Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2004-09-13
Physics
Condensed Matter
Disordered Systems and Neural Networks
4 pages, 7 figures
Scientific paper
We suggest an approach to study hierarchy, especially hidden one, of complex networks based on the analysis of their vulnerability. Two quantities are proposed as a measure of network hierarchy. The first one is the system vulnerability V. We show that being quite suitable for regular networks this characteristic does not allow one to estimate the hierarchy of large random networks. The second quantity is a relative variance h of the system vulnerability that allows us to characterize a "natural" hierarchy level of random networks. We find that hierarchical properties of random networks depend crucially on a ratio between the number of nodes and the number of edges. We note that any graph with a transitive isometry group action (i.e. an absolutely symmetric graph) is not hierarchical. Breaking such a symmetry leads to appearance of hierarchy.
Gol'dshtein Vladimir
Koganov Gennady A.
Surdutovich G. I.
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