Modeling water infiltration in unsaturated porous media by interacting lattice gas-cellular automata
NASA Astrophysics Data System (ADS)
di Pietro, L. B.; Melayah, A.; Zaleski, S.
1994-10-01
A two-dimensional lattice gas-cellular automaton fluid model with long-range interactions (Appert and Zaleski, 1990) is used to simulate saturated and unsaturated water infiltration in porous media. Water and gas within the porous medium are simulated by applying the dense and the light phase, respectively, of the cellular automaton fluid. Various wetting properties can be modeled when adjusting the corresponding solid-liquid interactions. The lattice gas rules include a gravity force step to allow buoyancy-driven flow. The model handles with ease complex geometries of the solid, and an algorithm for generating random porous media is presented. The results of four types of simulation experiments are presented: (1) We verified Poiseuille's law for steady and saturated flow between two parallel plates. (2) We analyzed transient water infiltration between two parallel plates of varying degrees of saturation and various apertures. (3) Philip's infiltration equation was adequately simulated in an unsaturated porous medium. (4) Infiltration into an aggregated medium containing one vertical parallel crack was simulated. Further applications of this lattice gas method for studying unsaturated flow in porous media are discussed.
Modeling dynamical geometry with lattice gas automata
Hasslacher, B.; Meyer, D.A.
1998-06-27
Conventional lattice gas automata consist of particles moving discretely on a fixed lattice. While such models have been quite successful for a variety of fluid flow problems, there are other systems, e.g., flow in a flexible membrane or chemical self-assembly, in which the geometry is dynamical and coupled to the particle flow. Systems of this type seem to call for lattice gas models with dynamical geometry. The authors construct such a model on one dimensional (periodic) lattices and describe some simulations illustrating its nonequilibrium dynamics.
Lattice-gas automata for the Navier-Stokes equation
NASA Astrophysics Data System (ADS)
Frisch, U.; Hasslacher, B.; Pomeau, Y.
1986-04-01
It is shown that a class of deterministic lattice gases with discrete Boolean elements simulates the Navier-Stokes equations, and can be used to design simple, massively parallel computing machines. A hexagonal lattice gas (HLG) model consisting of a triangular lattice with hexagonal symmetry is developed, and is shown to lead to the two-dimensional Navier-Stokes equations. The three-dimensional formulation is obtained by a splitting method in which the nonlinear term in the three-dimensional Navier-Stokes equation is recasts as the sum of two terms, each containing spurious elements and each realizable on a different lattice. Freed slip and rigid boundary conditions are easily implemented. It is noted that lattice-gas models must be run at moderate Mach numbers to remain incompressible, and to avoid spurious high-order nonlinear terms. The model gives a concrete hydrodynamical example of how cellular automata can be used to simulate classical nonlinear fields.
NASA Astrophysics Data System (ADS)
Azevedo, R. M.; Montenegro-Filho, R. R.; Coutinho-Filho, M. D.
2013-09-01
We use a lattice gas cellular automata model in the presence of random dynamic scattering sites and quenched disorder in the two-phase immiscible model with the aim of producing an interface dynamics similar to that observed in Hele-Shaw cells. The dynamics of the interface is studied as one fluid displaces the other in a clean lattice and in a lattice with quenched disorder. For the clean system, if the fluid with a lower viscosity displaces the other, we show that the model exhibits the Saffman-Taylor instability phenomenon, whose features are in very good agreement with those observed in real (viscous) fluids. In the system with quenched disorder, we obtain estimates for the growth and roughening exponents of the interface width in two cases: viscosity-matched fluids and the case of unstable interface. The first case is shown to be in the same universality class of the random deposition model with surface relaxation. Moreover, while the early-time dynamics of the interface behaves similarly, viscous fingers develop in the second case with the subsequent production of bubbles in the context of a complex dynamics. We also identify the Hurst exponent of the subdiffusive fractional Brownian motion associated with the interface, from which we derive its fractal dimension and the universality classes related to a percolation process.
