搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

人工智能赋能量子通信与量子传感系统

徐佳歆 徐乐辰 刘靖阳 丁华建 王琴

引用本文:
Citation:

人工智能赋能量子通信与量子传感系统

徐佳歆, 徐乐辰, 刘靖阳, 丁华建, 王琴

Research Progress on Artificial Intelligence Empowered Quantum Communication and Quantum Sensing Systems

XU Jiaxin, XU Lechen, LIU Jingyang, DING Huajian, WANG Qin
Article Text (iFLYTEK Translation)
PDF
导出引用
  • 量子通信和量子传感分别利用量子系统的独特特性,比如量子态的叠加性或量子纠缠特性等,能够实现信息论安全的通信以及对物理量的高精度测量。量子通信和量子传感,作为当前最接近实用化的两种量子技术,成为学术界的研究热点。然而,这两种技术在走向实用化的过程中也面临着诸多挑战,例如:设备缺陷导致现实安全性问题,环境噪声干扰大导致测量精度降低等,使得系统的大规模部署受到严重限制。人工智能凭借其强大的算力和数据处理能力,已经在通信、计算和成像等领域发挥着重要作用。本文主要综述人工智能与量子通信和量子传感交叉领域的发展现状,主要包括人工智能在量子密钥分发、量子存储、量子网络、量子传感等方向的具体结合与应用,为提升系统的可靠性、安全性、智能化与可扩展性等方面提供了强有力的保障。接着,本文分析了人工智能在赋能量子通信和量子传感系统中目前存在的问题,最后,本文对该领域未来的发展前景进行了展望和讨论。
    Quantum communication and quantum sensing, which leverage the unique characteristics of quantum systems, enable information-theoretically secure communication and high-precision measurement of physical quantities. They have attracted significant attention in recent research. However, they both face numerous challenges on the path to practical application. For instance, device imperfections may lead to security vulnerability, and environmental noise may significantly reduce measurement accuracy. Traditional solutions often involve high computational complexity, long processing times, and substantial hardware resource requirements, posing major obstacles to the large-scale deployment of quantum communication and quantum sensing networks. Artificial intelligence (AI), as a major technological advancement in current scientific landscape, offers powerful data processing and analytical capabilities, providing new ideas and methods for optimizing and enhancing quantum communication and sensing systems.
    Significant progresses have been made in applying AI to quantum communication and sensing, injecting new vitality into these cutting-edge technologies. In quantum communication, AI techniques have greatly improved the performance and security of quantum key distribution, quantum memory, and quantum networks through parameter optimization, real-time feedback control, and attack detection. In quantum sensing, quantum sensing technology enables ultra-high sensitivity detection of physical quantities such as time and magnetic fields. The introduction of AI has opened up new avenues for achieving highprecision and high-sensitivity quantum measurements. With AI, sensor performance is optimized, and measurement accuracy is further enhanced through data analysis.
    This paper also analyzes the current challenges in applying AI to empower quantum communication and sensing systems, such as implementing efficient algorithm deployment and system feedback control under limited computational resources, and addressing complex task environments, dynamically changing scenarios, and multi-task coordination requirements. Finally, the paper discusses and envisions future development prospects in this field.
  • [1]

    Das Sarma S, Deng D L, Duan L M 2019 Phys. Today 72 48

    [2]

    Carleo G, Cirac I, Cranmer K, Daudet L, Schuld M, Tishby N, Vogt-Maranto L, Zdeborová L 2019 Rev. Mod. Phys 91 045002

    [3]

    Wallnöfer J, Melnikov A A, Dür W, Briegel H J 2020 PRX Quantum 1 010301

    [4]

    Kaelbling L P, Littman M L, Moore A W 1996 J. Artif. Intell. Res. 4 237

    [5]

    LeCun Y, Bengio Y, Hinton G 2015 Nature 521 436

    [6]

    Ma W, Liu Z, Kudyshev Z A, Boltasseva A, Cai W, Liu Y 2021 Nat. Photonics 15 77

    [7]

    Jain A K, Mao J, Mohiuddin K M 1996 Computer 29 31

    [8]

    Gers F A, Schmidhuber J, Cummins F 2000 Neural Comput. 12 2451

    [9]

    Cleveland W S, Devlin S J, Grosse E 1988 J. Econom. 37 87

    [10]

    Kotsiantis S B 2013 Artif. Intell. Rev. 39 261

    [11]

    Snoek J, Larochelle H, Adams R P 2012 Adv. Neural Inf. Process. Syst. 25

    [12]

    Xu R, Wunsch D 2005 IEEE Trans. Neural Netw 16 645

    [13]

