Mean-field theory for clustering coefficients in Barabási-Albert networks
نویسندگان
چکیده
منابع مشابه
Mean-field theory for clustering coefficients in Barabási-Albert networks.
We applied a mean-field approach to study clustering coefficients in Barabási-Albert (BA) networks. We found that the local clustering in BA networks depends on the node degree. Analytic results have been compared to extensive numerical simulations finding a very good agreement for nodes with low degrees. Clustering coefficient of a whole network calculated from our approach perfectly fits nume...
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On Barabási-Albert networks with z neighbours selected by each added site, the Ising model was seen to show a spontaneous magnetisation. This spontaneous magnetisation was found below a critical temperature which increases logarithmically with system size. On these networks the majority-vote model with noise is now studied through Monte Carlo simulations. However, in this model, the order-disor...
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Higher order clustering coefficients C(x) are introduced for random networks. The coefficients express probabilities that the shortest distance between any two nearest neighbours of a certain vertex i equals x, when one neglects all paths crossing the node i. Using C(x) we found that in the Barabási-Albert (BA) model the average shortest path length in a node’s neighbourhood is smaller than the...
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www.sciencemag.org (this information is current as of October 19, 2007 ): The following resources related to this article are available online at http://www.sciencemag.org/cgi/content/full/286/5439/509 version of this article at: including high-resolution figures, can be found in the online Updated information and services, found at: can be related to this article A list of selected additional ...
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ژورنال
عنوان ژورنال: Physical Review E
سال: 2003
ISSN: 1063-651X,1095-3787
DOI: 10.1103/physreve.68.046126