Crossovers in ScaleFree Networks on Geographical Space

Details Crossovers in ScaleFree Networks on Geographical Space Crossovers in ScaleFree Networks on Geographical Space

2005-12-24

arxiv.org/abs/cond-mat/0512639v1

Physics

Condensed Matter

Disordered Systems and Neural Networks

4 pages, 3 figures

Scientific paper

10.1103/PhysRevE.73.035104

Complex networks are characterized by several topological properties: degree distribution, clustering coefficient, average shortest path length, etc. Using a simple model to generate scale-free networks embedded on geographical space, we analyze the relationship between topological properties of the network and attributes (fitness and location) of the vertices in the network. We find there are two crossovers for varying the scaling exponent of the fitness distribution.

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