International Journal of Modern Physics C

In this paper, the melting behaviors of the glasslike cluster Au₁₉ are calculated and analyzed by using standard microcanonical molecular-dynamics simulations. The calculated results show a multi-step melting process. The first stage involves the majority of the surface atoms (14 atoms). An interesting phenomenon is that the minority of the surface atoms (4 atoms) are still in a solid-like state. The second stage involves all of the surface atoms. But there are two sites where the atoms stay for a relatively long time. The third stage corresponds to the frequent isomerizations involving all the surface atoms. The final stage consists of isomerization transitions involving all of the atoms, including the central atom of the cluster. The unique melting processes lead to the unique features of the caloric curve, the root-mean-square bond-length fluctuation and the heat capacity of the glasslike Au₁₉.

We develop a consensus model for studying opinion dynamics in weighted networks and investigate the effects of both the distribution of weights and the correlations between weight and degree on dynamical behaviors of opinion formation. Our results suggest that a global consensus in the weighted networks to reach is more difficult than that in unweighted network, and strongly depends on the heterogeneity of connection strengths. In addition, in the weighted network with very large heterogeneity of connection strengths, only single macroscopic opinion cluster can be formed, which differs from the behavior in the unweighted network where the next-largest macroscopic opinion cluster may exist.

This paper presents particle swarm optimization (PSO) method to solve the parameter estimation problem of the Schottky-barrier diode model. Based on the synthetic and experimental data, we have demonstrated that the proposed method has high parameter estimation accuracy. Besides, the initial guesses for the model parameter values are not required in the PSO method. Also, the performance of the PSO method is compared with that of the genetic algorithm (GA) method. The results indicate that the PSO method outperforms the binary-coded and real-coded GA methods in terms of estimation accuracy and computation efficiency.

Much empirical evidence has shown realistic networks are weighted. Compared with those on unweighted networks, the dynamics on weighted network often exhibit distinctly different phenomena. In this paper, we investigate the evolutionary game dynamics (prisoner's dilemma game and snowdrift game) on a weighted social network consisted of rational agents and focus on the evolution of cooperation in the system. Simulation results show that the cooperation level is strongly affected by the weighted nature of the network. Moreover, the variation of time series has also been investigated. Our work may be helpful in understanding the cooperative behavior in the social systems.

We present a modified cellular automaton model to study the traffic flow on a signal controlled ring road with velocity guidance. The velocity guidance is such a strategy that when vehicles approach the traffic light, suggested velocities are provided for avoiding the vehicles' sharp brakes in front of red light. Simulation results show that this strategy may significantly reduce the vehicles' stopping rate and the effect size is dependent upon the traffic density, the detector position, the signal's cycle time and the obedience rate of vehicles to the guidance.

We compare the Lattice BGK, the Multiple Relaxation Times and the Entropic Lattice Boltzmann Methods for time harmonic flows. We measure the stability, speed and accuracy of the three models for Reynolds and Womersley numbers that are representative for human arteries.

The Lattice BGK shows predictable stability and is the fastest method in terms of lattice node updates per second. The Multiple Relaxation Times LBM shows erratic stability which depends strongly on the relaxation times set chosen and is slightly slower. The Entropic LBM gives the best stability at the price of fewer lattice node updates per second.

A parameter constraint optimization technique is used to determine which is the fastest model given a certain preset accuracy. It is found that the Lattice BGK performs best at most arterial flows, except for the high Reynolds number flow in the aorta, where the Entropic LBM is the fastest method due to its better stability. However we also conclude that the Entropic LBM with velocity/pressure inlet/outlet conditions shows much worse performance.

We investigate the critical short-time scaling of the two-dimensional lattice ϕ⁴ field theory with a Langevin dynamics. Starting from a "hot" initial configuration but with a small magnetization, the critical initial increase of the magnetization is observed, through which we determine the critical point. From the short-time relaxation dynamics of various quantities at the critical point obtained, the dynamic critical exponents θ, z and the static exponent β/ν are evaluated. In executing a Langevin simulation, an appropriate discretization method with respect to the time degree of freedom becomes essentially important to be adopted and we show that the well-known second-order form of discretized Langevin equation works well to investigate the short-time dynamics.

This work introduces a novel coarse-grained model representing the dynamics of polar molecules that adsorb on a substrate in the presence of a solvent. The motivation of the model is to avoid the explicit representation of the solvent. Instead, the solvent-mediated interaction is indirectly represented using a fluctuating energy landscape. The dynamics, on which this model is based, are similar to the dynamics in game theory. In particular, the strategy of an agent in a game is similar to the modification of the free energy barrier between the molecule and the substrate induced by other companion molecules. The aim of this method is to show how the interplay between solvents and companion molecules can imply a modification in the adsorption energy of molecules, and how this modification can buffer the adsorption of specific molecules on surfaces. The results, and their implications in the molecular recognition of surfaces, are discussed.

We propose a freezing ferromagnetic moment model to explain the exchange bias discovered in α-Fe₂O₃ antiferromagnetic nanoleaves most recently. The model assumes that in the antiferromagnetic nanosystem, the disorder surface spins are frozen at low temperature along magnetic filed direction, forming a ferromagnetic layer. Then this frozen ferromagnetic surface state couples with the inside antiferromagnetic layers that results in an exchange bias. After some proper simplification, we get the magnetization at different applied field by the minimal energy calculation using MATLAB. Our model computerizing indicates the exchange bias shift of the magnetization curve is -48.2 Oe for n = 100 antiferromagnetic layers, which matches the observed value very well.

Based on the general unitary operations of two-qubit system, we investigate the dynamics of information swapping between two qubits. We briefly describe the general behavior of entanglement entropy and the purity taking into account two classes of initially states, either product state or entangled state. Using the phenomenon of information swapping, we suggest a theoretical protocol to transform the coded information from sender to the receiver.

In this paper, a growing network model with aging mechanism is investigated. Each new node of the network gets attached to the ith existing node with the probability , where k_i is the degree of the ith node and τ_i is its age at time t. β denotes attraction factor and α represents aging intensity. It is found that the network shows scaling behaviors such as scale-free and exponential distribution of degree. Moreover, the phase diagram in the β - α plane is observed, in which there are three regions plotted by two boundaries.

This paper mainly investigated a hybrid function projective synchronization of two different chaotic systems. Based on the Lyapunov stability theory, an adaptive controller for the synchronization of two different chaotic systems is designed. This technique is applied to achieve the synchronization between Lorenz and Rössler chaotic systems, and the synchronization of hyperchaotic Rössler and Chen systems. The numerical simulation results illustrate the effectiveness and feasibility of the proposed scheme.