THE COMPLEX NETWORKS WITH RANDOM INITIALIZING AND PREFERENTIAL LINKING

2010 ◽  
Vol 24 (24) ◽  
pp. 4753-4759 ◽  
Author(s):  
TIELI SUN ◽  
JINGWEI DENG ◽  
KAIYING DENG ◽  
SHUANGLIANG TIAN
Keyword(s):  
Field Theory ◽  
Theoretical Analysis ◽  
Computer Simulations ◽  
Mean Field Theory ◽  
Mean Field ◽  
Scale Free ◽  
Proposed Model ◽  
Free Behavior ◽  
Analytical Expressions ◽  
Theoretical Results

In this paper, we first derive the analytical expressions of the degree distributions for the network with random initializing attractiveness and preferential linking by using the approach of mean-field theory. Then we discuss the justification of the scale-free behavior and give a remark about the proposed model. Finally, a series of theoretical analysis and numerical simulations for the network model are conducted. The computer simulations and the theoretical results are consistent, and display the effectiveness of the model.

Spreading of Epidemics on Scale-Free Networks with Time Delay

2012 ◽  
Vol 562-564 ◽  
pp. 1386-1389
Author(s):  
Yuan Mei Wang ◽  
Tao Li
Keyword(s):  
Field Theory ◽  
Time Delay ◽  
Mean Field Theory ◽  
Mean Field ◽  
Sir Model ◽  
Scale Free ◽  
Spreading Dynamics ◽  
Scale Free Networks ◽  
The Mean ◽  
Theoretical Results

In the SIR model once a node is cured after infection it becomes permanently immune,but we assume this immunity to be temporary. So we obtain an epidemic model with time delay on scale-free networks. Using the mean field theory the spreading threshold and the spreading dynamics is analyzed. Theoretical results indicate that the threshold is significantly dependent on the topology of scale-free networks and time delay. Numerical simulations confirmed the theoretical results.

Analyses of Complex Networks Based on the Random Walk Model

2014 ◽  
Vol 610 ◽  
pp. 850-853
Author(s):  
Jing Wei Deng ◽  
Kai Ying Deng ◽  
Ying Xing Li
Keyword(s):  
Theoretical Analysis ◽  
Scale Free Network ◽  
Theoretical Justification ◽  
Scale Free ◽  
Proposed Model ◽  
Global Meaning ◽  
Master Equation Approach ◽  
Free Network ◽  
Free Behavior ◽  
Analytical Expressions

In this letter, we derive the analytical expressions of the degree distributions for a kind of networks model random initializing attractiveness and preferential linking, which analyzed degree evolution by using the master equation approach. We also discuss the theoretical justification of the scale-free behavior about the proposed model. The influencing range of initialization to the degree distribution only related to initialization’s expectation under the global meaning. Finally, a series of theoretical analysis and numerical simulations to the scale-free network model are conducted in this letter. The results of computer simulation is presented to the theoretical analysis.

THEORETICAL INVESTIGATION OF ASYMMETRIC SIMPLE EXCLUSION PROCESSES WITH OFF-RAMP ON THE BOUNDARIES

2012 ◽  
Vol 26 (24) ◽  
pp. 1250155 ◽  
Author(s):  
SONG XIAO ◽  
SHUYING WU ◽  
LIQIONG TANG ◽  
DONGSHENG ZHENG ◽  
JING SHANG
Keyword(s):  
Field Theory ◽  
Monte Carlo ◽  
Computer Simulations ◽  
Mean Field Theory ◽  
Mean Field ◽  
Exclusion Processes ◽  
Density Profiles ◽  
Asymmetric Simple Exclusion ◽  
Simple Exclusion ◽  
Good Agreement

In this letter, asymmetric simple exclusion processes with off-ramp on the boundaries have been studied by asymmetric simple exclusion processes (ASEPs). In this model, particles can only detach from a single off-ramp on the boundaries of the system. The phase diagrams and density profiles are calculated by approximate mean field theory and have shown good agreement with the extensive Monte Carlo computer simulations.

