International Journal of Modern Physics C

The study of the reversibility of elementary cellular automata with rule number 150 over the finite state set 𝔽_p and endowed with periodic boundary conditions is done. The dynamic of such discrete dynamical systems is characterized by means of characteristic circulant matrices, and their analysis allows us to state that the reversibility depends on the number of cells of the cellular space and to explicitly compute the corresponding inverse cellular automata.

Due to the existence of curved roads in real traffic situation, a novel lattice traffic flow model on a curved road is proposed by taking the effect of friction coefficient and radius into account. The stability condition is obtained by using linear stability theory. The result shows that the traffic flow becomes stable with the decrease of friction coefficient and radius of the curved road. Using nonlinear analysis method, the Korteweg–de Vries (KdV) and modified Korteweg–de Vries (mKdV) equation are derived to describe soliton waves and the kink–antikink waves in the meta-stable region and unstable region, respectively. Numerical simulations are carried out and the results are consistent with the theoretical results.

The present study quantified the degree of the small-world (SW) property defined by Watts, and evaluated its achievement level to characterize complex networks. However, because this process has a combinatorial optimization problem, we applied the chaos neural network (CNN) and the simulated annealing (SA), and confirmed their performance in terms of optimized values and numerical costs. Next, we visualized the original network and its optimized networks whose SW property was maximized or minimized by exchanging the original network topology. As a result, although CNN and SA require huge computational time, we confirmed that they can evaluate the SW property and even real SW networks still have plenty of room to enlarge their own SW property.

Financial market is a complex evolved dynamic system with high volatilities and noises, and the modeling and analyzing of financial time series are regarded as the rather challenging tasks in financial research. In this work, by applying the Potts dynamic system, a random agent-based financial time series model is developed in an attempt to uncover the empirical laws in finance, where the Potts model is introduced to imitate the trading interactions among the investing agents. Based on the computer simulation in conjunction with the statistical analysis and the nonlinear analysis, we present numerical research to investigate the fluctuation behaviors of the proposed time series model. Furthermore, in order to get a robust conclusion, we consider the daily returns of Shanghai Composite Index and Shenzhen Component Index, and the comparison analysis of return behaviors between the simulation data and the actual data is exhibited.

To propose method that can optimize the movement efficiency of passengers in the railway station and then guarantee the personal security under emergency case, we did experimental and modeling research on the movement behavior and characteristics of the passengers in a railway station. Observation experiments were conducted to analyze the process of passengers catching trains and leaving the station, through which, the phenomena of lane changing and dislocation were found in a straight channel, and seven categories of baggage were also identified in the crowd. Analysis shows that personal speed would rise as the increasing size of the baggage. A modified lattice gas model focus on the passengers carrying baggage was further built to study passengers movement characteristics. Using this model, the effect of pause probability of passengers and the effect of channel width on movement efficiency were analyzed, according to which, a management strategy to promote the flow rate of crowd in railway station was proposed. This study may be useful to study on evacuation of the railway station, control of the passengers and formulate pre-proposal on emergency evacuation.

This study extends the understanding of the spiral of silence theory by taking into account four factors, including the topology of networks, the time factor of information transmission, the node degree of individuals and the freedom of expression. Simulation experiments analyze the silencers, public opinion in steady state and relaxation time in small-world networks, scale-free networks and community-structured networks by adjusting the initial conditions. Results highlight that individuals are easier to keep silent in scale-free network, especially when the individual with big degree and minority opinion starts the discussion. Conversely, there are only a few individuals keep silent in the community-structured network when the two communities hold opposite opinions. Moreover, the number of silencers grows as the degree of coupling increases, and it decreases as the freedom of expression goes up. By analyzing the public opinion evolution, we also find some important conditions, such as the network topology, the potential public opinion distribution, and the status and sides of the first speaker, can drive the minority reversal.

We present a method which allows for a reduction of a size of a simulated system. The method can be applied to any system where one can define a finite set of possible states of the system and an elementary process which transforms one state of the system to another. The method is based on the system symmetry; we get classes of states, which can be used instead of states. A detailed procedure is presented for undirected/directed and/or unweighted/weighted graphs. Several applications of the method are shown for different types of systems. In particular, new results are presented for the random Boolean networks.

In this paper, a macroscopic traffic flow model for three-lane highways is proposed. The model is an extension of the speed gradient model by taking into account the lane changing. The new source and sink terms of lane change rate are added into the continuity equations and the speed dynamic equations to describe the lane-changing behavior. The result of the steady state analysis shows that our model can describe the lane usage inversion phenomenon. The numerical results demonstrate that the present model effectively reproduces several traffic phenomena observed in real traffic such as shock and rarefaction waves, stop-and-go waves and local clusters.

This paper discusses the initial value sensitivity (IVS) of Chinese stock market, including the single stock market and the Chinese A-share stock market, with respect to real markets and evolving models. The aim is to explore the relationship between IVS of the Chinese A-share stock market and the investment psychology based on the evolving model of genetic cellular automaton (GCA). We find: (1) The Chinese stock market is sensitively dependent on the initial conditions. (2) The GCA model provides a considerable reliability in complexity simulation (e.g. the IVS). (3) The IVS of stock market is positively correlated with the imitation probability when the intensity of the imitation psychology reaches a certain threshold. The paper suggests that the government should seek to keep the imitation psychology under a certain level, otherwise it may induce severe fluctuation to the market.

We study the effect of networks interconnection on the epidemic cost of them. When an epidemic will eventually die out, we find that the total cost of the epidemic over the interconnected network is approximate to the sum of the total epidemic cost of the two sub-networks. We also prove that the interconnection behavior can reduce epidemic threshold. Thus network interconnecting makes an epidemic more easily to occur, while keeping the total cost of the epidemic almost unchanged.

We have studied the electronic structure and magnetic properties of Nitrogen and Carbon codoped ZnO (5,0) single-walled zigzag nanotube using first-principle calculations based on the density functional theory. We performed our calculations for N- and C- codoping ZnO nanotube in two different configurations. For the first configuration in which the two impurity atoms (N or C) are on first nearest-neighbor sites in the plane of codoping, our calculation predicts that the N- and C-codoped ZnO nanotubes are antiferromagnetic material with no net magnetization. On the other hand, it is found that for the configuration in which the two impurity atoms are next nearest-neighbors, a spin polarization results in a magnetic moment in the N- and C-codoped ZnO nanotubes.

In order to effectively depict the characteristics of bidirectional pedestrian flow, a novel pedestrian flow model is proposed based on cellular automata. At first, according to direction gain, velocity gain and herding gain, the calculation formula of target position is defined, and the walking rules by combining overtaking behavior and herding behavior are given in the model. Meanwhile, the actual channel is used for experiments, where the self-organizing effect formed by pedestrian flow is observed. The simulation platform is established to study the key factors influencing pedestrian flow characteristics. The numerical analysis results showed that when the pedestrian density in the channel reached to the critical degree, the overtaking behavior can easily produce jamming. Moreover, pedestrians' rational choice is good for relieving jamming.