Please wait a minute...
Chin. Phys. B, 2022, Vol. 31(2): 020306    DOI: 10.1088/1674-1056/ac2807
GENERAL Prev   Next  

Parameter estimation of continuous variable quantum key distribution system via artificial neural networks

Hao Luo(罗浩)1,3, Yi-Jun Wang(王一军)1, Wei Ye(叶炜)2, Hai Zhong(钟海)2,†, Yi-Yu Mao(毛宜钰)1, and Ying Guo(郭迎)1,‡
1 School of Automation, Central South University, Changsha 410083, China;
2 School of Computer Science and Engineering, Central South University, Changsha 410083, China;
3 College of Applied Science, Jiangxi University of Science and Technology, Ganzhou 341000, China
Abstract  Continuous-variable quantum key distribution (CVQKD) allows legitimate parties to extract and exchange secret keys. However, the tradeoff between the secret key rate and the accuracy of parameter estimation still around the present CVQKD system. In this paper, we suggest an approach for parameter estimation of the CVQKD system via artificial neural networks (ANN), which can be merged in post-processing with less additional devices. The ANN-based training scheme, enables key prediction without exposing any raw key. Experimental results show that the error between the predicted values and the true ones is in a reasonable range. The CVQKD system can be improved in terms of the secret key rate and the parameter estimation, which involves less additional devices than the traditional CVQKD system.
Keywords:  quantum key distribution      artificial neural networks      secret key rate      parameter estimation  
Received:  26 July 2021      Revised:  11 September 2021      Accepted manuscript online:  18 September 2021
PACS:  03.67.-a (Quantum information)  
  87.85.dq (Neural networks)  
Corresponding Authors:  Hai Zhong, Ying Guo     E-mail:  zhonghai@csu.edu.cn;yingguo@csu.edu.cn

Cite this article: 

Hao Luo(罗浩), Yi-Jun Wang(王一军), Wei Ye(叶炜), Hai Zhong(钟海), Yi-Yu Mao(毛宜钰), and Ying Guo(郭迎) Parameter estimation of continuous variable quantum key distribution system via artificial neural networks 2022 Chin. Phys. B 31 020306

