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Continuous-Variable Quantum Network Coding Based on Quantum Discord

Tao Shang1, *, Ran Liu1, Jianwei Liu1, Yafei Hou2

1 School of Cyber Science & Technology, Beihang University, Beijing, 100083, China.
2 Graduate School of Natural Science and Technology, Okayama University, Okayama Prefecture, 700-8530, Japan.

* Corresponding Author: Tao Shang. Email: email.

Computers, Materials & Continua 2020, 64(3), 1629-1645. https://doi.org/10.32604/cmc.2020.09820

Abstract

Establishing entanglement is an essential task of quantum communication technology. Beyond entanglement, quantum discord, as a measure of quantum correlation, is a necessary prerequisite to the success of entanglement distribution. To realize efficient quantum communication based on quantum discord, in this paper, we consider the practical advantages of continuous variables and propose a feasible continuous-variable quantum network coding scheme based on quantum discord. By means of entanglement distribution by separable states, it can achieve quantum entanglement distribution from sources to targets in a butterfly network. Compared with the representative discrete-variable quantum network coding schemes, the proposed continuous-variable quantum network coding scheme has a higher probability of entanglement distribution and defends against eavesdropping and forgery attacks. Particularly, the deduced relationship indicates that the increase in entanglement is less than or equal to quantum discord.

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APA Style
Shang, T., Liu, R., Liu, J., Hou, Y. (2020). Continuous-variable quantum network coding based on quantum discord. Computers, Materials & Continua, 64(3), 1629-1645. https://doi.org/10.32604/cmc.2020.09820
Vancouver Style
Shang T, Liu R, Liu J, Hou Y. Continuous-variable quantum network coding based on quantum discord. Comput Mater Contin. 2020;64(3):1629-1645 https://doi.org/10.32604/cmc.2020.09820
IEEE Style
T. Shang, R. Liu, J. Liu, and Y. Hou, “Continuous-Variable Quantum Network Coding Based on Quantum Discord,” Comput. Mater. Contin., vol. 64, no. 3, pp. 1629-1645, 2020. https://doi.org/10.32604/cmc.2020.09820



cc Copyright © 2020 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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