Generalized hydrodynamic transport in lattice-gas automata
NASA Technical Reports Server (NTRS)
Luo, Li-Shi; Chen, Hudong; Chen, Shiyi; Doolen, Gary D.; Lee, Yee-Chun
1991-01-01
The generalized hydrodynamics of two-dimensional lattice-gas automata is solved analytically in the linearized Boltzmann approximation. The dependence of the transport coefficients (kinematic viscosity, bulk viscosity, and sound speed) upon wave number k is obtained analytically. Anisotropy of these coefficients due to the lattice symmetry is studied for the entire range of wave number, k. Boundary effects due to a finite mean free path (Knudsen layer) are analyzed, and accurate comparisons are made with lattice-gas simulations.
Generalized hydrodynamic transport in lattice-gas automata
Luo, L. School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332-0430 ); Chen, H. Department of Physics, Dartmouth College, Hanover, New Hampshire 03755 ); Chen, S. Bartol Research Institute, University of Delaware, Newark, Delaware 19716 ); Doolen, G.D.; Lee, Y. )
1991-06-15
The generalized hydrodynamics of two-dimensional lattice-gas automata is solved analytically in the linearized Boltzmann approximation. The dependence of the transport coefficients (kinematic viscosity, bulk viscosity, and sound speed) upon wave number {bold k} is obtained analytically. Anisotropy of these coefficients due to the lattice symmetry is studied for the entire range of wave number, {bold k}. Boundary effects due to a finite mean free path (Knudsen layer) are analyzed, and accurate comparisons are made with lattice-gas simulations.
Knot invariants and the thermodynamics of lattice gas automata
Meyer, D.A.
1992-01-01
The goal of this project is to build on the understanding of the connections between knot invariants, exactly solvable statistical mechanics models and discrete dynamical systems that we have gained in earlier work, toward an answer to the question of how early and robust thermodynamic behavior appears in lattice gas automata.
Theory of multicolor lattice gas - A cellular automaton Poisson solver
NASA Technical Reports Server (NTRS)
Chen, H.; Matthaeus, W. H.; Klein, L. W.
1990-01-01
The present class of models for cellular automata involving a quiescent hydrodynamic lattice gas with multiple-valued passive labels termed 'colors', the lattice collisions change individual particle colors while preserving net color. The rigorous proofs of the multicolor lattice gases' essential features are rendered more tractable by an equivalent subparticle representation in which the color is represented by underlying two-state 'spins'. Schemes for the introduction of Dirichlet and Neumann boundary conditions are described, and two illustrative numerical test cases are used to verify the theory. The lattice gas model is equivalent to a Poisson equation solution.
Lattice gas automata for flow and transport in geochemical systems
Janecky, D.R.; Chen, S.; Dawson, S.; Eggert, K.C.; Travis, B.J.
1992-01-01
Lattice gas automata models are described, which couple solute transport with chemical reactions at mineral surfaces within pore networks. Diffusion in a box calculations are illustrated, which compare directly with Fickian diffusion. Chemical reactions at solid surfaces, including precipitation/dissolution, sorption, and catalytic reaction, can be examined with the model because hydrodynamic transport, solute diffusion and mineral surface processes are all treated explicitly. The simplicity and flexibility of the approach provides the ability to study the interrelationship between fluid flow and chemical reactions in porous materials, at a level of complexity that has not previously been computationally possible.
Quantum cellular automata without particles
NASA Astrophysics Data System (ADS)
Meyer, David A.; Shakeel, Asif
2016-01-01
Quantum cellular automata (QCA) constitute space and time homogeneous discrete models for quantum field theories (QFTs). Although QFTs are defined without reference to particles, computations are done in terms of Feynman diagrams, which are explicitly interpreted in terms of interacting particles. Similarly, the easiest QCA to construct are quantum lattice gas automata (QLGA). A natural question then is, which QCA are not QLGA? Here we construct a nontrivial example of such a QCA; it provides a simple model in 1 +1 dimensions with no particle interpretation at the scale where the QCA dynamics are homogeneous.