[1] Bennett C H and Brassard G 1984 Proceedings of IEEE International Conference on Computers Systems, and Signal Processing, December 10-12, 1984, Bangalore, India, pp. 175-179
[2] Ruppert L, Usenko V C and Filip R 2014 Phys. Rev. A 90 062310
[3] Diamanti E and Leverrier A 2015 Entropy 17 6072
[4] Grosshans F and Grangier P 2002 Phys. Rev. Lett. 88 057902
[5] Lance A M, Symul T, Sharma V, Weedbrook C, Ralph T C and Lam P K 2005 Phys. Rev. Lett. 95 180503
[6] Grosshans F, Van Assche G, Wenger J, Brouri R, Cerf N J and Grangier P 2003 Nature 421 238
[7] Jouguet P, Kunz-Jacques S, Leverrier A, Grangier P and Diamanti E 2013 Nat. Photon. 7 378
[8] Lodewyck J, Bloch M, García-Patrón R, Fossier S, Karpov E, Diamanti E, Debuisschert T, Cerf N J, TualleBrouri R, McLaughlin S W and Grangier P 2007 Phys. Rev. A 76 042305
[9] Mao Y Y, Huang W T, Zhong H, Wang Y J, Qin H, Guo Y and Huang D 2020 New J. Phys. 22 083073
[10] Wu X D, Wang Y J, Guo Y, Zhong H and Huang D 2021 Phys. Rev. A 103 032604
[11] Liao Q, Xiao G, Zhong H and Guo Y 2020 New J. Phys. 22 083086
[12] Su X L, Wang W Z, Wang Y, Jia X J, Xie C D and Peng K C 2009 Europhys. Lett. 87 20005
[13] Su X L 2014 Chin. Sci. Bull. 59 1083
[14] M Navascués, Grosshans F and Acin A 2006 Phys. Rev. Lett. 97 190502
[15] Furrer F, Franz T, Berta M, Leverrier A, Scholz V B, Tomamichel M and Werner R F 2012 Phys. Rev. Lett. 109 100502
[16] García-Patrón R and Cerf N J 2006 Phys. Rev. Lett. 97 190503
[17] Leverrier A 2015 Phys. Rev. Lett. 114 070501
[18] Wang Y J, Mao Y Y, Huang W T, Huang D and Guo Y 2019 Opt. Express 27 25314
[19] Zeng G H 2010 Quantum private communication (Beijing:Higher Education Press and Springer Publishing Company) pp. 293-297
[20] Weedbrook C, Lance A M, Bowen W P, Symul T, Ralph T C and Lam P K 2004 Phys. Rev. Lett. 93 170504
[21] Brunner H H, Comandar L C, Karinou F, Bettelli S, Hillerkuss D, Fung F, Wang D W, Mikroulis S, Yi Q, Kuschnerov M, Poppe A, Xie C S and Peev M 2017 19th International Conference on Transparent Optical Networks (ICTON), July 2-6, 2017, Girona, Spain, pp. 1-4
[22] Guo Y, Xie C L, Huang P, Li J W, Zhang L, Huang D and Zeng G H 2018 Phys. Rev. A 97 052326
[23] Chai G, Cao Z W, Liu W Q, Wang S Y, Huang P and Zeng G H 2019 Phys. Rev. A 99 032326
[24] Guo Y, Zhou Z H, Wang X D, Wu X D, Zhang L and Huang D 2019 Int. J. Theor. Phys. 58 1613
[25] Wang X Y, Zhang Y C, Yu S and Guo H 2019 Quantum Inf. Process. 18 1
[26] Yang J, Xu B J, Peng X and Guo H 2012 Phys. Rev. A 85 052302
[27] Li Y, Huang P, Wang S Y, Wang T, Li D W and Zeng G H 2018 Phys. Lett. A 382 3253
[28] Garcia-Patron Sanchez Raul 2007 Quantum information with optical continuous variables:from bell tests to key distribution, Ph.D. Dissertation (Brussels:Université libre de Bruxelles)
[29] Chai G, Li D W, Cao Z W, Zhang M H, Huang P and Zeng G H 2020 Quantum Engineering 2 e37
[30] Gyongyosi L and Imre S 2018 Appl. Sci. 8 87
[31] Jiang X Q, Yang S Y, Huang P and Zeng G H 2018 IEEE Photon. J. 10 1
[32] Gyongyosi L and Imre S 2014 Advances in Photonics of Quantum Computing, Memory, and Communication VII, February 19, 2014, San Francisco, USA, pp. 28-40
[33] Liu B, Zhao B K, Zou D J, Wu C Q, Yu W R and You I 2013 Information and Communication Technology-EurAsia Conference, March, 2013, Yogyakarta, Indonesia, pp. 453-458
[34] Li D W, Huang P, Zhou Y M, Li Y and Zeng G H 2018 IEEE Photon. J. 10 1
[35] McCulloch W S and Pitts W 1943 The bulletin of mathematical biophysics volume 5 p. 115
[36] Wang W Y and Hoi-Kwong Lo 2019 Phys. Rev. A 100 062334
[37] Zhou M G, Liu Z P, Liu W B, Li C L, Bai J L, Xue Y R, Fu Y, Yin H L and Chen Z B 2021 arXiv:2108.02578v1[quant-ph]
[38] Beale H D, Demuth H B and Hagan M 1997 Neural network design (Boston:PWS Publishing Co.) Chapter 1 pp. 4-7
