Am. Econ. Rev. 88: 848–881.
25 25 Fudenberg, D. and Kreps, D. (1993). Learning mixed equilibria. Behav. Ther. 5: 320–367.
26 26 Fudenberg, D. and Kreps, D. (1995). Learning in extensive form games I: self‐confirming equilibria. Games Econ. Behav. 8: 20–55.
27 27 Fudenberg, D. and Levine, D. (1993). Self‐confirming equilibrium. Econometrica 61: 523–546.
28 28 Fudenberg, D. and Levine, D. (1999). The Theory of Learning in Games. Cambridge: MIT Press.
29 29 Kalai, E. and Lehrer, E. (1993). Rational learning leads to Nash equilibria. Econometrica 61 (5): 1019–1045.
30 30 Kalai, E. and Lehrer, E. (1993). Subjective equilibrium in repeated games. Econometrica 61 (5): 1231–1240.
31 31 Robinson, J. (1951). An iterative method of solving a game. Ann. Math. Stat. 54: 296–301.
32 32 Hanzo, L. et al. (2012). Wireless myths, realities, and futures: from 3G/4G to optical and quantum wireless. Proc. IEEE 100: 1853–1888.
33 33 Nielsen, M.A. and Chuang, I.L. (2011). Quantum Computation and Quantum Information, 10e. New York, NY, USA: Cambridge University Press.
34 34 Imre, S. and Balázs, F. (2005). Quantum Computing and Communications: An Engineering Approach. Chichester, UK: Wiley.
35 35 Imre, S. and Gyongyosi, L. (2013). Advanced Quantum Communications: An Engineering Approach. Hoboken, NJ, USA: Wiley.
36 36 Lipton, R.J. and Regan, K.W. (2014). Quantum Algorithms via Linear Algebra: A Primer. Cambridge, MA, USA: MIT Press.
37 37 Hsieh, M.‐H. and Wilde, M.M. (2010). Entanglement‐assisted communication of classical and quantum information. IEEE Trans. Inf. Theory 56 (9): 4682–4704.
38 38 Hsiehand, M.‐H. and Wilde, M.M. (2010). Trading classical communication, quantum communication, and entanglement in quantum Shannon theory. IEEE Trans. Inf. Theory 56 (9): 4705–4730.
39 39 Wilde, M.M., Hsieh, M.‐H., and Babar, Z. (2014). Entanglement‐assisted quantum turbo codes. IEEE Trans. Inf. Theory 60 (2): 1203–1222.
40 40 Takeoka, M., Guha, S., and Wilde, M.M. (2014). The squashed entanglement of a quantum channel. IEEE Trans. Inf. Theory 60 (8): 4987–4998.
41 41 Inoue, K. (2006). Quantum key distribution technologies. IEEE J. Sel. Topics Quantum Electron. 12 (4): 888–896.
42 42 V. Sharma and S. Banerjee, “Analysis of quantum key distribution based satellite communication,” in Proc. Int. Conf. Comput., Commun. Netw. Technol., Jul. 2018, pp. 1–5.
43 43 Piparo, N.L. and Razavi, M. (May 2015). Long‐distance trust‐free quantum key distribution. IEEE J. Sel. Topics Quantum Electron. 21 (3): 123–130.
44 44 Calderbank, A.R. and Shor, P.W. (1996). Good quantum error‐correcting codes exist. Phys. Rev. A 54: 1098–1106.
45 45 Steane, A. (1996). Error correcting codes in quantum theory. Phys. Rev. Lett. 77: 793–797.
46 46 Kovalev, A.A. and Pryadko, L.P. (2013). Quantum kronecker sum‐product low‐density paritycheck codes with finite rate. Phys. Rev. A 88 (1) https://doi.org/10.1103/physreva.88.012311.
47 47 Tillich, J.P. and Zemor, G. (2014). Quantum LDPC codes with positive rate and minimum distance proportional to the square root of the blocklength. IEEE Trans. Inf. Theory 60 (2): 1193.
48 48 Bravyi SB, Kitaev AY. Quantum codes on a lattice with boundary. arXiv:quant‐ph/9811052. 1998;.
49 49 Freedman MH, Meyer DA. Projective plane and planar quantum codes; 1998.
50 50 Nickerson, N.H., Fitzsimons, J.F., and Benjamin, S.C. (2014). Freely scalable quantum technologies using cells of 5‐to‐50 qubits with very lossy and noisy photonic links. Phys. Rev. X 4 (4): 041041.
51 51 Kelly, J., Barends, R., Fowler, A.G. et al. (2016). Scalablein situqubit calibration during repetitive error detection. Phys. Rev. A 94 (3).
