arXiv subjects

Wen-Jie Bai

Publications and source records attributed to Wen-Jie Bai.

10 recordsLinked to original sources

arXiv2007

Epidemic spreading and immunization with identical infectivity

In this paper, a susceptible-infected-susceptible (SIS) model with identical infectivity, where each node is assigned with the same capability of active contacts, $A$, at each time step, is presented. We found that on scale-free networks, the density of the infected nodes shows the existence of threshold, whose value equals 1/A, both demonstrated by analysis and numerical simulation. The infected population grows in an exponential form and follows hierarchical dynamics, indicating that once the highly connected hubs are reached, the infection pervades almost the whole network in a progressive cascade. In addition, the effects of random, proportional, and targeted immunization for this model are investigated. Based on the current model and for heterogenous networks, the targeted strategy performs best, while the random strategy is much more efficient than in the standard SIS model. The present results could be of practical importance in the setup of dynamic control strategies.

physics.soc-ph↗

arXiv2006

Geographical networks evolving with optimal policy

In this article, we propose a growing network model based on an optimal policy involving both topological and geographical measures. In this model, at each time step, a new node, having randomly assigned coordinates in a $1 \times 1$ square, is added and connected to a previously existing node $i$, which minimizes the quantity $r_i^2/k_i^α$, where $r_i$ is the geographical distance, $k_i$ the degree, and $α$ a free parameter. The degree distribution obeys a power-law form when $α=1$, and an exponential form when $α=0$. When $α$ is in the interval $(0,1)$, the network exhibits a stretched exponential distribution. We prove that the average topological distance increases in a logarithmic scale of the network size, indicating the existence of the small-world property. Furthermore, we obtain the geographical edge-length distribution, the total geographical length of all edges, and the average geographical distance of the whole network. Interestingly, we found that the total edge-length will sharply increase when $α$ exceeds the critical value $α_c=1$, and the average geographical distance has an upper bound independent of the network size. All the results are obtained analytically with some reasonable approximations, which are well verified by simulations.

physics.soc-ph↗

arXiv2006

Immunization of Susceptible-Infected Model on Scale-Free networks

In this paper, we investigate two major immunization strategies, random immunization and targeted immunization, of the susceptible-infected (SI) Model on the Barabási-Albert (BA) networks. For the heterogenous structure, the random strategy is quite ineffective if the vaccinated proportion is quite small, while the targeted one which prefers to vaccinate the individuals with the largest degree can sharply depress the epidemic spreading even only a small amount of population are vaccinated. The analytical solution is also obtained,which can capture the trend of velocity change versus the amount of vaccinated population.

physics.bio-ph↗

arXiv2006

Epidemic spreading on heterogeneous networks with identical infectivity

In this paper, we propose a modified susceptible-infected-recovered (SIR) model, in which each node is assigned with an identical capability of active contacts, $A$, at each time step. In contrast to the previous studies, we find that on scale-free networks, the density of the recovered individuals in the present model shows a threshold behavior. We obtain the analytical results using the mean-field theory and find that the threshold value equals 1/A, indicating that the threshold value is independent of the topology of the underlying network. The simulations agree well with the analytic results. Furthermore, we study the time behavior of the epidemic propagation and find a hierarchical dynamics with three plateaus. Once the highly connected hubs are reached, the infection pervades almost the whole network in a progressive cascade across smaller degree classes. Then, after the previously infected hubs are recovered, the disease can only propagate to the class of smallest degree till the infected individuals are all recovered. The present results could be of practical importance in the setup of dynamic control strategies.

physics.soc-ph↗

arXiv2006

Behaviors of susceptible-infected epidemics on scale-free networks with identical infectivity