[39] Leverrier A, Grosshans F and Grangier P 2010 Phys. Rev. A 81 062343
[40] Fossier S, Diamanti E, Debuisschert T, Tuallebrouri R and Grangier P 2009 J. Phys. B:At. Mol. Opt. Phys. 42 114014
[41] Leverrier A and Grangier P 2009 Phys. Rev. Lett. 102 180504
[42] Thearle O, Assad S M and Symul T 2016 Phys. Rev. A 93 042343
[1] Feedback control and quantum error correction assisted quantum multi-parameter estimation
Hai-Yuan Hong(洪海源), Xiu-Juan Lu(鲁秀娟), and Sen Kuang(匡森). Chin. Phys. B, 2023, 32(4): 040603.
[2] Security of the traditional quantum key distribution protocolswith finite-key lengths
Bao Feng(冯宝), Hai-Dong Huang(黄海东), Yu-Xiang Bian(卞宇翔), Wei Jia(贾玮), Xing-Yu Zhou(周星宇), and Qin Wang(王琴). Chin. Phys. B, 2023, 32(3): 030307.
[3] Performance of phase-matching quantum key distribution based on wavelength division multiplexing technology
Haiqiang Ma(马海强), Yanxin Han(韩雁鑫), Tianqi Dou(窦天琦), and Pengyun Li(李鹏云). Chin. Phys. B, 2023, 32(2): 020304.
[4] Temperature characterizations of silica asymmetric Mach-Zehnder interferometer chip for quantum key distribution
Dan Wu(吴丹), Xiao Li(李骁), Liang-Liang Wang(王亮亮), Jia-Shun Zhang(张家顺), Wei Chen(陈巍), Yue Wang(王玥), Hong-Jie Wang(王红杰), Jian-Guang Li(李建光), Xiao-Jie Yin(尹小杰), Yuan-Da Wu(吴远大), Jun-Ming An(安俊明), and Ze-Guo Song(宋泽国). Chin. Phys. B, 2023, 32(1): 010305.
[5] Improvement of a continuous-variable measurement-device-independent quantum key distribution system via quantum scissors
Lingzhi Kong(孔令志), Weiqi Liu(刘维琪), Fan Jing(荆凡), Zhe-Kun Zhang(张哲坤), Jin Qi(齐锦), and Chen He(贺晨). Chin. Phys. B, 2022, 31(9): 090304.
[6] Practical security analysis of continuous-variable quantum key distribution with an unbalanced heterodyne detector
Lingzhi Kong(孔令志), Weiqi Liu(刘维琪), Fan Jing(荆凡), and Chen He(贺晨). Chin. Phys. B, 2022, 31(7): 070303.
[7] Short-wave infrared continuous-variable quantum key distribution over satellite-to-submarine channels
Qingquan Peng(彭清泉), Qin Liao(廖骎), Hai Zhong(钟海), Junkai Hu(胡峻凯), and Ying Guo(郭迎). Chin. Phys. B, 2022, 31(6): 060306.
[8] Quantum key distribution transmitter chip based on hybrid-integration of silica and lithium niobates
Xiao Li(李骁), Liang-Liang Wang(王亮亮), Jia-shun Zhang(张家顺), Wei Chen(陈巍), Yue Wang(王玥), Dan Wu (吴丹), and Jun-Ming An (安俊明). Chin. Phys. B, 2022, 31(6): 064212.
[9] Environmental parameter estimation with the two-level atom probes
Mengmeng Luo(罗萌萌), Wenxiao Liu(刘文晓), Yuetao Chen(陈悦涛), Shangbin Han(韩尚斌), and Shaoyan Gao(高韶燕). Chin. Phys. B, 2022, 31(5): 050304.
[10] Phase-matching quantum key distribution with light source monitoring
Wen-Ting Li(李文婷), Le Wang(王乐), Wei Li(李威), and Sheng-Mei Zhao(赵生妹). Chin. Phys. B, 2022, 31(5): 050310.
[11] Detecting the possibility of a type of photon number splitting attack in decoy-state quantum key distribution
Xiao-Ming Chen(陈小明), Lei Chen(陈雷), and Ya-Long Yan(阎亚龙). Chin. Phys. B, 2022, 31(12): 120304.
[12] Realization of simultaneous balanced multi-outputs for multi-protocols QKD decoding based onsilica-based planar lightwave circuit
Jin You(游金), Yue Wang(王玥), and Jun-Ming An(安俊明). Chin. Phys. B, 2021, 30(8): 080302.
[13] Practical decoy-state BB84 quantum key distribution with quantum memory
Xian-Ke Li(李咸柯), Xiao-Qian Song(宋小谦), Qi-Wei Guo(郭其伟), Xing-Yu Zhou(周星宇), and Qin Wang(王琴). Chin. Phys. B, 2021, 30(6): 060305.
[14] Continuous-variable quantum key distribution based on photon addition operation
Xiao-Ting Chen(陈小婷), Lu-Ping Zhang(张露萍), Shou-Kang Chang(常守康), Huan Zhang(张欢), and Li-Yun Hu(胡利云). Chin. Phys. B, 2021, 30(6): 060304.
[15] Blind parameter estimation of pseudo-random binary code-linear frequency modulation signal based on Duffing oscillator at low SNR
Ke Wang(王珂), Xiaopeng Yan(闫晓鹏), Ze Li(李泽), Xinhong Hao(郝新红), and Honghai Yu(于洪海). Chin. Phys. B, 2021, 30(5): 050708.
No Suggested Reading articles found!