First-Order Network Coherence and Eigentime Identity on the Weighted Cayley Networks

Dai, Meifeng; Wang, Xiaoqian; Zong, Yue; Zou, Jiahui; Chen, Yufei; Su, Weiyi

doi:10.1142/s0218348x17500499

Cited by 54 publications

(5 citation statements)

References 20 publications

(23 reference statements)

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“…The deterministic network is the network generated by the deterministic way. Its advantage is that we can easily study many problems on it, such as the topology of deterministic networks, the dynamic process of deterministic networks and so on [5,6]. In the study of dynamic process of network, diusion is a basic dynamic process.…”

Section: Introductionmentioning

confidence: 99%

Average trapping time of weighted scale-free m-triangulation networks

Chen

Zhang

et al. 2019

J. Stat. Mech.

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This paper investigates the average trapping time (ATT) on weighted scale-free m-triangulation networks. ATT is the mean of the firstpassage time from any node to the trap fixed at a hub node over the entire network. Based on the structural properties of weighted scale-free m-triangulation networks, we deduce the accurate expression of ATT for weight-dependent walk. The result shows that the scaling expression of ATT with network size obeys a power-law function with exponent ln 2+4mr 2+mr ln(2m+1) characterized by the weight factor r and the growth factor m. Further, we find that the parameters r and m have a significant impact on the diusion eciency of the network, namely, the smaller r and m are, the more ecient the trapping process of the network is.

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Section: Introductionmentioning

confidence: 99%

Average trapping time of weighted scale-free m-triangulation networks

Chen

Zhang

et al. 2019

J. Stat. Mech.

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“…Therefore, we study MFPT from node C k to trap node A. By deriving z from equation (21) and making z = 1, we can get…”

Section: Att On Wpsfwmentioning

confidence: 99%

“…However, the binary network does not really reflect real life. Many real networks are essentially weighted [19][20][21][22]. Weighted networks are the extension of binary networks and can provide more information for the interaction between agents of complex system.…”

Section: Introductionmentioning

confidence: 99%

The average trapping time on the weighted pseudofractal scale-free web

2020

J. Stat. Mech.

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In this paper, we consider the average trapping time (ATT) on the weighted pseudofractal scale-free web (WPSFW) with weight factor r. According to the iteration mechanism of WPSFW, we consider the weight-dependent walk from the node of web subunit to the trap fixed in a hub node. Using the tool of probability generating function, the relationship between the mean first passage time (MFPT) of two generations of the web is discovered, and the expression of the MFPT is obtained. Moreover, we consider the MFPT averaged over all the starting nodes of subunit and finally get the analytical expression of ATT. The result shows that the ATT growth approximates a power-law function of the number of web nodes, and its exponent is .

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“…In recent years, the network research has attracted more and more attention from scientific communities [1][2][3][4][5], for example, chemical networks, social networks, disease transmission networks, and product networks. Especially, product networks can result some larger networks than before if through some given rules.…”

Section: Introductionmentioning

confidence: 99%

Two Kinds of Laplacian Spectra and Degree Kirchhoff Index of the Weighted Corona Networks

Liu

Shao

2022

Journal of Mathematics

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Recently, the study related to network has aroused wide attention of the scientific community. Many problems can be usefully represented by corona graphs or networks. Meanwhile, the weight is a vital factor in characterizing some properties of real networks. In this paper, we give complete information about the signless Laplacian spectra of the weighted corona of a graph G 1 and a regular graph G 2 and the complete information about the normalized Laplacian spectra of the weighted corona of two regular graphs. The corresponding linearly independent eigenvectors of all these eigenvalues are also obtained. The spanning trees’ total number and the degree Kirchhoff index of the weighted corona graph are computed.

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First-Order Network Coherence and Eigentime Identity on the Weighted Cayley Networks

Cited by 54 publications

References 20 publications

Average trapping time of weighted scale-free m-triangulation networks

Average trapping time of weighted scale-free m-triangulation networks

The average trapping time on the weighted pseudofractal scale-free web

Two Kinds of Laplacian Spectra and Degree Kirchhoff Index of the Weighted Corona Networks

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