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Criticality in Two-Variable Earthquake Model on a Random Graph

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Communications in Theoretical Physics 2008年第8期50卷 417-420页

作者： SUN Fan ZHANG Duan-Ming physics Laboratory Center Nanjing University of Aeronautics and Astronautics Nanjing 221000 China Department of Physics Huazhong University of Science and Technology Wuhan 430074 China

A two-variable earthquake model on a quenched random graph is established here. It can be seen as a generalization of the OFC models. We numerically study the critical behavior of the model when the system is nonconservative： the result indicates that the model exhibits self-organized criticality deep within the nonconservative regime. The probability distribution for avalanche size obeys finite size scaling. We compare our mode/with the mode/ introduced by Stefano Lise and Maya Paczuski [Phys. Rev. Lett. 88 （2002） 228301], it is proved that they are not in the same universality class.

关键词： self-organized criticality two-variable earthquake model critical behavior power-law behavior finite size scaling

Self-organized Criticality in an Earthquake Model on Random Network

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Communications in Theoretical Physics 2006年第2期45卷 293-296页

作者： ZHANG Duan-Ming SUN Fan YU Bo-Ming PAN Gui-Jun SUN Hong-Zhang YIN Yah-Ping LI Rui SU Xiang-Ying Department of Physics Huazhong University of Science and Technology Wuhan 430074 China

A simplified Olami-Feder-Christensen model on a random network has been studied. We propose a new toppling rule -- when there is an unstable site toppling, the energy of the site is redistributed to its nearest neighbors randomly not averagely. The simulation results indicate that the model displays self-organized criticality when the system is conservative, and the avalanche size probability distribution of the system obeys finite size scaling. When the system is nonconservative, the model does not display scaling behavior. Simulation results of our model with different nearest neighbors q is also compared, which indicates that the spatial topology does not alter the critical behavior of the system.

关键词： self-organized criticality earthquake model finite size scaling random network

Critical Behaviors in a Stochastic Local Limited One-Dimensional Rice-Pile Model

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Communications in Theoretical Physics 2008年第8期50卷 425-428页

作者： SUN Hong-Zhang TANG Zheng-Xin School of Science Henan University of Science and Technology Luoyang 471003 China

A stochastic local limited one-dimensional rice-pile model is numerically investigated. The distributions for avalanche sizes have a clear power-law behavior and it displays a simple finite size scaling. We obtain the avalanche exponents Ts= 1.54±0.10,βs = 2.17±0.10 and TT = 1.80±0.10, βT =1.46 ± 0.10. This self-organized critical model belongs to the same universality class with the Oslo rice-pile model studied by K. Christensen et al. [Phys. Rev. Lett. 77 （1996） 107], a rice-pile model studied by L.A.N. Amaral et al. [Phys. Rev. E 54 （1996） 4512], and a simple deterministic self-organized critical model studied by M.S. Vieira [Phys. Rev. E 61 （2000） 6056].

关键词： self-organized criticality rice-pile model finite size scaling universality class

Influence of Inhomogeneity on Critical Behavior of Earthquake Model on Random Graph

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Communications in Theoretical Physics 2006年第2X期46卷 261-264页

作者： ZHANG Duan-Ming SUN Fan YU Bo-Ming PAN Gui-Jun YIN Yah-Ping LI Rui SU Xiang-Ying Department of Physics Huazhong University of Science and Technology Wuhan 430074 China

We consider the earthquake model on a random graph. A detailed analysis of the probability distribution of the size of the avalanches will be given. The model with different inhomogeneities is studied in order to compare the critical behavior of different systems. The results indicate that with the increase of the inhomogeneities, the avalanche exponents reduce, i.e., the different numbers of defects cause different critical behaviors of the system. This is virtually ascribed to the dynamical perturbation.

关键词： self-organized criticality earthquake model critical behavior power-law finite size scaling random network