Monte Carlo investigation of the critical behavior of Stavskaya's probabilistic cellular automaton

Stavskaya's model is a one-dimensional probabilistic cellular automaton (PCA) introduced in the end of the 1960s as an example of a model displaying a nonequilibrium phase transition. Although its absorbing state phase transition is well understood nowadays, the model never received a full numerical treatment to investigate its critical behavior. In this Brief Report we characterize the critical behavior of Stavskaya's PCA by means of Monte Carlo simulations and finite-size scaling analysis. The critical exponents of the model are calculated and indicate that its phase transition belongs to the directed percolation universality class of critical behavior, as would be expected on the basis of the directed percolation conjecture. We also explicitly establish the relationship of the model with the Domany-Kinzel PCA on its directed site percolation line, a connection that seems to have gone unnoticed in the literature so far.

Evolution of stress deficit and changing rates of seismicity in cellular automaton models of earthquake faults

We investigate the internal dynamics of two cellular automaton models with heterogeneous strength fields and differing nearest neighbour laws. One model is a crack-like automaton, transferring ail stress from a rupture zone to the surroundings. The other automaton is a partial stress drop automaton, transferring only a fraction of the stress within a rupture zone to the surroundings. To study evolution of stress, the mean spectral density. f(k(r)) of a stress deficit held is: examined prior to, and immediately following ruptures in both models. Both models display a power-law relationship between f(k(r)) and spatial wavenumber (k(r)) of the form f(k(r)) similar tok(r)(-beta). In the crack model, the evolution of stress deficit is consistent with cyclic approach to, and retreat from a critical state in which large events occur. The approach to criticality is driven by tectonic loading. Short-range stress transfer in the model does not affect the approach to criticality of broad regions in the model. The evolution of stress deficit in the partial stress drop model is consistent with small fluctuations about a mean state of high stress, behaviour indicative of a self-organised critical system. Despite statistics similar to natural earthquakes these simplified models lack a physical basis. physically motivated models of earthquakes also display dynamical complexity similar to that of a critical point system. Studies of dynamical complexity in physical models of earthquakes may lead to advancement towards a physical theory for earthquakes.

Accelerating seismic energy release and evolution of event time and size statistics: Results from two heterogeneous cellular automaton models

The evolution of event time and size statistics in two heterogeneous cellular automaton models of earthquake behavior are studied and compared to the evolution of these quantities during observed periods of accelerating seismic energy release Drier to large earthquakes. The two automata have different nearest neighbor laws, one of which produces self-organized critical (SOC) behavior (PSD model) and the other which produces quasi-periodic large events (crack model). In the PSD model periods of accelerating energy release before large events are rare. In the crack model, many large events are preceded by periods of accelerating energy release. When compared to randomized event catalogs, accelerating energy release before large events occurs more often than random in the crack model but less often than random in the PSD model; it is easier to tell the crack and PSD model results apart from each other than to tell either model apart from a random catalog. The evolution of event sizes during the accelerating energy release sequences in all models is compared to that of observed sequences. The accelerating energy release sequences in the crack model consist of an increase in the rate of events of all sizes, consistent with observations from a small number of natural cases, however inconsistent with a larger number of cases in which there is an increase in the rate of only moderate-sized events. On average, no increase in the rate of events of any size is seen before large events in the PSD model.

Long-range automaton models of earthquakes: Power-law accelerations, correlation evolution, and mode-switching

We introduce a conceptual model for the in-plane physics of an earthquake fault. The model employs cellular automaton techniques to simulate tectonic loading, earthquake rupture, and strain redistribution. The impact of a hypothetical crustal elastodynamic Green's function is approximated by a long-range strain redistribution law with a r(-p) dependance. We investigate the influence of the effective elastodynamic interaction range upon the dynamical behaviour of the model by conducting experiments with different values of the exponent (p). The results indicate that this model has two distinct, stable modes of behaviour. The first mode produces a characteristic earthquake distribution with moderate to large events preceeded by an interval of time in which the rate of energy release accelerates. A correlation function analysis reveals that accelerating sequences are associated with a systematic, global evolution of strain energy correlations within the system. The second stable mode produces Gutenberg-Richter statistics, with near-linear energy release and no significant global correlation evolution. A model with effectively short-range interactions preferentially displays Gutenberg-Richter behaviour. However, models with long-range interactions appear to switch between the characteristic and GR modes. As the range of elastodynamic interactions is increased, characteristic behaviour begins to dominate GR behaviour. These models demonstrate that evolution of strain energy correlations may occur within systems with a fixed elastodynamic interaction range. Supposing that similar mode-switching dynamical behaviour occurs within earthquake faults then intermediate-term forecasting of large earthquakes may be feasible for some earthquakes but not for others, in alignment with certain empirical seismological observations. Further numerical investigation of dynamical models of this type may lead to advances in earthquake forecasting research and theoretical seismology.

An extinction-survival-type phase transition in the probabilistic cellular automaton p182-q200

We investigate the critical behaviour of a probabilistic mixture of cellular automata (CA) rules 182 and 200 (in Wolfram`s enumeration scheme) by mean-field analysis and Monte Carlo simulations. We found that as we switch off one CA and switch on the other by the variation of the single parameter of the model, the probabilistic CA (PCA) goes through an extinction-survival-type phase transition, and the numerical data indicate that it belongs to the directed percolation universality class of critical behaviour. The PCA displays a characteristic stationary density profile and a slow, diffusive dynamics close to the pure CA 200 point that we discuss briefly. Remarks on an interesting related stochastic lattice gas are addressed in the conclusions.