History dependent quantum random walks as quantum lattice gas automata
Shakeel, Asif E-mail: dmeyer@math.ucsd.edu Love, Peter J. E-mail: dmeyer@math.ucsd.edu; Meyer, David A. E-mail: dmeyer@math.ucsd.edu
2014-12-15
Quantum Random Walks (QRW) were first defined as one-particle sectors of Quantum Lattice Gas Automata (QLGA). Recently, they have been generalized to include history dependence, either on previous coin (internal, i.e., spin or velocity) states or on previous position states. These models have the goal of studying the transition to classicality, or more generally, changes in the performance of quantum walks in algorithmic applications. We show that several history dependent QRW can be identified as one-particle sectors of QLGA. This provides a unifying conceptual framework for these models in which the extra degrees of freedom required to store the history information arise naturally as geometrical degrees of freedom on the lattice.
History dependent quantum random walks as quantum lattice gas automata
NASA Astrophysics Data System (ADS)
Shakeel, Asif; Meyer, David A.; Love, Peter J.
2014-12-01
Quantum Random Walks (QRW) were first defined as one-particle sectors of Quantum Lattice Gas Automata (QLGA). Recently, they have been generalized to include history dependence, either on previous coin (internal, i.e., spin or velocity) states or on previous position states. These models have the goal of studying the transition to classicality, or more generally, changes in the performance of quantum walks in algorithmic applications. We show that several history dependent QRW can be identified as one-particle sectors of QLGA. This provides a unifying conceptual framework for these models in which the extra degrees of freedom required to store the history information arise naturally as geometrical degrees of freedom on the lattice.
Dynamic behavior of multirobot systems using lattice gas automata
NASA Astrophysics Data System (ADS)
Stantz, Keith M.; Cameron, Stewart M.; Robinett, Rush D., III; Trahan, Michael W.; Wagner, John S.
1999-07-01
Recent attention has been given to the deployment of an adaptable sensor array realized by multi-robotic systems (or swarms). Our group has been studying the collective, autonomous behavior of these such systems and their applications in the area of remote-sensing and emerging threats. To accomplish such tasks, an interdisciplinary research effort at Sandia National Laboratories are conducting tests in the fields of sensor technology, robotics, and multi- agents architectures. Our goal is to coordinate a constellation of point sensors using unmanned robotic vehicles (e.g., RATLERs, Robotic All-Terrain Lunar Exploration Rover- class vehicles) that optimizes spatial coverage and multivariate signal analysis. An overall design methodology evolves complex collective behaviors realized through local interaction (kinetic) physics and artificial intelligence. Learning objectives incorporate real-time operational responses to environmental changes. This paper focuses on our recent work understanding the dynamics of many-body systems according to the physics-based hydrodynamic model of lattice gas automata. Three design features are investigated. One, for single-speed robots, a hexagonal nearest-neighbor interaction topology is necessary to preserve standard hydrodynamic flow. Two, adaptability, defined by the swarm's rate of deformation, can be controlled through the hydrodynamic viscosity term, which, in turn, is defined by the local robotic interaction rules. Three, due to the inherent nonlinearity of the dynamical equations describing large ensembles, stability criteria ensuring convergence to equilibrium states is developed by scaling information flow rates relative to a swarm's hydrodynamic flow rate. An initial test case simulates a swarm of twenty-five robots maneuvering past an obstacle while following a moving target. A genetic algorithm optimizes applied nearest-neighbor forces in each of five spatial regions distributed over the simulation domain. Armed with
Quantum mechanics of lattice gas automata: One-particle plane waves and potentials
Meyer, D.A.
