118 research outputs found

    Assessing Percolation Threshold Based on High-Order Non-Backtracking Matrices

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    Percolation threshold of a network is the critical value such that when nodes or edges are randomly selected with probability below the value, the network is fragmented but when the probability is above the value, a giant component connecting large portion of the network would emerge. Assessing the percolation threshold of networks has wide applications in network reliability, information spread, epidemic control, etc. The theoretical approach so far to assess the percolation threshold is mainly based on spectral radius of adjacency matrix or non-backtracking matrix, which is limited to dense graphs or locally treelike graphs, and is less effective for sparse networks with non-negligible amount of triangles and loops. In this paper, we study high-order non-backtracking matrices and their application to assessing percolation threshold. We first define high-order non-backtracking matrices and study the properties of their spectral radii. Then we focus on 2nd-order non-backtracking matrix and demonstrate analytically that the reciprocal of its spectral radius gives a tighter lower bound than those of adjacency and standard non-backtracking matrices. We further build a smaller size matrix with the same largest eigenvalue as the 2nd-order non-backtracking matrix to improve computation efficiency. Finally, we use both synthetic networks and 42 real networks to illustrate that the use of 2nd-order non-backtracking matrix does give better lower bound for assessing percolation threshold than adjacency and standard non-backtracking matrices.Comment: to appear in proceedings of the 26th International World Wide Web Conference(WWW2017

    Self-similar planar graphs as models for complex networks

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    In this paper we introduce a family of planar, modular and self-similar graphs which have small-world and scale-free properties. The main parameters of this family are comparable to those of networks associated to complex systems, and therefore the graphs are of interest as mathematical models for these systems. As the clustering coefficient of the graphs is zero, this family is an explicit construction that does not match the usual characterization of hierarchical modular networks, namely that vertices have clustering values inversely proportional to their degrees.Comment: 10 pages, submitted to 19th International Workshop on Combinatorial Algorithms (IWOCA 2008

    Planar unclustered scale-free graphs as models for technological and biological networks

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    Many real life networks present an average path length logarithmic with the number of nodes and a degree distribution which follows a power law. Often these networks have also a modular and self-similar structure and, in some cases - usually associated with topological restrictions- their clustering is low and they are almost planar. In this paper we introduce a family of graphs which share all these properties and are defined by two parameters. As their construction is deterministic, we obtain exact analytic expressions for relevant properties of the graphs including the degree distribution, degree correlation, diameter, and average distance, as a function of the two defining parameters. Thus, the graphs are useful to model some complex networks, in particular several families of technological and biological networks, and in the design of new practical communication algorithms in relation to their dynamical processes. They can also help understanding the underlying mechanisms that have produced their particular structure.Comment: Accepted for publication in Physica

    Practices in Constructing High Rockfill Dams on Thick Overburden Layers

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    Rockfill dams are very widely constructed all over the world due to their good adaptability to diverse geological and geographical conditions, and their relatively low cost compared to other dam types. However, natural satisfactory sites are increasingly difficult to find in many countries due to past dam development. In some circumstance, building dams over thick overburden layers is unavoidable. In this chapter, Chinese practices in constructing high earth and rockfill dams over thick overburden layers are reviewed. The geological and geotechnical investigation techniques are briefly summarized, and seepage control systems of some selected cases as well as the connection of the impervious systems of both the dams and their foundation layers are described. Commonly used foundation improvement techniques are also presented, followed by simple descriptions of aspects that require further research and development

    Complete spectrum of stochastic master equation for random walks on treelike fractals

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    We study random walks on a family of treelike regular fractals with a trap fixed on a central node. We obtain all the eigenvalues and their corresponding multiplicities for the associated stochastic master equation, with the eigenvalues being provided through an explicit recursive relation. We also evaluate the smallest eigenvalue and show that its reciprocal is approximately equal to the mean trapping time. We expect that our technique can also be adapted to other regular fractals with treelike structures.Comment: Definitive version accepted for publication in EPL (Europhysics Letters
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