Cellular automaton model for molecular traffic jams

We consider the time evolution of an exactly solvable cellular automaton with random initial conditions both in the large-scale hydrodynamic limit and on the microscopic level. This model is a version of the totally asymmetric simple exclusion process with sublattice parallel update and thus may serve as a model for studying traffic jams in systems of self-driven particles. We study the emergence of shocks from the microscopic dynamics of the model. In particular, we introduce shock measures whose time evolution we can compute explicitly, both in the thermodynamic limit and for open boundaries where a boundary-induced phase transition driven by the motion of a shock occurs. The motion of the shock, which results from the collective dynamics of the exclusion particles, is a random walk with an internal degree of freedom that determines the jump direction. This type of hopping dynamics is reminiscent of some transport phenomena in biological systems.

Hyper-Automaton: avaliação interativa de alunos em cursos na WEB baseado em autômatos finitos

O objetivo desta dissertação é a elaboração de uma técnica da aplicação do formalismo de Autômatos Finitos com Saída (Máquina de Mealy e Máquina de Moore) como um modelo estrutural para a organização de hiperdocumentos instrucionais, em destacar especial, Avaliação e Exercício. Esse objetivo é motivado pela organização e agilização do processo de avaliação proporcionado ao professor e ao aluno. Existem diferentes técnicas de ensino utilizadas na Internet, algumas dessas continuam sendo projetadas com o uso de metodologias tradicionais de desenvolvimento, outras têm a capacidade de modelar de forma integrada e consistente alguns aspectos necessários para uma aplicação WEB. Para alcançar o objetivo proposto, foram realizadas pesquisas nas várias áreas abrangidas pelo tema em evidência, tanto relativo ao processo tradicional (aplicação de prova utilizando metodologia tradicional), como o desenvolvimento de software mediado por computador e uso da Internet em si. A modelagem de desenvolvimento para Internet deve integrar características de técnicas de projeto de sistemas de hipermídia devido à natureza hipertextual da Internet. O uso de hiperdocumento como autômatos com saída está na forma básica de representação de hipertexto, em que cada fragmento de informação é associado a um nodo ou a um link (estado/transições) do grafo. Sendo assim, os arcos direcionados representam relacionamentos entre os nodos ou links, ou seja, uma passagem do nodo origem para o nodo destino. As n-uplas dos autômatos apresentam uma correspondência as estruturas de hiperdocumentos na WEB, seu estado/transição inicial corresponde a sua primeira página e suas transições definidas na função programa, funcionam como ligações lógicas, quando selecionadas durante a navegação do hipertexto. Entretanto, faz-se necessário um levantamento dos modelos de hipertextos e das ferramentas de implementação disponíveis para a Internet, a fim de que seja capaz de suportar as peculiaridades do ambiente. Tudo isso deve ser integrado preferencialmente em um paradigma de desenvolvimento amplamente aceito, para que os projetistas não tenham muitas dificuldades em assimilar os conceitos propostos. A proposta apresentada nesta dissertação, batizada de Hyper-Automaton (hipertexto e autômato), consiste na integração de um Curso na WEB, utilizando formalismo de Autômatos Finitos com Saída para a modelagem dos conceitos necessários e definição das fases adequadas para completar a especificação de Sistema Exercício e Avaliação, bem como a especificação da Geração Automática dos Exercícios e Avaliações baseadas em autômatos para a WEB. Os modelos criados abrangem conceitos de Máquina de Mealy, Máquina de Moore e Aplicações de Hiperdocumentos e Ferramentas de Programação para Internet, os mesmos já testados em caso real. Os parâmetros apurados, nos testes, serviram a uma seqüência de etapas importantes para modelar e complementar a especificação do sistema projetado. Com os parâmetros e etapas de modelagem, a metodologia Hyper-Automaton consegue integrar, de forma consistente, as vantagens de várias técnicas específicas de modelagem de documentos e sistemas de hipermídia. Essas vantagens, aliadas ao suporte às ferramentas de desenvolvimento para Internet, garantem que a metodologia fique adequada para a modelagem de Sistemas com aplicação de métodos de autômatos para exercícios e avaliação na WEB.

A Cellular Automaton Approach to Spatial Electric Load Forecasting

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Modeling the dynamics of human hair cycles by a follicular automaton

The hair follicle cycle successively goes through the anagen, catagen, telogen, and latency phases, which correspond, respectively, to hair growth, arrest, shedding, and absence before a new anagen phase is initiated. Experimental observations collected over a period of 14 years in a group of 10 male volunteers, alopecic and nonalopecic, allowed us to determine the characteristics of scalp hair follicle cycles. On the basis of these observations, we propose a follicular automaton model to simulate the dynamics of human hair cycles. The automaton model is defined by a set of rules that govern the stochastic transitions of each follicle between the successive states anagen, telogen, and latency, and the subsequent return to anagen. The transitions occur independently for each follicle, after time intervals given stochastically by a distribution characterized by a mean and a variance. The follicular automaton model accounts both for the dynamical transitions observed in a single follicle and for the behavior of an ensemble of independently cycling follicles. Thus, the model successfully reproduces the evolution of the fractions of follicle populations in each of the three phases, which fluctuate around steady-state or slowly drifting values. We apply the follicular automaton model to the study of spatial patterns of follicular growth that result from a spatially heterogeneous distribution of parameters such as the mean duration of anagen phase. When considering that follicles die or miniaturize after going through a critical number of successive cycles, the model can reproduce the evolution to hair patterns similar to well known types of diffuse or androgenetic alopecia.

On the automorphism group of a reduced automaton /

"Supported in part jointly by the Atomic Energy Commission and the Advanced Research Projects Agency under AEC Contract AT(11-1)-1018."

The automorphism group of a strongly connected automaton and its quotient automata /

"February 14, 1966."