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Zhang, P; Zhang, P (reprint author), Chinese Acad Sci, Inst Theoret Phys, CAS Key Lab Theoret Phys, Beijing 100190, Peoples R China.
Spectral estimation of the percolation transition in clustered networks
Source PublicationPHYSICAL REVIEW E
Language英语
AbstractThere have been several spectral bounds for the percolation transition in networks, using spectrum of matrices associated with the network such as the adjacency matrix and the nonbacktracking matrix. However, they are far from being tight when the network is sparse and displays clustering or transitivity, which is represented by existence of short loops, e.g., triangles. In this paper, for the bond percolation, we first propose a message-passing algorithm for calculating size of percolating clusters considering effects of triangles, then relate the percolation transition to the leading eigenvalue of a matrix that we name the triangle-nonbacktracking matrix, by analyzing stability of the message-passing equations. We establish that our method gives a tighter lower bound to the bond percolation transition than previous spectral bounds, and it becomes exact for an infinite network with no loops longer than 3. We evaluate numerically our methods on synthetic and real-world networks, and discuss further generalizations of our approach to include higher-order substructures.
2017
Volume96Issue:4Pages:42303
Subject AreaPhysics
DOIhttp://dx.doi.org/10.1103/PhysRevE.96.042303
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Document Type期刊论文
Identifierhttp://ir.itp.ac.cn/handle/311006/21950
Collection理论物理所科研产出_SCI期刊论文
Corresponding AuthorZhang, P (reprint author), Chinese Acad Sci, Inst Theoret Phys, CAS Key Lab Theoret Phys, Beijing 100190, Peoples R China.
Recommended Citation
GB/T 7714
Zhang, P,Zhang, P . Spectral estimation of the percolation transition in clustered networks[J]. PHYSICAL REVIEW E,2017,96(4):42303.
APA Zhang, P,&Zhang, P .(2017).Spectral estimation of the percolation transition in clustered networks.PHYSICAL REVIEW E,96(4),42303.
MLA Zhang, P,et al."Spectral estimation of the percolation transition in clustered networks".PHYSICAL REVIEW E 96.4(2017):42303.
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