Symmetry-preserving mean field theory for electrostatics at interfaces

2014 ◽  
Vol 50 (92) ◽  
pp. 14397-14400 ◽  
Author(s):  
Zhonghan Hu
Keyword(s):  
Field Theory ◽  
Computer Simulations ◽  
Mean Field Theory ◽  
Mean Field ◽  
Molecular Liquids ◽  
Novel Method

A novel method is developed for complex nonuniform electrostatics in computer simulations of molecular liquids at interfaces.

scholarly journals Associated Credit Risk Contagion with Incubatory Period: A Network-Based Perspective

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Kai Xu ◽  
Jianming Mo ◽  
Qian Qian ◽  
Fengying Zhang ◽  
Xiaofeng Xie ◽  
...  
Keyword(s):  
Field Theory ◽  
Credit Risk ◽  
Mean Field Theory ◽  
Mean Field ◽  
Stable State ◽  
Scale Free Network ◽  
Scale Free ◽  
Free Network ◽  
The Mean ◽  
Credit Risk Contagion

Associated credit risk is a kind of credit risk among the associated credit entities formed by credit-related entities. Focusing on this hot topic of associated credit risk and the relevant contagion and considering the latent entities and their incubatory period, this paper builds an infectious dynamic model to describe the associated credit risk contagion of associated credit entities based on the mean-field theory of complex networks. Firstly, this paper analyzes the stable state of the associated credit risk contagion in the associated entity network, considering the latent entities and their incubatory period. Secondly, from the perspective of complex network and considering the incubatory period, a SHIS model is built to reveal how the incubatory period influences associated credit risk contagion. Finally, the sensitivity of some parameters is analyzed in the Barabási–Albert (BA) scale-free network. The results show the following: (i) the contagion threshold of associated credit risk is related to the incubatory period of latent entities, the recovery rate and infectivity of infected entities, and the newborn rate of credit entities; (ii) the infectious rate of infected entities, the mortality rate of credit entities, and the important factors stated in (i) are all significantly correlated with the density of infected entities.

Effect of hopping rates coupled with on-ramp on the phase diagrams of totally asymmetric simple exclusion process

2019 ◽  
Vol 33 (13) ◽  
pp. 1950127 ◽  
Author(s):  
Song Xiao ◽  
Xiaoyu Chen ◽  
Jianhui Shi ◽  
Yanna Liu
Keyword(s):  
Field Theory ◽  
Phase Diagrams ◽  
Mean Field Theory ◽  
Mean Field ◽  
Exclusion Process ◽  
Asymmetric Simple Exclusion Process ◽  
Simple Exclusion Process ◽  
Asymmetric Simple Exclusion ◽  
Simple Exclusion ◽  
Theoretical Results

In this paper, the effect of different hopping rates coupled with on-ramp on the phase diagrams has been investigated by totally asymmetric simple exclusion process (TASEP). The topology of phase diagrams on different hopping rates and on-ramp has been obtained. Additionally, the corresponding phase diagrams and the existing condition are given by approximate mean field theory, and the theoretical results agree well with Monte Carlo simulations.

scholarly journals Six Susceptible-Infected-Susceptible Models on Scale-free Networks

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Satoru Morita
Keyword(s):  
Field Theory ◽  
Mean Field Theory ◽  
Mean Field ◽  
Information Networks ◽  
Propagation Mechanism ◽  
Contact Rate ◽  
Scale Free ◽  
Scale Free Networks ◽  
Information Spread ◽  
Nature And Society

Abstract Spreading phenomena are ubiquitous in nature and society. For example, disease and information spread over underlying social and information networks. It is well known that there is no threshold for spreading models on scale-free networks; this suggests that spread can occur on such networks, regardless of how low the contact rate may be. In this paper, I consider six models with different contact and propagation mechanisms, which include models studied so far, but are apt to be confused. To compare these six models, I analyze them by degree-based mean-field theory. I find that the result depends on the details of contact and propagation mechanism.

scholarly journals Mean-field theory for scale-free random networks

1999 ◽  
Vol 272 (1-2) ◽  
pp. 173-187 ◽  
Author(s):  
Albert-László Barabási ◽  
Réka Albert ◽  
Hawoong Jeong
Keyword(s):  
Field Theory ◽  
Mean Field Theory ◽  
Mean Field ◽  
Random Networks ◽  
Scale Free
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