H. J. Wang

Fast synchronization in neuronal networks

We study the fast synchronization in complex networks of coupled Hindmarsh-Rose neurons. The relation between the maximal Lyapunov exponent corresponding to the least stable transverse mode and the speed of synchronization is given, based on which we can obtain an optimal value of global coupling strength, with which the network synchronizes with the minimal synchronization time. The speed limits of several kinds of complex networks (small-world, scale-free, and modular) with different eigenratios are studied. Finally, we extend to the modified Hodgkin-Huxley neuron case.

Cellular automaton simulations of a four-leg intersection with two-phase signalization

In this paper, we present a cellular automaton (CA) simulation of a signalized intersection. When there is no exclusive lane for left-turn vehicles, through vehicles and left-turn vehicles have to share one lane. Under such situation usually two-phase signalization is adopted, and the conflicts between the two traffic streams need to be analyzed. We use a refined configuration for the intersection simulation: the geometry of the intersection has been considered and vehicles are assumed to move along 1/4 circle arcs. We focus on the averaged travel times on left lanes and their distributions. The diagrams of intersection approach capacities (IACs) and the corresponding phase diagrams are also presented, which depend on the approach flow rates and the percentage of left-turn vehicles. Besides, we find that the minimum green time could be determined by finding out the critical value for the travel times.

An empirical study of phase transitions from synchronized flow to jams on a single-lane highway

In this paper we study empirical data for traffic flow at low velocities in single-lane traffic and compare them with those for multi-lane traffic. It is found that the traffic dynamics are quite different. When the velocities are low in multi-lane traffic, the traffic flow always becomes unstable and develops into jams. In single-lane traffic, some drivers drive in a more relaxed way and stay further back from the preceding car, as they know they cannot overtake the slow vehicle in front of them or at the front of the line. It may also be because they prefer not to follow the preceding vehicle too closely in single-lane traffic, to avoid the incessant deceleration and acceleration. This strategy is feasible because even if the space in front is large, no vehicle could ?cut in? in the single lane traffic. This phenomenon is called the ?moderating effect?, and it harmonizes the traffic flow at low velocities. It is shown that the data points of synchronized flow in single-lane traffic are usually to the left and below those for multi-lane traffic in the flow?density plane. Thus, it is more difficult for the phase transition from synchronized flow to jams to occur in single-lane traffic, as pointed out in Kerners three-phase traffic theory.

Dynamical symmetry and synchronization in modular networks

The effects of dynamical symmetry on the chaotic pattern synchronization in modular networks have been studied. It is found that the topological and the coupling symmetries between modules (subnetworks) can both enhance and speed up the chaotic pattern synchronization between modules. The calculation of Lyapunov exponent shows that this dynamical symmetry is a necessary condition for complete chaotic pattern synchronization in both modular networks composed by identical oscillators and heterogeneous modular networks if the states of nodes are much different from one another.

Time-delay–induced synchronization in complex networks: Exploring the dynamical mechanism

We show that delayed coupling could induce or enhance stable chaotic synchronization in complex networks, where no or weak synchrony would exist for the usual instantaneous coupling. The mechanism behind this phenomenon reveals that the phase structure of the coupled chaotic oscillator plays the main role. Numerical results for Rossler and Lorenz oscillators as network nodes confirm the generality of this phenomenon. Together with our previous findings, we highlight the importance of taking the dynamical structure into account when studying or designing large-scale networks for stable synchronization.