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有损量子网络中的纠缠分布

Entanglement distribution in lossy quantum networks.

作者信息

Oleynik Leonardo, Rehman Junaid Ur, Koudia Seid, Chatzinotas Symeon

机构信息

Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg, L-1855, Luxembourg.

Department of Electrical Engineering, and the Center for Intelligent Secure Systems, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, 31261, Saudi Arabia.

出版信息

Sci Rep. 2025 Aug 14;15(1):29778. doi: 10.1038/s41598-025-14226-2.

Abstract

Entanglement distribution is essential for unlocking the potential of distributed quantum information processing. We consider an N-partite network where entanglement is distributed via a central source over lossy channels, and network participants cooperate to establish entanglement between any two chosen parties under local operations and classical communication (LOCC). We develop a general mathematical framework to assess the average bipartite entanglement shared in a lossy distribution, and introduce a tractable lower bound by optimizing over a subset of single-parameter LOCC transformations. Our results show that probabilistically extracting Bell pairs from W states is more advantageous than deterministically extracting them from GHZ-like states in lossy networks, with this advantage increasing with network size. We further extend our analysis analytically, proving that W states remain more effective in large-scale networks. These findings offer valuable insights into the practical deployment of near-term networks, and corroborate a trade-off relationship between the success conversion probability of entanglement distribution protocols and their robustness to loss.

摘要

纠缠分布对于释放分布式量子信息处理的潜力至关重要。我们考虑一个N部网络,其中纠缠通过一个中央源在有损信道上进行分布,并且网络参与者通过局部操作和经典通信(LOCC)协作在任意两个选定的方之间建立纠缠。我们开发了一个通用的数学框架来评估有损分布中共享的平均二分纠缠,并通过在单参数LOCC变换的一个子集上进行优化引入了一个易于处理的下界。我们的结果表明,在有损网络中,从W态概率性地提取贝尔对比从类GHZ态确定性地提取贝尔对更具优势,并且这种优势随着网络规模的增加而增大。我们进一步通过分析扩展了我们的分析,证明W态在大规模网络中仍然更有效。这些发现为近期网络的实际部署提供了有价值的见解,并证实了纠缠分布协议的成功转换概率与其对损耗的鲁棒性之间的权衡关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/430a/12350926/f051ca5249a9/41598_2025_14226_Fig1_HTML.jpg

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