6533b7d8fe1ef96bd126afca
RESEARCH PRODUCT
Percolation on correlated random networks
Enore GuadagniniClaudia CioliElena AgliariElena Agliarisubject
Condensed Matter Physics; Statistical and Nonlinear Physics; Statistics and ProbabilityStatistics and ProbabilitySocial and Information Networks (cs.SI)FOS: Computer and information sciencesRandom graphDiscrete mathematicsPhysics - Physics and SocietyStatistical Mechanics (cond-mat.stat-mech)Interdependent networksFOS: Physical sciencesComputer Science - Social and Information NetworksStatistical and Nonlinear PhysicsPercolation thresholdPhysics and Society (physics.soc-ph)Complex networkCondensed Matter PhysicsGiant componentPercolationContinuum percolation theoryStatistical physicsCondensed Matter - Statistical MechanicsClustering coefficientMathematicsdescription
We consider a class of random, weighted networks, obtained through a redefinition of patterns in an Hopfield-like model and, by performing percolation processes, we get information about topology and resilience properties of the networks themselves. Given the weighted nature of the graphs, different kinds of bond percolation can be studied: stochastic (deleting links randomly) and deterministic (deleting links based on rank weights), each mimicking a different physical process. The evolution of the network is accordingly different, as evidenced by the behavior of the largest component size and of the distribution of cluster sizes. In particular, we can derive that weak ties are crucial in order to maintain the graph connected and that, when they are the most prone to failure, the giant component typically shrinks without abruptly breaking apart; these results have been recently evidenced in several kinds of social networks.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2011-01-01 | Physical Review E |