52 52 Sete EA, Zeng WJ, Rigetti CT. A functional architecture for scalable quantum computing. In: 2016 IEEE International Conference on Rebooting Computing (ICRC). IEEE; 2016.
53 53 O'Gorman, J., Nickerson, N.H., Ross, P. et al. (2016). A silicon‐based surface code quantum computer. NPJ Quantum Inf. 2 (1) https://doi.org/10.1038/npjqi.2015.19.
54 54 Takita, M., Cross, A.W., C'orcoles, A. et al. (2017). Experimental demonstration of fault‐tolerant state preparation with superconducting qubits. Phys. Rev. Lett. 119 (18): 180501. https://doi.org/10.1103/PhysRevLett.119.180501. Epub 2017 Oct 31. PMID: 29219563. Also arXiv:1705.09259v1 [quant‐ph] 25 May 2017.
55 55 Kitaev, A. (2003). Fault‐tolerant quantum computation by anyons. Ann. Phys. Rehabil. Med. 303 (1): 2–30. https://doi.org/10.1016/s0003‐4916(02)00018‐0.
56 56 S. Lloyd, M. Mohseni, and P. Rebentrost. (2013). “Quantum algorithms for supervised and unsupervised machine learning.” [Online]. Available: https://arxiv.org/abs/1307.0411
57 57 Dunjko, V., Taylor, J.M., and Briegel, H.J. (2016). Quantum‐enhancedmachine learning. Phys. Rev. Lett. 117 (13): 130501–130506.
58 58 Wittek, P. (2014). Quantum Machine Learning: What Quantum Computing Means to Data Mining. New York, NY, USA: Academic.
59 59 Oneto, L., Ridella, S., and Anguita, D. (2017). Quantum computing and supervised machine learning: training, model selection, and error estimation. In: Quantum Inspired Computational Intelligence (eds. S. Bhattacharyya, U. Maulik and P. Dutta), 33–83. Amsterdam, The Netherlands: Elsevier.
60 60 Plenio, M.B. and Virmani, S. (2005). An introduction to entanglement measures. Quantum Inf. Comput. 7: 1. arXiv:quant‐ph/0504163.
61 61 Horodecki, R., Horodecki, M., and Horodecki, K. (2009). Quantum entanglement. Rev. Mod. Phys. 81: 865. arXiv:arXiv:quantph/0702225v2.
62 62 Yukalov, V.I. and Sornette, D. Quantitative predictions in quantum decision theory. IEEE Trans. Syst.: 366–381. also arXiv:1802.06348v1 [physics.soc‐ph] 18 Feb 2018.
63 63 Ashtiani, M. and Azgomi, M.A. (2015). A survey of quantum‐like approaches to decision making and cognition. Math. Social Sci. 75: 49–80.
64 64 Yukalov, V.I. and Sornette, D. (2009). Scheme of thinking quantum systems. Laser Phys. Lett. 6 (11): 833–839.
65 65 W. Liu, J. Liu, M. Cui, and M. He, “An introductory review on quantum game theory,” in Proc. Int. Conf. Genetic Evol. Comput., Dec. 2010, pp. 386–389.
66 66 Brandt, H.E. (1999). Qubit devices and the issue of quantum decoherence. Prog. Quantum Electron. 22 (5–6): 257–370.
67 67 Lee, C.F. and Johnson, N.F. (2002). Exploiting randomness in quantum information processing. Phys. Lett. A 301 (5–6): 343–349.
68 68 D. Huang and S. Li, “A survey of the current status of research on quantum games,” in Proc. 4th Int. Conf. Inf. Manage., May 2018, pp. 46–52.
69 69 Qi, B., Zhu, W., Qian, L., and Lo, H.‐K. (2010). Feasibility of quantum key distribution through a dense wavelength division multiplexing network. New J. Phys. 12 (10): 103042.
70 70 Patel, K.A., Dynes, J.F., Lucamarini, M. et al. (2014). Quantum key distribution for 10 Gb/s dense wavelength division multiplexing networks. Appl. Phys. Lett. 104 (5): 051123.
71 71 S. Bahrani, M. Razavi, and J. A. Salehi, “Optimal wavelength allocation,” in Proc. 24th Eur. Signal Process. Conf., Budapest, Hungary, Aug./Sep. 2016, pp. 483–487.
72 72 Cao, Y., Zhao, Y., Yu, X., and Wu, Y. (2017). Resource assignment strategy in optical networks integrated with quantum key distribution. IEEE/OSA J. Opt. Commun. Netw. 9 (11): 995–1004.
73 73