Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2005-06-09
Physics
Condensed Matter
Disordered Systems and Neural Networks
5 pages, 3 figures
Scientific paper
We propose that negative degree correlation among nodes in a network of nonlinear oscillators, often detected in real world networks, is motivated by its positive effects on synchronizability. In so doing, we use a novel methodology to characterise degree correlation based on clustering the network vertices in p classes according to their degrees. Using this strategy 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 dissassortative, i.e. when nodes with low degree are more likely to be connected to nodes with higher degree. Our numerical observations are confirmed by the analytical estimates found in this letter using an innovative approach based on the use of graph theoretical results.
Bernardo Mario di
Garofalo Franco
Sorrentino Francesco
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