In this article, we proposed a susceptible-infected model with identical infectivity, in which, at every time step, each node can only contact a constant number of neighbors. We implemented this model on scale-free networks, and found that the infected population grows in an exponential form with the time scale proportional to the spreading rate. Further more, by numerical simulation, we demonstrated that the targeted immunization of the present model is much less efficient than that of the standard susceptible-infected model. Finally, we investigated a fast spreading strategy when only local information is available. Different from the extensively studied path finding strategy, the strategy preferring small-degree nodes is more efficient than that preferring large-degree nodes. Our results indicate the existence of an essential relationship between network traffic and network epidemic on scale-free networks.

physics.bio-ph↗

arXiv2006

Boolean Game on Scale-free Networks

Inspired by the local minority game, we propose a network Boolean game and investigate its dynamical properties on scale-free networks. The system can self-organize to a stable state with better performance than random choice game, although only the local information is available to the agent. By introducing the heterogeneity of local interactions, we find the system has the best performance when each agent's interaction frequency is linear correlated with its information capacity. Generally, the agents with more information gain more than those with less information, while in the optimal case, each agent almost has the same average profit. In addition, we investigate the role of irrational factor and find an interesting symmetrical behavior.

physics.soc-ph↗

arXiv2006

Relations between Average Distance, Heterogeneity and Network Synchronizability

By using the random interchanging algorithm, we investigate the relations between average distance, standard deviation of degree distribution and synchronizability of complex networks. We find that both increasing the average distance and magnifying the degree deviation will make the network synchronize harder. Only the combination of short average distance and small standard deviation of degree distribution that ensures strong synchronizability. Some previous studies assert that the maximal betweenness is a right quantity to estimate network synchronizability: the larger the maximal betweenness, the poorer the network synchronizability. Here we address an interesting case, which strongly suggests that the single quantity, maximal betweenness, may not give a comprehensive description of network synchronizability.

cond-mat.stat-mech↗

arXiv2006

Interplay between HIV/AIDS Epidemics and Demographic Structures Based on Sexual Contact Networks

In this article, we propose a network spread model for HIV epidemics, wherein each individual is represented by a node of the transmission network and the edges are the connections between individuals along which the infection may spread. The sexual activity of each individual, measured by its degree, is not homogeneous but obeys a power-law distribution. Due to the heterogeneity of activity, the infection can persistently exist at a very low prevalence, which has been observed in real data but can not be illuminated by previous models with homogeneous mixing hypothesis. Furthermore, the model displays a clear picture of hierarchical spread: In the early stage the infection is adhered to these high-risk persons, and then, diffuses toward low-risk population. The prediction results show that the development of epidemics can be roughly categorized into three patterns for different countries, and the pattern of a given country is mainly determined by the average sex-activity and transmission probability per sexual partner. In most cases, the effect of HIV epidemics on demographic structure is very small. However, for some extremely countries, like Botswana, the number of sex-active people can be depressed to nearly a half by AIDS.

physics.bio-ph↗

arXiv2006

Growing Scale-free Small-world Networks with Tunable Assortative Coefficient

In this paper, we propose a simple rule that generates scale-free small-world networks with tunable assortative coefficient. These networks are constructed by two-stage adding process for each new node. The model can reproduce scale-free degree distributions and small-world effect. The simulation results are consistent with the theoretical predictions approximately. Interestingly, we obtain the nontrivial clustering coefficient $C$ and tunable degree assortativity $r$ by adjusting the parameter: the preferential exponent $β$. The model can unify the characterization of both assortative and disassortative networks.

physics.soc-ph↗

arXiv2004

Continuous extremal optimization for Lennard-Jones Clusters

In this paper, we explore a general-purpose heuristic algorithm for finding high-quality solutions to continuous optimization problems. The method, called continuous extremal optimization(CEO), can be considered as an extension of extremal optimization(EO) and is consisted of two components, one is with responsibility for global searching and the other is with responsibility for local searching. With only one adjustable parameter, the CEO's performance proves competitive with more elaborate stochastic optimization procedures. We demonstrate it on a well known continuous optimization problem: the Lennerd-Jones clusters optimization problem.

cond-mat.mtrl-sci↗