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Anti-Noise Quantum Network Coding Protocol Based on Bell States and Butterfly Network Model

Zhexi Zhang1, Zhiguo Qu1,2,*
Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
*Corresponding Author: Zhiguo Qu. Email: .

Journal of Quantum Computing 2019, 1(2), 89-109. https://doi.org/10.32604/jqc.2019.07415

Abstract

How to establish a secure and efficient quantum network coding algorithm is one of important research topics of quantum secure communications. Based on the butterfly network model and the characteristics of easy preparation of Bell states, a novel anti-noise quantum network coding protocol is proposed in this paper. The new protocol encodes and transmits classical information by virtue of Bell states. It can guarantee the transparency of the intermediate nodes during information, so that the eavesdropper Eve disables to get any information even if he intercepts the transmitted quantum states. In view of the inevitability of quantum noise in quantum channel used, this paper analyzes the influence of four kinds of noises on the new protocol in detail further, and verifies the efficiency of the protocol under different noise by mathematical calculation and analysis. In addition, based on the detailed mathematical analysis, the protocol has functioned well not only on improving the efficiency of information transmission, throughput and link utilization in the quantum network, but also on enhancing reliability and anti-eavesdropping attacks.

Keywords

Network coding, quantum network coding, bell states, butterfly network model, quantum communication, eavesdropping detection.

Cite This Article

Z. Zhang and Z. Qu, "Anti-noise quantum network coding protocol based on bell states and butterfly network model," Journal of Quantum Computing, vol. 1, no.2, pp. 89–109, 2019.

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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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