1997-05-01
Classical lattice gas automata effectively simulate physical processes, such as diffusion and fluid flow (in certain parameter regimes), despite their simplicity at the microscale. Motivated by current interest in quantum computation we recently defined {ital quantum} lattice gas automata; in this paper we initiate a project to analyze which physical processes these models can effectively simulate. Studying the single particle sector of a one-dimensional quantum lattice gas we find discrete analogs of plane waves and wave packets, and then investigate their behavior in the presence of inhomogeneous potentials. {copyright} {ital 1997} {ital The American Physical Society}
Probabilistic cellular automata.
Agapie, Alexandru; Andreica, Anca; Giuclea, Marius
2014-09-01
Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case-connecting the probability of a configuration in the stationary distribution to its number of zero-one borders-the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata. PMID:24999557
Predictability in cellular automata.
Agapie, Alexandru; Andreica, Anca; Chira, Camelia; Giuclea, Marius
2014-01-01
Modelled as finite homogeneous Markov chains, probabilistic cellular automata with local transition probabilities in (0, 1) always posses a stationary distribution. This result alone is not very helpful when it comes to predicting the final configuration; one needs also a formula connecting the probabilities in the stationary distribution to some intrinsic feature of the lattice configuration. Previous results on the asynchronous cellular automata have showed that such feature really exists. It is the number of zero-one borders within the automaton's binary configuration. An exponential formula in the number of zero-one borders has been proved for the 1-D, 2-D and 3-D asynchronous automata with neighborhood three, five and seven, respectively. We perform computer experiments on a synchronous cellular automaton to check whether the empirical distribution obeys also that theoretical formula. The numerical results indicate a perfect fit for neighbourhood three and five, which opens the way for a rigorous proof of the formula in this new, synchronous case. PMID:25271778
NASA Astrophysics Data System (ADS)
Bagnoli, Franco; Rechtman, Raúl; El Yacoubi, Samira
2012-12-01
We study the problem of master-slave synchronization and control of totalistic cellular automata. The synchronization mechanism is that of setting a fraction of sites of the slave system equal to those of the master one (pinching synchronization). The synchronization observable is the distance between the two configurations. We present three control strategies that exploit local information (the number of nonzero first-order Boolean derivatives) in order to choose the sites to be synchronized. When no local information is used, we speak of simple pinching synchronization. We find the critical properties of control and discuss the best control strategy compared with simple synchronization.
NASA Astrophysics Data System (ADS)
Porod, Wolfgang; Lent, Craig S.; Bernstein, Gary H.
1994-06-01
The Notre Dame group has developed a new paradigm for ultra-dense and ultra-fast information processing in nanoelectronic systems. These Quantum Cellular Automata (QCA's) are the first concrete proposal for a technology based on arrays of coupled quantum dots. The basic building block of these cellular arrays is the Notre Dame Logic Cell, as it has been called in the literature. The phenomenon of Coulomb exclusion, which is a synergistic interplay of quantum confinement and Coulomb interaction, leads to a bistable behavior of each cell which makes possible their use in large-scale cellular arrays. The physical interaction between neighboring cells has been exploited to implement logic functions. New functionality may be achieved in this fashion, and the Notre Dame group invented a versatile majority logic gate. In a series of papers, the feasibility of QCA wires, wire crossing, inverters, and Boolean logic gates was demonstrated. A major finding is that all logic functions may be integrated in a hierarchial fashion which allows the design of complicated QCA structures. The most complicated system which was simulated to date is a one-bit full adder consisting of some 200 cells. In addition to exploring these new concepts, efforts are under way to physically realize such structures both in semiconductor and metal systems. Extensive modeling work of semiconductor quantum dot structures has helped identify optimum design parameters for QCA experimental implementations.
Global properties of cellular automata
Jen, E.
1986-04-01
Cellular automata are discrete mathematical systems that generate diverse, often complicated, behavior using simple deterministic rules. Analysis of the local structure of these rules makes possible a description of the global properties of the associated automata. A class of cellular automata that generate infinitely many aperoidic temporal sequences is defined,a s is the set of rules for which inverses exist. Necessary and sufficient conditions are derived characterizing the classes of ''nearest-neighbor'' rules for which arbitrary finite initial conditions (i) evolve to a homogeneous state; (ii) generate at least one constant temporal sequence.
