Synchronization on community networks

Physics – Condensed Matter – Disordered Systems and Neural Networks

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

4 figures and 4 pages

Scientific paper

10.1016/j.physleta.2007.04.083

In this Letter, we propose a growing network model that can generate scale-free networks with a tunable community strength. The community strength, $C$, is directly measured by the ratio of the number of external edges to internal ones; a smaller $C$ corresponds to a stronger community structure. According to the criterion obtained based on the master stability function, we show that the synchronizability of a community network is significantly weaker than that of the original Barab\'asi-Albert network. Interestingly, we found an unreported linear relationship between the smallest nonzero eigenvalue and the community strength, which can be analytically obtained by using the combinatorial matrix theory. Furthermore, we investigated the Kuramoto model and found an abnormal region ($C\leq 0.002$), in which the network has even worse synchronizability than the uncoupled case (C=0). On the other hand, the community effect will vanish when $C$ exceeds 0.1. Between these two extreme regions, a strong community structure will hinder global synchronization.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Synchronization on community networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Synchronization on community networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Synchronization on community networks will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-47183

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.