    Raymer M L, Punch W F, Goodman E D, Kuhn L A, Jain A K 2000 IEEE Trans. Evol. Comput. 4 164

    [14]

    Dietterich T G 2000 Springer pp1-15

    [15]

    Bennett C H, Brassard G, Proceeding of the IEEE International Conference on Computers, Systems and Signal Processing, 1984, pp175-179

    [16]

    Ekert A K 1991 Phys. Rev. Lett. 67 661

    [17]

    Bennett C H, Brassard G, Mermin N D 1992 Phys. Rev. Lett. 68 557

    [18]

    Bennett C H 1992 Phys. Rev. Lett. 68 3121

    [19]

    Acín A, Brunner N, Gisin N, Massar S, Pironio S, Scarani V 2007 Phys. Rev. Lett. 98 230501

    [20]

    Lo H K, Curty M, Qi B 2012 Phys. Rev. Lett. 108 130503

    [21]

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

    [22]

    Zeng P, Zhou H, Wu W, Ma X 2022 Nat. Commun. 13 3903

    [23]

    Xie Y M, Lu Y S, Weng C X, Cao X Y, Jia Z J, Bao Y, Wang Y, Fu Y, Yin H L, Chen Z B 2022 PRX Quantum 3 020315

    [24]

    Ding H J, Liu J Y, Zhang C M, Wang Q 2020 Quantum Inf. Process. 19 1

    [25]

    Wang W, Lo H K 2019 Phys. Rev. A 100 062334

    [26]

    Lu F Y, Yin Z Q, Wang C, Cui C H, Teng J, Wang S, Chen W, Huang W, Xu B J, Guo G C, Han Z F 2019 J. Opt. Soc. Am. B 36 B92

    [27]

    Dong Q, Huang G, Cui W, Jiao R 2022 Quantum Inf. Process. 21 233

    [28]

    Liu J Y, Ding H J, Zhang C M, Xie S P, Wang Q 2019 Phys. Rev. Appl. 12 014059

    [29]

    Zhang S, Liu J, Zhang C, Zhou X, Wang Q 2021 Entropy 23 1242

    [30]

    Liu J Y, Jiang Q Q, Ding H J, Ma X, Sun M S, Xu J X, Zhang C H, Xie S P, Li J, Zeng G G, Zhou X Y, Wang Q 2023 Sci. China Inf. Sci. 66 189402

    [31]

    Xu J X, Ma X, Liu J Y, Zhang C H, Li H W, Zhou X Y, Wang Q 2024 Sci. China Inf. Sci. 67 202501

    [32]

    Liu W, Huang P, Peng J, Fan J, Zeng G H 2018 Phys. Rev. A 97 022316

    [33]

    Su Y, Guo Y, Huang D 2019 Entropy 21 908

    [34]

    Liao Q, Xiao G, Zhong H, Guo Y 2020 New J. Phys. 22 083086

    [35]

    Zhou M G, Liu Z P, Liu W B, Li C L, Bai J L, Xue Y R, Fu Y, Yin H L 2022 Sci. Rep. 12 8879

    [36]

    Liu Z P, Zhou M G, Liu W B, Li C L, Gu J, Yin H L, Chen Z B 2022 Opt. Express 30 15024

    [37]

    Mao Y, Huang W, Zhong H, Wang Y, Qin H, Guo Y, Huang D 2020 New J. Phys. 22 083073

    [38]

    Ding C, Wang S, Wang Y, Wu Z, Sun J, Mao Y 2023 Phys. Rev. A 107 062422

    [39]

    Hajomer A A, Derkach I, Jain N, Chin H M, Andersen U L, Gehring T 2024 Science Advances 10 eadi9474

    [40]

    Chen Y H, Lee M J, Wang I C, Du S, Chen Y F, Chen Y C, Yu I A 2013 Phys. Rev. Lett. 110 083601

    [41]

    Reim K F, Michelberger P, Lee K C, Nunn J, Langford N K, Walmsley I A 2011 Phys. Rev. Lett. 107 053603

    [42]

    Cho Y W, Campbell G T,Everett J L, Bernu J, Higginbottom D B, Cao M T, Geng J, Robins N P, Lam P K, Buchler B C 2016 Optica 3 100

    [43]

    Sun M S, Zhang C H, Luo Y Z, Wang S, Liu Y, Li J, Wang Q 2025 Appl. Phys. Lett. 126 10

    [44]

    Meng R R, Liu X, Jin M, Zhou Z Q, Li C H, Guo G C 2024 Chip 3 100081

    [45]

    Leung A,Tranter A, Paul K, Everett J, Gris P V, Higginbottom D Campbell G, Lam P K, Buchler B 2018 Conference on Lasers and Electro-Optics Pacific Rim (CLEO-PR), Hong Kong, China, 2018, pp. 1-2

