32 research outputs found
Formation of Modularity in a Model of Evolving Networks
Modularity structures are common in various social and biological networks.
However, its dynamical origin remains an open question. In this work, we set up
a dynamical model describing the evolution of a social network. Based on the
observations of real social networks, we introduced a link-creating/deleting
strategy according to the local dynamics in the model. Thus the coevolution of
dynamics and topology naturally determines the network properties. It is found
that for a small coupling strength, the networked system cannot reach any
synchronization and the network topology is homogeneous. Interestingly, when
the coupling strength is large enough, the networked system spontaneously forms
communities with different dynamical states. Meanwhile, the network topology
becomes heterogeneous with modular structures. It is further shown that in a
certain parameter regime, both the degree and the community size in the formed
network follow a power-law distribution, and the networks are found to be
assortative. These results are consistent with the characteristics of many
empirical networks, and are helpful to understand the mechanism of formation of
modularity in complex networks.Comment: 6 pages, 4 figur
The multiple effects of gradient coupling on network synchronization
Recent studies have shown that synchronizability of complex networks can be
significantly improved by asymmetric couplings, and increase of coupling
gradient is always in favor of network synchronization. Here we argue and
demonstrate that, for typical complex networks, there usually exists an optimal
coupling gradient under which the maximum network synchronizability is
achieved. After this optimal value, increase of coupling gradient could
deteriorate synchronization. We attribute the suppression of network
synchronization at large gradient to the phenomenon of network breaking, and
find that, in comparing with sparsely connected homogeneous networks, densely
connected heterogeneous networks have the superiority of adopting large
gradient. The findings are supported by indirect simulations of eigenvalue
analysis and direct simulations of coupled nonidentical oscillator networks.Comment: 4 pages, 4 figure
Optimization of synchronization in gradient clustered networks
We consider complex clustered networks with a gradient structure, where sizes
of the clusters are distributed unevenly. Such networks describe more closely
actual networks in biophysical systems and in technological applications than
previous models. Theoretical analysis predicts that the network
synchronizability can be optimized by the strength of the gradient field but
only when the gradient field points from large to small clusters. A remarkable
finding is that, if the gradient field is sufficiently strong,
synchronizability of the network is mainly determined by the properties of the
subnetworks in the two largest clusters. These results are verified by
numerical eigenvalue analysis and by direct simulation of synchronization
dynamics on coupled-oscillator networks.Comment: PRE, 76, 056113 (2007
Epidemic spreading induced by diversity of agents' mobility
In this paper, we study into the impact of the preference of an individual
for public transport on the spread of infectious disease, through a quantity
known as the public mobility. Our theoretical and numerical results based on a
constructed model reveal that if the average public mobility of the agents is
fixed, an increase in the diversity of the agents' public mobility reduces the
epidemic threshold, beyond which an enhancement in the rate of infection is
observed. Our findings provide an approach to improve the resistance of a
society against infectious disease, while preserving the utilization rate of
the public transportation system.Comment: 8 pages, 5 figure
Evolutionary Subnetworks in Complex Systems
Links in a practical network may have different functions, which makes the
original network a combination of some functional subnetworks. Here, by a model
of coupled oscillators, we investigate how such functional subnetworks are
evolved and developed according to the network structure and dynamics. In
particular, we study the case of evolutionary clustered networks in which the
function of each link (either attractive or repulsive coupling) is updated by
the local dynamics. It is found that, during the process of system evolution,
the network is gradually stabilized into a particular form in which the
attractive (repulsive) subnetwork consists only the intralinks (interlinks).
Based on the properties of subnetwork evolution, we also propose a new
algorithm for network partition which is distinguished by the convenient
operation and fast computing speed.Comment: 4 pages, 4 figure