32,864 research outputs found
Popularity versus Similarity in Growing Networks
Popularity is attractive -- this is the formula underlying preferential
attachment, a popular explanation for the emergence of scaling in growing
networks. If new connections are made preferentially to more popular nodes,
then the resulting distribution of the number of connections that nodes have
follows power laws observed in many real networks. Preferential attachment has
been directly validated for some real networks, including the Internet.
Preferential attachment can also be a consequence of different underlying
processes based on node fitness, ranking, optimization, random walks, or
duplication. Here we show that popularity is just one dimension of
attractiveness. Another dimension is similarity. We develop a framework where
new connections, instead of preferring popular nodes, optimize certain
trade-offs between popularity and similarity. The framework admits a geometric
interpretation, in which popularity preference emerges from local optimization.
As opposed to preferential attachment, the optimization framework accurately
describes large-scale evolution of technological (Internet), social (web of
trust), and biological (E.coli metabolic) networks, predicting the probability
of new links in them with a remarkable precision. The developed framework can
thus be used for predicting new links in evolving networks, and provides a
different perspective on preferential attachment as an emergent phenomenon
From simple to complex networks: inherent structures, barriers and valleys in the context of spin glasses
Given discrete degrees of freedom (spins) on a graph interacting via an
energy function, what can be said about the energy local minima and associated
inherent structures? Using the lid algorithm in the context of a spin glass
energy function, we investigate the properties of the energy landscape for a
variety of graph topologies. First, we find that the multiplicity Ns of the
inherent structures generically has a lognormal distribution. In addition, the
large volume limit of ln/ differs from unity, except for the
Sherrington-Kirkpatrick model. Second, we find simple scaling laws for the
growth of the height of the energy barrier between the two degenerate ground
states and the size of the associated valleys. For finite connectivity models,
changing the topology of the underlying graph does not modify qualitatively the
energy landscape, but at the quantitative level the models can differ
substantially.Comment: 10 pages, 9 figs, slightly improved presentation, more references,
accepted for publication in Phys Rev
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