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Study of practical state-preparation error tolerant reference-frame-independent quantum key distribution protocol

Zhou Yang Ma Xiao Zhou Xing-Yu Zhang Chun-Hui Wang Qin

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Study of practical state-preparation error tolerant reference-frame-independent quantum key distribution protocol

Zhou Yang, Ma Xiao, Zhou Xing-Yu, Zhang Chun-Hui, Wang Qin
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  • Quantum key distribution (QKD) enables the establishment of shared keys between two distant users, Alice and Bob, based on the fundamental principles of quantum mechanics, and it has proven to possess information-theoretic security. In most of QKD systems, Alice and Bob require a shared reference frame, and real-time calibration of the reference frame increases system costs and reduces its performance. Fortunately, the reference-frame-independent QKD protocol has been proposed, overcoming reference-frame drift issues and receiving widespread attention. However, in practical QKD systems, the non-ideal characteristics of realistic devices introduce certain inconsistency between the theory and the practice. In real-world quantum key distribution systems, device imperfections can lead to security vulnerabilities, thereby reducing system security. For example, imperfections in the encoding apparatus at the source end may result in errors in the quantum states. The inherent defects in the detection part may cause after-pulse effects and dead-time effects, thus reducing the key rate. Therefore, in this work, we propose a practical state-preparation error tolerant reference-frame-independent quantum key distribution protocol by taking imperfections in both the source and the detectors into account. Moreover, a three-intensity decoy-state scheme for modeling analysis and numerical simulations is employed. In this protocol, we reduce the influence of state-preparation errors on the key rate by utilizing virtual state methods to precisely estimate the phase-error rate. Furthermore, by characterizing the effects of after-pulses and dead-time on the key rate, our protocol exhibits higher robustness and can effectively address issues related to detector imperfections. This approach can also be extended to other quantum key distribution protocols with higher security levels, such as measurement-device-independent quantum key distribution protocol and twin-field quantum key distribution, further mitigating the influence of device imperfections on practical implementation of QKD system. Therefore, our present work provide important reference value for putting the quantum key distributions into practical application.
      Corresponding author: Wang Qin, qinw@njupt.edu.cn
    • Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 12074194, 11774180), the Leading-edge Technology Program of Natural Science Foundation of Jiangsu Province, China (Grant No. BK20192001), the Industrial Prospect and Key Core Technology Projects of Key R & D Program of Jiangsu Province, China (Grant No. BE2022071), and the Postgraduate Research & Practice Innovation Program of Jiangsu Province, China (Grant Nos. KYCX20_0726, KYCX23_1039).
    [1]

    Bennett C H, Brassard G 1984 Proceedings of IEEE International Conference on Computers, System and Signal Processing (Vol. 1 of 3) (Bangalore: IEEE) pp175–179

    [2]

    Brassard G, Lütkenhaus N, Mor T, Sanders B C 2000 Phys. Rev. Lett. 85 1330Google Scholar

    [3]

    Yuan Z, Plews A, Takahashi R, Doi K, Tam W, Sharpe A W, Dixon A R, Lavelle E, Dynes J F, Murakami A, Kujiraoka M, Lucamarini M, Tanizawa Y, Sato H, Shields A J 2018 J. Light. Technol. 36 16

    [4]

    Boaron A, Korzh B, Houlmann R, Boso G, Rusca D, Gray S, Li M, Nolan D, Martin A, Zbinden H 2018 Appl. Phys. Lett. 112 17Google Scholar

    [5]

    Minder M, Pittaluga M, Roberts G, Lucamarini M, Dynes J F, Yuan Z L, Shields A J 2019 Nat. Photonics 13 5Google Scholar

    [6]

    Liu Y, Yu Z W, Zhang W, Guan J Y, Chen J P, Zhang C, Hu X L, Li H, Jiang C, Lin J, Chen T Y, You L, Wang Z, Wang X B, Zhang Q, Pan J W 2019 Phys. Rev. Lett. 123 100505Google Scholar

