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多重网络上的最优渗流。

Optimal percolation on multiplex networks.

机构信息

Molecular Simulation Laboratory, Department of Physics, Faculty of Basic Sciences, Azarbaijan Shahid Madani University, Tabriz, 53714-161, Iran.

Quantum Complexity Science Initiative, Skolkovo Institute of Science and Technology, Skoltech Building 3, Moscow, 143026, Russia.

出版信息

Nat Commun. 2017 Nov 16;8(1):1540. doi: 10.1038/s41467-017-01442-2.

Abstract

Optimal percolation is the problem of finding the minimal set of nodes whose removal from a network fragments the system into non-extensive disconnected clusters. The solution to this problem is important for strategies of immunization in disease spreading, and influence maximization in opinion dynamics. Optimal percolation has received considerable attention in the context of isolated networks. However, its generalization to multiplex networks has not yet been considered. Here we show that approximating the solution of the optimal percolation problem on a multiplex network with solutions valid for single-layer networks extracted from the multiplex may have serious consequences in the characterization of the true robustness of the system. We reach this conclusion by extending many of the methods for finding approximate solutions of the optimal percolation problem from single-layer to multiplex networks, and performing a systematic analysis on synthetic and real-world multiplex networks.

摘要

最优渗流是指在网络中找到最小节点集,将其从网络中移除会将系统分割成非广泛不连通的簇。这个问题的解决方案对于疾病传播中的免疫策略和意见动态中的影响最大化都很重要。最优渗流在孤立网络的背景下受到了相当多的关注。然而,它在多重网络中的推广尚未得到考虑。在这里,我们表明,在多重网络上近似最优渗流问题的解决方案,使用从多重网络中提取的单层网络的有效解决方案,可能会对系统真正的鲁棒性的特征产生严重的后果。我们通过将用于从单层网络中找到最优渗流问题的近似解的许多方法扩展到多重网络,并对合成和真实世界的多重网络进行系统分析,得出了这一结论。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c97c/5691044/a79a93487127/41467_2017_1442_Fig1_HTML.jpg

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