When is a quantum cellular automaton (QCA) a quantum lattice gas automaton (QLGA)?
NASA Astrophysics Data System (ADS)
Shakeel, Asif; Love, Peter J.
2013-09-01
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. QLGA have been more deeply analyzed than QCA, whereas general QCA are likely to capture a wider range of quantum behavior. Discriminating between QLGA and QCA is therefore an important question. In spite of much prior work, classifying which QCA are QLGA has remained an open problem. In the present paper we establish necessary and sufficient conditions for unbounded, finite QCA (finitely many active cells in a quiescent background) to be QLGA. We define a local condition that classifies those QCA that are QLGA, and we show that there are QCA that are not QLGA. We use a number of tools from functional analysis of separable Hilbert spaces and representation theory of associative algebras that enable us to treat QCA on finite but unbounded configurations in full detail.
Meyer, D.A.
1995-12-01
The goal of this project has been to build on the understanding of the connections between knot invariants, exactly solvable statistical mechanics models and discrete dynamical systems gained in earlier work, toward an answer to the question of how early and robust thermodynamic behavior appears in lattice gas automata. These investigations have recently become relevant, unanticipatedly, to crucial issues in quantum computation.
Meyer, D.A.
1992-05-01
The goal of this project is to build on the understanding of the connections between knot invariants, exactly solvable statistical mechanics models and discrete dynamical systems that we have gained in earlier work, toward an answer to the question of how early and robust thermodynamic behavior appears in lattice gas automata.
Wells, J.T. . Dept. of Geological Sciences); Janecky, D.R.; Travis, B.J. )
1990-01-15
A lattice gas automata (LGA) model is described, which couples solute transport with chemical reactions at mineral surfaces and in pore networks. Chemical reactions and transport are integrated into a FHP-I LGA code as a module so that the approach is readily transportable to other codes. Diffusion in a box calculations are compared to finite element Fickian diffusion results and provide an approach to quantifying space-time ratios of the models. Chemical reactions at solid surfaces, including precipitation/dissolution, sorption, and catalytic reaction, can be examined with the model because solute diffusion and mineral surface processes are all treated explicitly. The simplicity and flexibility of the LGA approach provides the ability to study the interrelationship between fluid flow and chemical reactions in porous materials, at a level of complexity that has not previously been computationally possible. 20 refs., 8 figs.
Adaptive stochastic cellular automata: Applications
NASA Astrophysics Data System (ADS)
Qian, S.; Lee, Y. C.; Jones, R. D.; Barnes, C. W.; Flake, G. W.; O'Rourke, M. K.; Lee, K.; Chen, H. H.; Sun, G. Z.; Zhang, Y. Q.; Chen, D.; Giles, C. L.
1990-09-01
The stochastic learning cellular automata model has been applied to the problem of controlling unstable systems. Two example unstable systems studied are controlled by an adaptive stochastic cellular automata algorithm with an adaptive critic. The reinforcement learning algorithm and the architecture of the stochastic CA controller are presented. Learning to balance a single pole is discussed in detail. Balancing an inverted double pendulum highlights the power of the stochastic CA approach. The stochastic CA model is compared to conventional adaptive control and artificial neural network approaches.
From quantum cellular automata to quantum lattice gases
Meyer, D.A.
1996-12-01
A natural architecture for nanoscale quantum computation is that of a quantum cellular automaton. Motivated by this observation, we begin an investigation of exactly unitary cellular automata. After proving that there can be no nontrivial, homogeneous, local, unitary, scalar cellular automaton in one dimension, we weaken the homogeneity condition and show that there are nontrivial, exactly unitary, partitioning cellular automata. We find a one-parameter family of evolution rules which are best interpreted as those for a one-particle quantum automaton. This model is naturally reformulated as a two component cellular automaton which we demonstrate to limit to the Dirac equation. We describe two generalizations of this automaton, the second of which, to multiple interacting particles, is the correct definition of a quantum lattice gas.