    [7]

    Bennett C H, Bessette F, Brassard G, Salvail L, Smolin J 1992 J Cryptol 5 3Google Scholar

    [8]

    Kurtsiefer C, Zarda P, Halder M, Weinfurter H, Gorman P M, Tapster P R, Rarity J G 2002 Nature 419 450Google Scholar

    [9]

    Laing A, Scarani V, Rarity J G, O’Brien J L 2018 Phys. Rev. A 82 012304Google Scholar

    [10]

    Gottesman D, Lo H K, Lütkenhaus N, Preskill J 2004 Quantum Inf. Comput. 4 325Google Scholar

    [11]

    Tamaki K, Curty M, Kato G, Lo H K, Azuma K 2014 Phys. Rev. A 90 052314Google Scholar

    [12]

    Wang C, Sun S H, Ma X C, Tang G Z, Liang L M 2015 Phys. Rev. A 92 042319Google Scholar

    [13]

    Xu F H, Wei K J, Sajeed S, Kaiser S, Sun S H, Tang Z Y, Qian L, Makarov V, Lo H K 2015 Phys. Rev. A 92 032305Google Scholar

    [14]

    Tang Z Y, Wei K J, Bedroya O, Qian L, Lo H K 2016 Phys. Rev. A 93 042308Google Scholar

    [15]

    Zhou X Y, Ding H J, Zhang C H, Li J, Zhang C M, Wang Q 2020 Opt. Lett. 45 4176Google Scholar

    [16]

    Fan Y G J, Wang C, Wang S, Yin Z Q, Liu H, Chen W, He D Y, Han Z F, Guo G C 2018 Phys. Rev. Appl. 10 064032Google Scholar

    [17]

    Campbell L 1992 Rev. Sci. Instrum. 63 5794Google Scholar

    [18]

    Rusca D, Boaron A, Grünenfelder F, Martin A, Zbinden H 2018 Appl. Phys. Lett. 112 171104Google Scholar

    [19]

    莫小范 2006 博士毕业论文 (合肥: 中国科学技术大学)

    Mo X F 2006 Ph. D. Dissertation (Hefei: University of Science and Technology of China

    [20]

    Wang W J, Zhou X Y, Zhang C H, Ding H J, Wang Q 2022 Quantum Inf. Process 21 1Google Scholar

    [21]

    范元冠杰 2020 博士毕业论文 (合肥: 中国科学技术大学)

    Fan Y G J 2020 Ph. D. Dissertation (Hefei: University of Science and Technology of China

    [22]

    Wang X B 2005 Phys. Rev. Lett. 94 30503Google Scholar

    [23]

    马啸, 孙铭铄, 刘靖阳, 丁华建, 王琴 2022 物理学报 71 030301Google Scholar

    Ma X, Sun M S, Liu J Y, Ding H J, Wang Q 2022 Acta Phys. Sin. 71 030301Google Scholar

    [24]

    Fung C F, Tamaki K, Qi B, Lo H K, Ma X F 2009 Quantum Inf. Comput. 9 1533Google Scholar

    [25]

    Sun S H, Xu F H 2021 New J. Phys. 23 023011Google Scholar

    [26]

    Zhou Y H, Yu Z W, Wang X B 2016 Phys. Rev. A 93 042324Google Scholar

    [27]

    Zhang C H, Zhang C M, Guo G C, Wang Q 2018 Opt. Express 26 4219Google Scholar

    [28]

    Zhou X Y, Zhang C H, Zhang C M, Wang Q 2017 Phys. Rev. A 96 052337Google Scholar

    [29]

    Jiang C, Yu Z W, Hu X L, Wang X B 2021 Phys. Rev. A 103 012402Google Scholar

    [30]

    Huang L Y, Zhang Y C, Yu S 2021 Chin. Phys. Lett. 38 040301Google Scholar

    [31]

