Effects of Interactive Function Forms and Refractoryperiod in a Self-Organized Critical Model Based on Neural Networks

Based on the standard self-organizing map neural network model and an integrate-and-tire mechanism, we investigate the effect of the nonlinear interactive function on the self-organized criticality in our model. Based on these we also investigate the effect of the refractoryperiod on the self-organized criticality of the system.     

Effects of Some Neurobiological Factors in a Self-organized Critical Model Based on Neural Networks

Based on an integrate-and-fire mechanism, we investigate the effect of changing the efficacy of the synapse,the transmitting time-delayed, and the relative refractoryperiod on the self-organized criticality in our neural network model.     

Effects of Some Neurobiological Factors in a Self-organized Critical Model Based on Neural Networks

Based on an integrate-and-fire mechanism, we investigate the effect of changing the efficacy of the synapse,the transmitting time-delayed, and the relative refractoryperiod on the self-organized criticality in our neural network model.     

Self-organized Criticality in a Model Based on Neural Network

Based on the LISSOM neural network model, we introduce a model to investigate self-organized criticality in the activity of neural populations. The influence of connection (synapse) between neurons has been adequately considered in this model. It is found to exhibit self-organized criticality (SOC) behavior under appropriate conditions. We also find that the learning process has promotive influence on emergence of SOC behavior. In addition, we analyze the influence of various factors of the model on the SOC behavior, which is characterized by the power-law behavior of the avalanche size distribution.     

Self-organized Criticality in an Integrate-and-Fire Neuron Model Based on Modified Aging Networks

Based on an integrate-and-fire mechanism, we investigate self-organized criticality of a simple neuron model on a modified BA scale-free network with aging nodes. In our model, we find that the distribution of avalanche size follows power-law behavior. The critical exponent τ depends on the aging exponent α. The structures of the network with aging of nodes change with an increase of α. The different topological structures lead to different behaviors in models of integrate-and-fire neurons.     

Influence of Selective Edge Removal and Refractory Period in a Self-Organized Critical Neuron Model

A simple model for a set of integrate-and-fire neurons based on the weighted network is introduced. By considering the neurobiological phenomenon in brain development and the difference of the synaptic strength, we construct weighted networks develop with link additions and followed by selective edge removal. Thenetwork exhibits the small-world and scale-free properties with high network efficiency. The model displays an avalanche activity on a power-law distribution. We investigate the effect of selective edge removal and the neuron refractory period on the self-organized criticality of the system.     

Renormalization of one-dimensional avalanche models

We investigate a renormalization group (RG) scheme for avalanche automata introduced recently by Pietroneroet al. to explain universality in self-organized criticality models. Using a modified approach, we construct exact RG equations for a one-dimensional model whose detailed dynamics is exactly solvable. We then investigate in detail the effect of approximations inherent in a practical implementation of the RG transformation where exact dynamical information is unavailable.     

Number theoretic example of scale-free topology inducing self-organized criticality

In this Letter we present a general mechanism by which simple dynamics running on networks become self-organized critical for scale-free topologies. We illustrate this mechanism with a simple arithmetic model of division between integers, the division model. This is the simplest self-organized critical model advanced so far, and in this sense it may help to elucidate the mechanism of self-organization to criticality. Its simplicity allows analytical tractability, characterizing several scaling relations. Furthermore, its mathematical nature brings about interesting connections between statistical physics and number theoretical concepts. We show how this model can be understood as a self-organized stochastic process embedded on a network, where the onset of criticality is induced by the topology.     

Olami-Feder-Christensen model on different networks

We investigate numerically the Self Organized Criticality (SOC) properties of the dissipative Olami-Feder-Christensen model on small-world and scale-free networks. We find that the small-world OFC model exhibits self-organized criticality. Indeed, in this case we observe power law behavior of earthquakes size distribution with finite size scaling for the cut-off region. In the scale-free OFC model, instead, the strength of disorder hinders synchronization and does not allow to reach a critical state.     

Nonconservative earthquake model of self-organized criticality on a random graph

We numerically investigate the Olami-Feder-Christensen model on a quenched random graph. Contrary to the case of annealed random neighbors, we find that the quenched model exhibits self-organized criticality deep within the nonconservative regime. The probability distribution for avalanche size obeys finite size scaling, with universal critical exponents. In addition, a power law relation between the size and the duration of an avalanche exists. We propose that this may represent the correct mean-field limit of the model rather than the annealed random neighbor version.     

