Li Jing, Xu Gang, Chen Xiu-Bo, Qu Zhiguo, Niu Xin-Xin, Yang Yi-Xian
Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
School of Software Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
Sci Rep. 2017 Dec 1;7(1):16775. doi: 10.1038/s41598-017-16272-x.
Network coding is an effective means to enhance the communication efficiency. The characterization of network solvability is one of the most important topic in this field. However, for general network, the solvability conditions are still a challenge. In this paper, we consider the solvability of general quantum k-pair network in measurement-based framework. For the first time, a detailed account of measurement-based quantum network coding(MB-QNC) is specified systematically. Differing from existing coding schemes, single qubit measurements on a pre-shared graph state are the only allowed coding operations. Since no control operations are concluded, it makes MB-QNC schemes more feasible. Further, the sufficient conditions formulating by eigenvalue equations and stabilizer matrix are presented, which build an unambiguous relation among the solvability and the general network. And this result can also analyze the feasibility of sharing k EPR pairs task in large-scale networks. Finally, in the presence of noise, we analyze the advantage of MB-QNC in contrast to gate-based way. By an instance network [Formula: see text], we show that MB-QNC allows higher error thresholds. Specially, for X error, the error threshold is about 30% higher than 10% in gate-based way. In addition, the specific expressions of fidelity subject to some constraint conditions are given.
网络编码是提高通信效率的有效手段。网络可解性的表征是该领域最重要的课题之一。然而,对于一般网络而言,可解性条件仍然是一个挑战。在本文中,我们考虑基于测量框架下一般量子k对网络的可解性。首次系统地详细阐述了基于测量的量子网络编码(MB-QNC)。与现有编码方案不同,对预先共享的图态进行单量子比特测量是唯一允许的编码操作。由于不包含控制操作,这使得MB-QNC方案更具可行性。此外,给出了由特征值方程和稳定器矩阵制定的充分条件,这些条件在可解性和一般网络之间建立了明确的关系。并且该结果还可以分析在大规模网络中共享k个EPR对任务的可行性。最后,在存在噪声的情况下,我们分析了MB-QNC相对于基于门的方法的优势。通过一个实例网络[公式:见正文],我们表明MB-QNC允许更高的错误阈值。特别地,对于X错误,错误阈值比基于门的方法中的10%高出约30%。此外,还给出了在一些约束条件下保真度的具体表达式。