Cellular Automata and the Humanities.
ERIC Educational Resources Information Center
Gallo, Ernest
1994-01-01
The use of cellular automata to analyze several pre-Socratic hypotheses about the evolution of the physical world is discussed. These hypotheses combine characteristics of both rigorous and metaphoric language. Since the computer demands explicit instructions for each step in the evolution of the automaton, such models can reveal conceptual…
Dynamical Behavior of Multi-Robot Systems Using Lattice Gas Automata
Cameron, S.M.; Robinett, R.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.
1999-03-11
Recent attention has been given to the deployment of an adaptable sensor array realized by multi-robotic systems. Our group has been studying the collective behavior of autonomous, multi-agent systems and their applications in the area of remote-sensing and emerging threats. To accomplish such tasks, an interdisciplinary research effort at Sandia National Laboratories are conducting tests in the fields of sensor technology, robotics, and multi-robotic and multi-agents architectures. Our goal is to coordinate a constellation of point sensors that optimizes spatial coverage and multivariate signal analysis using unmanned robotic vehicles (e.g., RATLERs, Robotic All-ten-sin Lunar Exploration Rover-class vehicles). Overall design methodology is to evolve complex collective behaviors realized through simple interaction (kinetic) physics and artificial intelligence to enable real-time operational responses to emerging threats. This paper focuses on our recent work understanding the dynamics of many-body systems using the physics-based hydrodynamic model of lattice gas automata. Three design features are investigated. One, for single-speed robots, a hexagonal nearest-neighbor interaction topology is necessary to preserve standard hydrodynamic flow. Two, adaptability, defined by the swarm's deformation rate, can be controlled through the hydrodynamic viscosity term, which, in turn, is defined by the local robotic interaction rules. Three, due to the inherent non-linearity of the dynamical equations describing large ensembles, development of stability criteria ensuring convergence to equilibrium states is developed by scaling information flow rates relative to a swarm's hydrodynamic flow rate. An initial test case simulates a swarm of twenty-five robots that maneuvers past an obstacle while following a moving target. A genetic algorithm optimizes applied nearest-neighbor forces in each of five spatial regions distributed over the simulation domain. Armed with knowledge, the
Xtoys: Cellular automata on xwindows
Creutz, M.
1995-08-15
Xtoys is a collection of xwindow programs for demonstrating simulations of various statistical models. Included are xising, for the two dimensional Ising model, xpotts, for the q-state Potts model, xautomalab, for a fairly general class of totalistic cellular automata, xsand, for the Bak-Tang-Wiesenfield model of self organized criticality, and xfires, a simple forest fire simulation. The programs should compile on any machine supporting xwindows.
Irregular Cellular Learning Automata.
Esnaashari, Mehdi; Meybodi, Mohammad Reza
2015-08-01
Cellular learning automaton (CLA) is a recently introduced model that combines cellular automaton (CA) and learning automaton (LA). The basic idea of CLA is to use LA to adjust the state transition probability of stochastic CA. This model has been used to solve problems in areas such as channel assignment in cellular networks, call admission control, image processing, and very large scale integration placement. In this paper, an extension of CLA called irregular CLA (ICLA) is introduced. This extension is obtained by removing the structure regularity assumption in CLA. Irregularity in the structure of ICLA is needed in some applications, such as computer networks, web mining, and grid computing. The concept of expediency has been introduced for ICLA and then, conditions under which an ICLA becomes expedient are analytically found. PMID:25291810
Universal map for cellular automata
NASA Astrophysics Data System (ADS)
García-Morales, V.