    Lucamarini M, Yuan Z L, Dynes J F, Shields A J 2018 Nature 557 400Google Scholar

    [32]

    Wang X B, Yu Z W, Hu X L 2018 Phys. Rev. A 98 062323Google Scholar

  • 图 1  (a) 基于态制备缺陷$ \delta $的RFI协议以及LT-RFI协议的密钥生成率图; (b)基于后脉冲效应$ {P_{{\text{ap}}}} $的RFI协议以及LT-RFI协议的密钥生成率图

    Figure 1.  (a) Key generation rates of the RFI protocol and LT-RFI protocol based on state preparation flaws $ \delta $; (b) the key generation rates of the RFI protocol and LT-RFI protocol based afterpulse effect $ {P_{{\text{ap}}}} $.

    图 2  基于态制备缺陷和后脉冲效应的RFI 协议以及LT-RFI协议的密钥生成率图

    Figure 2.  Key generation rates of the RFI protocol and LT-RFI protocol based on state preparation flaws and after-pulse effect.

    图 3  基于态制备缺陷和后脉冲效应的RFI 协议与LT-RFI 协议的Eve获取的信息量

    Figure 3.  Information leakage to Eve of the RFI protocols and LT-RFI protocols based on state preparation flaws and after-pulse effect.

    图 4  基于不同设备缺陷的RFI协议以及LT-RFI协议密钥生成率图

    Figure 4.  Key generation rates of the RFI protocol and LT-RFI protocol based on different defects in equipments.

    表 1  基于后脉冲效应和死时间效应的LT-RFI协议仿真参数列表

    Table 1.  Parameter list used in simulation of LT-RFI protocol based on after-pulse effect and dead time effect.

    Bob探测器
    暗计数率$ {P_{{\text{dc}}}} $
    Bob探测器
    效率$ {\eta _{{\text{Bob}}}} $
    系统纠错
    系数f
    Alice发送的
    总脉冲数N
    系统
    重复频率F
    信道损耗系数
    $ \alpha $/(dB·km–1)
    系统
    本底误码$ {e_{\text{d}}} $
    3×10–6 0.145 1.16 1012 109 0.2 0.0015
    DownLoad: CSV
  • [1]

    Bennett C H, Brassard G 1984 Proceedings of IEEE International Conference on Computers, System and Signal Processing (Vol. 1 of 3) (Bangalore: IEEE) pp175–179

    [2]

    Brassard G, Lütkenhaus N, Mor T, Sanders B C 2000 Phys. Rev. Lett. 85 1330Google Scholar

    [3]

    Yuan Z, Plews A, Takahashi R, Doi K, Tam W, Sharpe A W, Dixon A R, Lavelle E, Dynes J F, Murakami A, Kujiraoka M, Lucamarini M, Tanizawa Y, Sato H, Shields A J 2018 J. Light. Technol. 36 16

    [4]

    Boaron A, Korzh B, Houlmann R, Boso G, Rusca D, Gray S, Li M, Nolan D, Martin A, Zbinden H 2018 Appl. Phys. Lett. 112 17Google Scholar

    [5]

    Minder M, Pittaluga M, Roberts G, Lucamarini M, Dynes J F, Yuan Z L, Shields A J 2019 Nat. Photonics 13 5Google Scholar

    [6]

    Liu Y, Yu Z W, Zhang W, Guan J Y, Chen J P, Zhang C, Hu X L, Li H, Jiang C, Lin J, Chen T Y, You L, Wang Z, Wang X B, Zhang Q, Pan J W 2019 Phys. Rev. Lett. 123 100505Google Scholar

    [7]

    Bennett C H, Bessette F, Brassard G, Salvail L, Smolin J 1992 J Cryptol 5 3Google Scholar

    [8]

    Kurtsiefer C, Zarda P, Halder M, Weinfurter H, Gorman P M, Tapster P R, Rarity J G 2002 Nature 419 450Google Scholar

    [9]

