Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2006-02-15
Lecture Notes in Computer Science 3993, 1075 (2006)
Physics
Condensed Matter
Disordered Systems and Neural Networks
8 pages, 3 figs., to appear in Lecture Notes in Computer Science
Scientific paper
In these notes we study synchronizability of dynamical processes defined on complex networks as well as its interplay with network topology. Building from a recent work by Barahona and Pecora [Phys. Rev. Lett. 89, 054101 (2002)], we use a simulated annealing algorithm to construct optimally-synchronizable networks. The resulting structures, known as entangled networks, are characterized by an extremely homogeneous and interwoven topology: degree, distance, and betweenness distributions are all very narrow, with short average distances, large loops, and small modularity. Entangled networks exhibit an excellent (almost optimal) performance with respect to other flow or connectivity properties such as robustness, random walk minimal first-passage times, and good searchability. All this converts entangled networks in a powerful concept with optimal properties in many respects.
Donetti Luca
Hurtado Pablo I.
Munoz Miguel A.
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