Goldstone Modes in Driven Diffusion Systems

By analyzing the dynamical equations of dissipative diffusion systems with the help of Feynman diagrams, we explicitly show that Goldstone modes exist in these systems and how these Goldstone modes are related to the origin of self-organized criticality. The analysis gives a clear statistical field theory picture of self-organized criticality.     

Self-organization of the critical state in granular superconductors

The critical state in granular superconductors is studied using two mathematical models: systems of differential equations for the gauge-invariant phase difference and a simplified model that is described by a system of coupled mappings and in many cases is equivalent to the standard models used for studying self-organized criticality. It is shown that the critical state of granular superconductors is self-organized in all cases studied. In addition, it is shown that the models employed are essentially equivalent, i.e., they demonstrate not only the same critical behavior, but they also lead to the same noncritical phenomena. The first demonstration of the existence of self-organized criticality in a system of nonlinear differential equations and its equivalence to self-organized criticality in standard models is given in this paper.     

Delayed self-organized criticality and earthquake modeling

Delayed self-organized criticality is defined. It is shown to preserve the power-law behavior of self-organized criticality with a significant change in the exponents. A delayed version of the Ito—Matsuzaki model for earthquakes is constructed and studied. This model explains some fractal features of earthquakes as well as the Gutenberg-Richter and Omori laws. Furthermore theb value obtained from the delayed model is closer to observations than theb value of the undelayed model.     

Self-organized Criticality in a Modified Evolution Model on Generalized Barabási-Albert Scale-Free Networks

A modified evolution model of self-organized criticality on generalized Barabási-Albert (GBA) scale-free networks is investigated. In our model, we find that spatial and temporal correlations exhibit critical behaviors. More importantly, these critical behaviors change with the parameter b, which weights the distance in comparison with the degree in the GBA network evolution.     

Energy avalanches in a rice-pile model

We investigate a one-dimensional rice-pile model. We show that the distribution of dissipated potential energy decays as a power law with an exponent α = 1.53. The system thus provides a one-dimensional example of self-organized criticality. Different driving conditions are examined in order to allow for comparisons with experiments.     

Fluctuations in mean-field self-organized criticality

We present two models that exhibit self-organized criticality at the mean-field level. These can be variously interpreted in epidemiological or chemical reaction terms. By studying the master equation for these models we find, however, that only in one of them does the self-organized critical behavior survive in the face of fluctuations. For this model we show the spectrum of the evolution operator to have spectral collapse, i.e., instead of a gap, as would occur in noncritical behavior, there are eigenvalues that approach zero as an inverse power of system size.     

Self-organized criticality with and without conservation

The self-organized sandpile models lose criticality if dissipation is introduced. Recently Christensen et al. have shown that dissipative automata based on the Burridge-Knopoff earthquake model exhibit critical behavior. Criticality is qualitatively different for the cases with and without conservation: A new characteristic length appears for the dissipative case which diverges slower than the system size. For all dissipative models we have found a characteristic frequency in the power spectrum of the released energy, which is absent for the conservative case. The exponents describing criticality change continuously as a function of the strength of dissipation and crossover phenomena occur in the vicinity of conservation. Disorder is irrelevant if conservation is present while it destroys criticality in the dissipative case.     

A Modified Earthquake Model of Self-Organized Criticality on Small World Networks

A modified Olami-Feder-Christensen model of self-organized criticality on a square lattice with the properties of small world networks has been studied. We find that our model displays power-law behavior and the exponent τ of the model depends on φ, the density of long-range connections in our network.     

Self-organized criticality in the olami-feder-christensen model

A system is in a self-organized critical state if the distribution of some measured events obeys a power law. The finite-size scaling of this distribution with the lattice size is usually enough to assume that the system displays self-organized criticality. This approach, however, can be misleading. In this paper we analyze the behavior of the branching rate sigma of the events to establish whether a system is in a critical state. We apply this method to the Olami-Feder-Christensen model to obtain evidence that, in contrast to previous results, the model is critical in the conservative regime only.     

Are avalanches in sandpiles a chaotic phenomenon?

We show that deterministic systems with strong nonlinearities seem to be more appropriate to model sandpiles than stochastic systems or deterministic systems in which discontinuities are the only nonlinearity. In particular, we are able to reproduce the breakdown of self-organized criticality found in two well known experiments, that is, a centrally fueled pile [Phys. Rev. Lett. 65 (1990) 1120] and sand in a rotating tray [Phys. Rev. Lett. 69 (1992) 2431]. By varying the parameters of the model we recover self-organized criticality, in agreement with other experiments and other models. We show that chaos plays a fundamental role in the dynamics of the system.