eprintid: 1101
rev_number: 8
eprint_status: archive
userid: 6
dir: disk0/00/00/11/01
datestamp: 2012-02-01 14:01:47
lastmod: 2018-03-08 17:09:03
status_changed: 2012-02-01 14:01:47
type: article
metadata_visibility: show
creators_name: Garlaschelli, Diego
creators_name: Capocci, Andrea
creators_name: Caldarelli, Guido
creators_id: diego.garlaschelli@imtlucca.it
creators_id: 
creators_id: guido.caldarelli@imtlucca.it
title: Self-organized network evolution coupled to extremal dynamics
ispublished: pub
subjects: HA
subjects: QC
divisions: EIC
full_text_status: none
keywords: Statistical physics, thermodynamics and nonlinear dynamics
abstract: The interplay between topology and dynamics in complex networks is a fundamental but widely unexplored problem. Here, we study this phenomenon on a prototype model in which the network is shaped by a dynamical variable. We couple the dynamics of the Bak–Sneppen evolution model with the rules of the so-called fitness network model for establishing the topology of a network; each vertex is assigned a 'fitness', and the vertex with minimum fitness and its neighbours are updated in each iteration. At the same time, the links between the updated vertices and all other vertices are drawn anew with a fitness-dependent connection probability. We show analytically and numerically that the system self-organizes to a non-trivial state that differs from what is obtained when the two processes are decoupled. A power-law decay of dynamical and topological quantities above a threshold emerges spontaneously, as well as a feedback between different dynamical regimes and the underlying correlation and percolation properties of the network.
date: 2007-09
publication: Nature Physics
volume: 3
number: 11
publisher: Nature Publishing Group
pagerange: 813-817
id_number: 10.1038/nphys729
refereed: TRUE
issn: 1745-2473
official_url: http://dx.doi.org/10.1038/nphys729
related_url_url: http://arxiv.org/abs/cond-mat/0611201
citation:   Garlaschelli, Diego and Capocci, Andrea and Caldarelli, Guido  Self-organized network evolution coupled to extremal dynamics.  Nature Physics, 3 (11).  pp. 813-817.  ISSN 1745-2473      (2007)