2012-08-01
A universal map is derived for all deterministic 1D cellular automata (CAs) containing no freely adjustable parameters and valid for any alphabet size and any neighborhood range (including non-symmetrical neighborhoods). The map can be extended to an arbitrary number of dimensions and topologies and to arbitrary order in time. Specific CA maps for the famous Conway's Game of Life and Wolfram's 256 elementary CAs are given. An induction method for CAs, based in the universal map, allows mathematical expressions for the orbits of a wide variety of elementary CAs to be systematically derived.
Symmetry analysis of cellular automata
NASA Astrophysics Data System (ADS)
García-Morales, V.
2013-01-01
By means of B-calculus [V. García-Morales, Phys. Lett. A 376 (2012) 2645] a universal map for deterministic cellular automata (CAs) has been derived. The latter is shown here to be invariant upon certain transformations (global complementation, reflection and shift). When constructing CA rules in terms of rules of lower range a new symmetry, “invariance under construction” is uncovered. Modular arithmetic is also reformulated within B-calculus and a new symmetry of certain totalistic CA rules, which calculate the Pascal simplices modulo an integer number p, is then also uncovered.
Beyond classical nucleation theory: A 2-D lattice-gas automata model
NASA Astrophysics Data System (ADS)
Hickey, Joseph
Nucleation is the first step in the formation of a new phase in a thermodynamic system. The Classical Nucleation Theory (CNT) is the traditional theory used to describe this phenomenon. The object of this thesis is to investigate nucleation beyond one of the most significant limitations of the CNT: the assumption that the surface tension of a nucleating cluster of the new phase is independent of the cluster's size and has the same value that it would have in the bulk of the new phase. In order to accomplish this, we consider a microscopic, two-dimensional Lattice Gas Automata (LGA) model of precipitate nucleation in a supersaturated system, with model input parameters Ess (solid particle-to-solid particle bonding energy), Esw (solid particle-to-water particle bonding energy), eta (next-to-nearest neighbour bonding coeffiicent in solid phase), and Cin (initial solute concentration). The LGA method was chosen for its advantages of easy implementation, low memory requirements, and fast computation speed. Analytical results for the system's concentration and the crystal radius as functions of time are derived and the former is fit to the simulation data in order to determine the system's equilibrium concentration. A mean first-passage time (MFPT) technique is used to obtain the nucleation rate and critical nucleus size from the simulation data. The nucleation rate and supersaturation are evaluated using a modification to the CNT that incorporates a two-dimensional, radius-dependent surface tension term. The Tolman parameter, delta, which controls the radius-dependence of the surface tension, decreases (increases) as a function of the magnitude of Ess (Esw), at fixed values of eta and Esw (Ess). On the other hand, delta increases as eta increases while E ss and Esw are held constant. The constant surface tension term of the CNT, Sigma0, increases (decreases) with increasing magnitudes of Ess (Esw) fixed values of Esw (Ess), and increases as eta is increased. Together
Aperiodicity in one-dimensional cellular automata
Jen, E.
1990-01-01
Cellular automata are a class of mathematical systems characterized by discreteness (in space, time, and state values), determinism, and local interaction. A certain class of one-dimensional, binary site-valued, nearest-neighbor automata is shown to generate infinitely many aperiodic temporal sequences from arbitrary finite initial conditions on an infinite lattice. The class of automaton rules that generate aperiodic temporal sequences are characterized by a particular form of injectivity in their interaction rules. Included are the nontrivial linear'' automaton rules (that is, rules for which the superposition principle holds); certain nonlinear automata that retain injectivity properties similar to those of linear automata; and a wider subset of nonlinear automata whose interaction rules satisfy a weaker form of injectivity together with certain symmetry conditions. A technique is outlined here that maps this last set of automata onto a linear automaton, and thereby establishes the aperiodicity of their temporal sequences. 12 refs., 3 figs.
Algorithmic crystal chemistry: A cellular automata approach
Krivovichev, S. V.
