News of Cellular Automata

El presente trabajo ilustra la descripción de rutinas computacionales basadas en diferentes modelos para la simulación de estructuras de grano. Métodos de Monte Carlo y de generación de números aleatorios son utilizados en conjunto a modelos geométricos y de autómatas celulares para generar diferentes morfologías en los granos y desplegarlas gráficamente en las pantallas de las computadoras. Además la influencia de los factores matemáticos y de los procesos computacionales empleados sobre la estructura de grano obtenida es descrita en detalle.

A cellular automaton (CA) is an infinite array of cells, each containing the same automaton. The dynamics of a CA is distributed over the cells where each computes its next state
as a function of the previous states of its neighborhood. Thus, the transmission of such states between neighbors is considered as feasible directly, in no time.

Security in the Wireless Sensor Networks (WSN) is a very challenging task because of their dissimilarities with the conventional wireless networks. The related works so far have been done have tried to solve the problem keeping in the mind the constraints of WSNs. In this paper we have proposed a set of cellular automata based security algorithms (CAWS) which consists of CAKD, a Cellular Automata (CA) based key management algorithm and CASC, a CA based secure data communication algorithm, which require very small amount of memory as well as simple computation.

There are usual complex causal relationships among faults to constitute complex system. Based on the introduction of Cellular Automata (CA) and its evolution theory, fault-relating pattern analysis method based on CA was studied. Application of CA for fault-relating pattern was proposed. Extended CA (ECA) and its algorithm were also proposed. Simulation and analysis for evolvement of complex process of multi-fault relating chain were realized.

Excitable cellular automata with dynamical excitation interval exhibit a wide range of space-time dynamics based on an interplay between propagating excitation patterns which modify excitability of the automaton cells. Such interactions leads to formation of standing domains of excitation, stationary waves and localised excitations. We analysed morphological and generative diversities of the functions studied and characterised the functions with highest values of the diversities.

Traffic models are fundamental resources in the management of road network.

Cellular automata are computer algorithms which apply a number of rules to a two-dimensional grid of cells, repeatedly. The grid starts in a certain state (e.g. some cells are white while others are black), after which the rules are applied in a never ending loop, for every cell of the grid. A rule can be as simple as “if this cell’s right neighbour is black, then colour this cell also black”.

Quantum cellular automata (QCA) are models of quantum computation of particular interest from the point of view of quantum simulation. Quantum lattice gas automata (QLGA - equivalently partitioned quantum cellular automata) represent an interesting subclass of QCA. Prior work on QCA has investigated the relationship between these two classes of models. In the present paper we establish necessary and sufficient conditions for unbounded, finite Quantum Cellular Automata (QCA) (finitely many active cells in a quiescent background) to be Quantum Lattice Gas Automata.

Early and burial diagenesis are the main processes modifying carbonate rock matrix properties. These processes have been studied extensively and are well-known. Detailed petrographic studies allow geologists to understand the sequence of events that increase or decrease the pore size and connectivity of the reservoir rock types. However, 3D spatial prediction of diagenetic trends or geobodies remains challenging, mainly due to interactions with the pre-existing geology, and because fault and/or fractures, and complex
fluids/rock reactions through time produce a very wide range of shapes and sizes.
Traditional variogram-based approaches used to populate rock properties in static reservoir models are not able to capture very complex geometries such as cave networks formed in karsted terrains. It is also very difficult to build 3D training images in order to obtain efficient multipoint statistic predictions for such systems. By contrast, forward modeling approaches are emerging as promising tools to better understand and assess the key parameters for specific fault or surface related diagenetic processes. We present here a new approach based on cellular automata, which uses very simple cell-based rules in order to reproduce trends and geometries.
As examples we present two case studies on fault and surface related processes. The first case will address the ability of cellular automata to predict complex karst sytems in an unconventional oil reservoir. Taking into account the geological architecture, the cellular automata is used to predict the distribution of karst breccias, cave networks or sinkholes. The second case study concerns dolomitisation in a Middle East carbonate reservoir. In this example we will emphasize the ability of the cellular automata approach to be conditioned to well data in order to better predict the spatial distribution of the dolomitised geobodies.