    [46]

    Cai M, Lu Y, Xiao M, Xia K 2021 Phys. Rev. A 104 053707

    [47]

    Khatri S 2021 Quantum 5 537

    [48]

    Reiß S D, Loock P 2023 Phys. Rev. A 108 012406

    [49]

    Robertson E, Esguerra L, Meßner L, Gallego G, Wolters J. 2024 Phys. Rev. Appl. 22 024026

    [50]

    Lei Y, An H, Li Z,Hosseini M 2024 Phys. Rev. Research 6 033153

    [51]

    Wehner S, Elkouss D, Hanson R 2018 Science 362 eaam9288

    [52]

    Cao Y, Zhao Y, Li Jun, Lin J, Zhang Jie, Chen J 2019 Optical Fiber Communications Conference and Exhibition (OFC), San Diego, CA, USA, 2019, pp. 1-3

    [53]

    Cao Y, Zhao Y, Li Jun, Lin J, Zhang Jie, Chen J 2020 IEEE Trans. Netw. Serv. Manage. 17 946

    [54]

    Sharma P, Gupta S, Bhatia V, Prakash S 2023 IET Quantum Commun. 4 136

    [55]

    Kang J L, Zhang M H, Liu X P, He C 2024 Phys. Rev. A 109 022617

    [56]

    Thielking J, Okhapkin M V, Glowacki P, Meier D M, Wense L, Seiferle B, Düllmann C E, Thirolf P G, Peik E 2018 Nature 556 321

    [57]

    Farooq M, Chupp T, Grange J, Tewsley-Booth A, Flay D, Kawall D, Sachdeva N, Winter P 2020 Phys. Rev. Lett. 124 223001

    [58]

    Poli N, Wang F Y, Tarallo M G, Alberti A, Prevedelli M, Tino G M 2011 Phys. Rev. Lett. 106 038501.

    [59]

    Gruber A, Drabenstedt A, Tietz C, Fleury L, Wrachtrup J, Borczyskowski C V 1997 Science 276 2012

    [60]

    Zhang H, Ma Y, Liao K, Yang W, Liu Z, Ding D, Yan H, Li W, Zhang L 2024 Sci. Bull. 69 1515

    [61]

    Guo H, Wu T, Luo B 2024 Physics 53 27 (in Chinese) [郭弘,吴腾,罗斌 2024 物理 53 27]

    [62]

    Degen C L, Reinhard F, Cappellaro P 2017 Rev. Mod. Phys. 89 035002

    [63]

    Pezzè L,Smerzi A,Oberthaler M K,Schmied R,Treutlein P 2018 Rev. Mod. Phys. 90 035005

    [64]

    Chen J P, Zhang C, Liu Y, Jiang C, Zhao D F, Zhang W J, Chen F X, Li H, You L X, Wang Z, Chen Y, Wang X B, Zhang Q, Pan J W 2022 Phys. Rev. Lett. 128 180502

    [65]

    Xu Y, Wang T, Huang P, Zeng G H 2024 Research 7 0416

    [66]

    Liu S S, Tian Y, Zhang Y, Lu Z G, Wang X Y, Li Y M 2024 Optica 11 1762

    [67]

    Pirandola S, Bardhan B R, Gehring T, Weedbrook C, Lloyd S 2018 Nat. Photon. 12 724

    [68]

    Lawrie B J, Lett P D, Marino A M, Pooser R C 2019 ACS Photon. 6 1307

    [69]

    Guo X, Breum C R, Borregaard J, Izumi S, Larsen M V, Gehring T, Christandl M, Neergaard-Nielsen J S, Andersen U L 2020 Nat. Phys. 16 281

    [70]

    Zhao S R, Zhang Y Z, Liu W Z, Guan J Y, Zhang W, Li C L, Bai B, Li M H, Liu Y, You L, Zhang J, Fan J, Xu F, Zhang Q, Pan J W 2021 Phys. Rev. X 11 031009

    [71]

    Guo X, Breum C R, Borregaard J, Izumi S, Larsen M V, Gehring T, Chridtandl M, Neergaard-Nielson J S, Andersen U L 2020 Nat. Photon. 16 281

    [72]

    Liu L Z, Zhang Y Z, Li Z D, Zhang R, Yin X F, Fei Y Y, Li L, Liu N L, Xu F, Chen Y A, Pan J W 2021 Nat. Photon. 15 137

    [73]

    Cimini V, Gianani I, Spagnolo N, Leccese F, Sciarrino F, Barbieri M 2019 Phys. Rev. Lett. 123 230502

    [74]