    Laing A, Scarani V, Rarity J G, O’Brien J L 2018 Phys. Rev. A 82 012304Google Scholar

    [10]

    Gottesman D, Lo H K, Lütkenhaus N, Preskill J 2004 Quantum Inf. Comput. 4 325Google Scholar

    [11]

    Tamaki K, Curty M, Kato G, Lo H K, Azuma K 2014 Phys. Rev. A 90 052314Google Scholar

    [12]

    Wang C, Sun S H, Ma X C, Tang G Z, Liang L M 2015 Phys. Rev. A 92 042319Google Scholar

    [13]

    Xu F H, Wei K J, Sajeed S, Kaiser S, Sun S H, Tang Z Y, Qian L, Makarov V, Lo H K 2015 Phys. Rev. A 92 032305Google Scholar

    [14]

    Tang Z Y, Wei K J, Bedroya O, Qian L, Lo H K 2016 Phys. Rev. A 93 042308Google Scholar

    [15]

    Zhou X Y, Ding H J, Zhang C H, Li J, Zhang C M, Wang Q 2020 Opt. Lett. 45 4176Google Scholar

    [16]

    Fan Y G J, Wang C, Wang S, Yin Z Q, Liu H, Chen W, He D Y, Han Z F, Guo G C 2018 Phys. Rev. Appl. 10 064032Google Scholar

    [17]

    Campbell L 1992 Rev. Sci. Instrum. 63 5794Google Scholar

    [18]

    Rusca D, Boaron A, Grünenfelder F, Martin A, Zbinden H 2018 Appl. Phys. Lett. 112 171104Google Scholar

    [19]

    莫小范 2006 博士毕业论文 (合肥: 中国科学技术大学)

    Mo X F 2006 Ph. D. Dissertation (Hefei: University of Science and Technology of China

    [20]

    Wang W J, Zhou X Y, Zhang C H, Ding H J, Wang Q 2022 Quantum Inf. Process 21 1Google Scholar

    [21]

    范元冠杰 2020 博士毕业论文 (合肥: 中国科学技术大学)

    Fan Y G J 2020 Ph. D. Dissertation (Hefei: University of Science and Technology of China

    [22]

    Wang X B 2005 Phys. Rev. Lett. 94 30503Google Scholar

    [23]

    马啸, 孙铭铄, 刘靖阳, 丁华建, 王琴 2022 物理学报 71 030301Google Scholar

    Ma X, Sun M S, Liu J Y, Ding H J, Wang Q 2022 Acta Phys. Sin. 71 030301Google Scholar

    [24]

    Fung C F, Tamaki K, Qi B, Lo H K, Ma X F 2009 Quantum Inf. Comput. 9 1533Google Scholar

    [25]

    Sun S H, Xu F H 2021 New J. Phys. 23 023011Google Scholar

    [26]

    Zhou Y H, Yu Z W, Wang X B 2016 Phys. Rev. A 93 042324Google Scholar

    [27]

    Zhang C H, Zhang C M, Guo G C, Wang Q 2018 Opt. Express 26 4219Google Scholar

    [28]

    Zhou X Y, Zhang C H, Zhang C M, Wang Q 2017 Phys. Rev. A 96 052337Google Scholar

    [29]

    Jiang C, Yu Z W, Hu X L, Wang X B 2021 Phys. Rev. A 103 012402Google Scholar

    [30]

    Huang L Y, Zhang Y C, Yu S 2021 Chin. Phys. Lett. 38 040301Google Scholar

    [31]

    Lucamarini M, Yuan Z L, Dynes J F, Shields A J 2018 Nature 557 400Google Scholar

    [32]

    Wang X B, Yu Z W, Hu X L 2018 Phys. Rev. A 98 062323Google Scholar

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Publishing process
  • Received Date:  15 July 2023
  • Accepted Date:  07 September 2023
  • Available Online:  21 September 2023
  • Published Online:  20 December 2023

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