides of the channels, including photon subtraction and addition, and photon catalysis. A comparison is also made between Gaussian modulation and non-Gaussian modulation. We show that the optimal transmission distance cannot be improved by non-Gaussian modulation at the sender's side, but it can be improved by single-photon catalysis at the receiver's side. For a given modulation variance that exceeds a certain threshold, the performance of the zero-photon catalysis at the sender's side is the best when compared with other non-Gaussian modulations (except single-photon catalysis at the receiver's side), and it can always reach the optimal distance. Our paper will provide a useful insight for the use of non-Gaussian modulation to other CV-QKD protocols.