Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2005-04-13
International Journal of Bifurcation and Chaos (IJBC) Volume: 17 No: 7 Year: 2007 pp. 2419-2434
Physics
Condensed Matter
Disordered Systems and Neural Networks
22 pages, 10 figures, Accepted for publication on International Journal of Bifurcation and Chaos
Scientific paper
We study the synchronizability and the synchronization dynamics of networks of nonlinear oscillators. We investigate how the synchronization of the network is influenced by some of its topological features such as variations of the power law exponent $\gamma$ and the degree correlation coefficient $r$. Using an appropriate construction algorithm based on clustering the network vertices in $p$ classes according to their degrees, we construct networks with an assigned power law distribution but changing degree correlation properties. We find that the network synchronizability improves when the network becomes disassortative, i.e. when nodes with low degree are more likely to be connected to nodes with higher degree. We consider the case of both weighed and unweighed networks. The analytical results reported in the paper are then confirmed by a set of numerical observations obtained on weighed and unweighed networks of nonlinear R\"ossler oscillators. Using a nonlinear optimization strategy we also show that negative degree correlation is an emerging property of networks when synchronizability is to be optimized. This suggests that negative degree correlation observed experimentally in a number of physical and biological networks might be motivated by their need to synchronize better.
Bernardo Mario di
Garofalo Franco
Sorrentino Francesco
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