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Analysis of atmospheric effects on the continuous variable quantum key distribution |
Tao Liu(刘涛)1,2,3,†, Shuo Zhao(赵硕)1, Ivan B. Djordjevic4, Shuyu Liu(刘舒宇)1, Sijia Wang(王思佳)1, Tong Wu(吴彤)1, Bin Li(李斌)1, Pingping Wang(王平平)1, and Rongxiang Zhang(张荣香)5 |
1 Department of Electronic and Communication Engineering, North China Electric Power University, Baoding 071003, China; 2 Hebei Key Laboratory of Power Internet of Things Technology, North China Electric Power University, Baoding 071003, China; 3 Baoding Key Laboratory of Optical Fiber Sensing and Optical Communication Technology, North China Electric Power University, Baoding 071003, China; 4 Department of Electrical and Computer Engineering, University of Arizona, 1230 E Speedway Blvd., Tucson, Arizona 85721, USA; 5 College of Physics Science and Technology, Hebei University, Baoding 071002, China |
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Abstract Atmospheric effects have significant influence on the performance of a free-space optical continuous variable quantum key distribution (CVQKD) system. In this paper, we investigate how the transmittance, excess noise and interruption probability caused by atmospheric effects affect the secret-key rate (SKR) of the CVQKD. Three signal wavelengths, two weather conditions, two detection schemes, and two types of attacks are considered in our investigation. An expression aims at calculating the interruption probability is proposed based on the Kolmogorov spectrum model. The results show that a signal using long working wavelength can propagate much further than that of using short wavelength. Moreover, as the wavelength increases, the influence of interruption probability on the SKR becomes more significant, especially within a certain transmission distance. Therefore, interruption probability must be considered for CVQKD by using long-signal wavelengths. Furthermore, different detection schemes used by the receiver will result in different transmission distances when subjected to individual attacks and collective attacks, respectively.
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Received: 03 January 2022
Revised: 10 April 2022
Accepted manuscript online: 28 April 2022
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PACS:
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03.67.Hk
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(Quantum communication)
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42.68.Bz
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(Atmospheric turbulence effects)
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Fund: Project supported by the National Natural Science Foundation of China (Grant No. 62071180) and Fundamental Research Funds for the Central Universities, China (Grant No. 2020MS099). |
Corresponding Authors:
Tao Liu
E-mail: taoliu@ncepu.edu.cn
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Cite this article:
Tao Liu(刘涛), Shuo Zhao(赵硕), Ivan B. Djordjevic, Shuyu Liu(刘舒宇), Sijia Wang(王思佳), Tong Wu(吴彤), Bin Li(李斌), Pingping Wang(王平平), and Rongxiang Zhang(张荣香) Analysis of atmospheric effects on the continuous variable quantum key distribution 2022 Chin. Phys. B 31 110303
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[1] Miao E L, Han Z F, Gong S S, Zhang T, Diao D S and Guo G C 2005 New J. Phys. 7 215 [2] Peng C Z, Yang T, Bao X H, Zhang J, Jin X M, Feng F Y, Yang B, Yang J, Yin J, Zhang Q, Li N, Tian B L and Pan J W 2005 Phys. Rev. Lett. 94 150501 [3] Raj A, Selvi J and Durairaj S 2015 Appl. Opt. 54 802 [4] Cui X Z, Yin X L, Chang H, Zhang Z C, Wang Y J and Wu G H 2017 Chin. Phys. B 26 114207 [5] Andrews L C and Phillips R L 2005 Laser Beam Propagation through Random Media (2nd edn.)(Washingon: SPIE PRESS) pp. 1-783 [6] Fante R L 1980 Proc. IEEE 68 1424 [7] Barbier P R, Rush D W, Plett M L and Polak-Dingels P 1998 SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, October 20, 1998, San Diego,CA, United States, 93 [8] Vasylyev D, Semenov A A and Vogel W 2019 Int. J. Theor. Phys. 58 3746 [9] Chai G, Liang K X, Liu W Q, Huang P, Cao Z W and Zeng G H 2019 Int. J. Theor. Phys. 58 3746) [10] Zhao W, Liao Q, Huang D and Guo Y 2019 Quantum. Inf. Proc. 18 39 [11] Wang S Y, Huang P, Wang T and Zeng G H 2018 New. J. Phys. 20 083037 [12] Mahlobogwane Z, Owolawi P A and Sokoya O 2018 2018 International Conference on Advances in Big Data, Computing and Data Communication Systems (icABCD), August 6-7, 2018, Durban, South Africa, p. 1 [13] Liu T, Zhang J Z, Lei Y X, Zhang R X and Sun J F 2019 J. Mod. Opt. 66 986 [14] Xu J C, Zhang Y X, Wang J Y and Jia J J 2011 Optik 122 586 [15] Hughes R J and Nordholt J E 2017 Nat. Photon. 11 456 [16] Liao S K, Yong H L, Liu C, et al. 2017 Nat. Photon. 11 509 [17] Büchter K F, Herrmann H, Langrock C, Fejer M M and Sohler W 2009 Opt. Lett. 34 470 [18] Miguel N and Antonio A 2005 Phys. Rev. Lett. 94 020505 [19] Lodewyck J, Bloch M, García-Patrón R, Fossier S, Karpov E, Diamanti E, Debuisschert T, Cerf N J, Tualle-Brouri R, McLaughlin S W and Grangier P 2007 Phys. Rev. A 76 042305 [20] Qu Z and Djordjevic I B 2018 IEEE. Photon. J. 10 1943 [21] Liu W Q, Peng J Y, Huang P, Huang D and Zeng G H 2017 Opt. Express 25 19429 [22] Huang B, Huang Y M and Peng Z M 2019 Opt. Express 27 20621 [23] Djordjevic I B 2019 IEEE. Access 5 147399 [24] Ricklin J C, Hammel S M, Eaton F D and Lachinova S 2006 J. Opt.Fiber Commun. Rep. 3 111 [25] Kim I I, Mcarthur B and Korevaar E J 2001 Proc. SPIE 4214 [26] Qi B, Lougovski P, Pooser R, Grice W and Bobrek M 2015 Phys. Rev. X 5 041009 [27] Liorni C, Kampermann H and Bruss D 2019 New J. Phys. 21 093055 [28] Bedington R, Arrazola J M and Ling A 2017 Npj. Quantum. Inform. 3 30 |
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