There is a complex relation between the mechanism of preferential attachment, scale-free degree distributions and hyperbolicity in complex networks. In fact, both preferential attachment and hidden hyperbolic spaces often generate scale-free networks. We show that there is actually a duality between a class of growing spatial networks based on preferential attachment on the sphere and a class of static random networks on the hyperbolic plane. Both classes of networks have the same scale-free degree distribution as the Barabasi-Albert model. As a limit of this correspondence, the Barabasi-Albert model is equivalent to a static random network on an hyperbolic space with infinite curvature. © 2014 EPLA
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Two common features of many large real networks are that they are sparse and that they have strong c...
Abstract A remarkable approach for grasping the relevant statistical features of real networks with ...
We introduce a fully nonhierarchical network growing mechanism, that furthermore does not impose exp...
There is a complex relation between the mechanism of preferential attachment, scale-free degree dist...
We obtain the degree distribution for a class of growing network models on flat and curved spaces. T...
Undirected hyperbolic graph models have been extensively used as models of scale-free small-world ne...
We present a general class of geometric network growth mechanisms by homogeneous attachment in which...
Popularised by Barabási and Albert (1999) preferential attachment is a building principle of networ...
A family of models of growing hypergraphs with preferential rules of new linking is introduced and s...
All real networks are different, but many have some structural properties in common. There seems to ...
We study preferential attachment models where vertices enter the network with i.i.d. random numbers ...
Random graphs with power-law degrees can model scale-free networks as sparse topologies with strong ...
Over the last decade, random hyperbolic graphs have proved successful in providing geometric explana...
\u3cp\u3eIn this paper we study weighted distances in scale-free spatial network models: hyperbolic ...
peer-reviewedWe show that the community structure of a network can be used as a coarse version of it...
Two common features of many large real networks are that they are sparse and that they have strong c...
Abstract A remarkable approach for grasping the relevant statistical features of real networks with ...
We introduce a fully nonhierarchical network growing mechanism, that furthermore does not impose exp...