    Hentschel A, Sanders B C 2010 Phys. Rev. Lett. 104 063603

    [75]

    Xu H, Li J, Liu L, Wang Y, Yuan H, Wang X 2019 npj Quantum Inf. 5 82

    [76]

    Schuff J, Fiderer L J, Braun D 2020 New J. Phys. 22 035001

    [77]

    Xiao T L, Fan J P, Zeng G H 2022 npj Quantum Inf. 8 2

    [78]

    Belliardo F, Zoratti F, Marquardt F, Giovannetti V 2024 Quantum 8 1555

    [79]

    Liu Z K, Zhang L H, Liu B, Zhang Z Y, Guo G C, Ding D S, Shi B S 2022 Nat. Commun. 13 1997

    [80]

    Zhou Z, Du Y, Yin X F, Zhao S, Tian X, Tao D 2024 Phys. Rev. Res. 6 043267

  • [1] 刘刚钦. 高压下的色心磁共振和量子传感.  , doi: 10.7498/aps.74.20250224
    [2] 王鹏, 麦麦提尼亚孜·麦麦提阿卜杜拉. 机器学习的量子动力学.  , doi: 10.7498/aps.74.20240999
    [3] 武博, 林沂, 吴逢川, 陈孝樟, 安强, 刘燚, 付云起. 基于平行板谐振器的量子微波电场测量技术.  , doi: 10.7498/aps.72.20221582
    [4] 侯晨阳, 孟凡超, 赵一鸣, 丁进敏, 赵小艇, 刘鸿维, 王鑫, 娄淑琴, 盛新志, 梁生. “机器微纳光学科学家”: 人工智能在微纳光学设计的应用与发展.  , doi: 10.7498/aps.72.20230208
    [5] 杨瑞科, 李福军, 武福平, 卢芳, 魏兵, 周晔. 沙尘湍流大气对自由空间量子通信性能影响研究.  , doi: 10.7498/aps.71.20221125
    [6] 刘瑞熙, 马磊. 海洋湍流对光子轨道角动量量子通信的影响.  , doi: 10.7498/aps.71.20211146
    [7] 危语嫣, 高子凯, 王思颖, 朱雅静, 李涛. 基于单光子双量子态的确定性安全量子通信.  , doi: 10.7498/aps.71.20210907
    [8] 刘刚钦. 极端条件下的金刚石自旋量子传感.  , doi: 10.7498/aps.71.20212072
    [9] 张嘉伟, 姚鸿博, 张远征, 蒋伟博, 吴永辉, 张亚菊, 敖天勇, 郑海务. 通过机器学习实现基于摩擦纳米发电机的自驱动智能传感及其应用.  , doi: 10.7498/aps.71.20211632
    [10] 陈以鹏, 刘靖阳, 朱佳莉, 方伟, 王琴. 机器学习在量子通信资源优化配置中的应用.  , doi: 10.7498/aps.71.20220871
    [11] 林键, 叶梦, 朱家纬, 李晓鹏. 机器学习辅助绝热量子算法设计.  , doi: 10.7498/aps.70.20210831
    [12] 刘刚钦, 邢健, 潘新宇. 金刚石氮空位中心自旋量子调控.  , doi: 10.7498/aps.67.20180755
    [13] 李熙涵. 量子直接通信.  , doi: 10.7498/aps.64.160307
    [14] 张沛, 周小清, 李智伟. 基于量子隐形传态的无线通信网络身份认证方案.  , doi: 10.7498/aps.63.130301
    [15] 李申, 马海强, 吴令安, 翟光杰. 全光纤量子通信系统中的高速偏振控制方案.  , doi: 10.7498/aps.62.084214
    [16] 何锐. 基于超导量子干涉仪与介观LC共振器耦合电路的量子通信.  , doi: 10.7498/aps.61.030303
    [17] 宋汉冲, 龚黎华, 周南润. 基于量子远程通信的连续变量量子确定性密钥分配协议.  , doi: 10.7498/aps.61.154206
    [18] 印娟, 钱勇, 李晓强, 包小辉, 彭承志, 杨涛, 潘阁生. 远距离量子通信实验中的高维纠缠源.  , doi: 10.7498/aps.60.060308
    [19] 周南润, 曾宾阳, 王立军, 龚黎华. 基于纠缠的选择自动重传量子同步通信协议.  , doi: 10.7498/aps.59.2193
    [20] 周南润, 曾贵华, 龚黎华, 刘三秋. 基于纠缠的数据链路层量子通信协议.  , doi: 10.7498/aps.56.5066
计量
  • 文章访问数:  14
  • PDF下载量:  0
  • 被引次数: 0
出版历程
  • 上网日期:  2025-04-19

/

返回文章
返回
Baidu
map