2012-01-15
Atomic-molecular mechanisms of crystal growth can be modeled based on crystallochemical information using cellular automata (a particular case of finite deterministic automata). In particular, the formation of heteropolyhedral layered complexes in uranyl selenates can be modeled applying a one-dimensional three-colored cellular automaton. The use of the theory of calculations (in particular, the theory of automata) in crystallography allows one to interpret crystal growth as a computational process (the realization of an algorithm or program with a finite number of steps).
Cellular automata to describe seismicity: A review
NASA Astrophysics Data System (ADS)
Jiménez, Abigail
2013-12-01
Cellular Automata have been used in the literature to describe seismicity. We first historically introduce Cellular Automata and provide some important definitions. Then we proceed to review the most important models, most of them being variations of the spring-block model proposed by Burridge and Knopoff, and describe the most important results obtained from them. We discuss the relation with criticality and also describe some models that try to reproduce real data.
Statistical Mechanics of Surjective Cellular Automata
NASA Astrophysics Data System (ADS)
Kari, Jarkko; Taati, Siamak
2015-09-01
Reversible cellular automata are seen as microscopic physical models, and their states of macroscopic equilibrium are described using invariant probability measures. We establish a connection between the invariance of Gibbs measures and the conservation of additive quantities in surjective cellular automata. Namely, we show that the simplex of shift-invariant Gibbs measures associated to a Hamiltonian is invariant under a surjective cellular automaton if and only if the cellular automaton conserves the Hamiltonian. A special case is the (well-known) invariance of the uniform Bernoulli measure under surjective cellular automata, which corresponds to the conservation of the trivial Hamiltonian. As an application, we obtain results indicating the lack of (non-trivial) Gibbs or Markov invariant measures for "sufficiently chaotic" cellular automata. We discuss the relevance of the randomization property of algebraic cellular automata to the problem of approach to macroscopic equilibrium, and pose several open questions. As an aside, a shift-invariant pre-image of a Gibbs measure under a pre-injective factor map between shifts of finite type turns out to be always a Gibbs measure. We provide a sufficient condition under which the image of a Gibbs measure under a pre-injective factor map is not a Gibbs measure. We point out a potential application of pre-injective factor maps as a tool in the study of phase transitions in statistical mechanical models.
Quantum features of natural cellular automata
NASA Astrophysics Data System (ADS)
Elze, Hans-Thomas
2016-03-01
Cellular automata can show well known features of quantum mechanics, such as a linear rule according to which they evolve and which resembles a discretized version of the Schrödinger equation. This includes corresponding conservation laws. The class of “natural” Hamiltonian cellular automata is based exclusively on integer-valued variables and couplings and their dynamics derives from an Action Principle. They can be mapped reversibly to continuum models by applying Sampling Theory. Thus, “deformed” quantum mechanical models with a finite discreteness scale l are obtained, which for l → 0 reproduce familiar continuum results. We have recently demonstrated that such automata can form “multipartite” systems consistently with the tensor product structures of nonrelativistic many-body quantum mechanics, while interacting and maintaining the linear evolution. Consequently, the Superposition Principle fully applies for such primitive discrete deterministic automata and their composites and can produce the essential quantum effects of interference and entanglement.
Cellular Automata Generalized To An Inferential System
NASA Astrophysics Data System (ADS)
Blower, David J.
2007-11-01
Stephen Wolfram popularized elementary one-dimensional cellular automata in his book, A New Kind of Science. Among many remarkable things, he proved that one of these cellular automata was a Universal Turing Machine. Such cellular automata can be interpreted in a different way by viewing them within the context of the formal manipulation rules from probability theory. Bayes's Theorem is the most famous of such formal rules. As a prelude, we recapitulate Jaynes's presentation of how probability theory generalizes classical logic using modus ponens as the canonical example. We emphasize the important conceptual standing of Boolean Algebra for the formal rules of probability manipulation and give an alternative demonstration augmenting and complementing Jaynes's derivation. We show the complementary roles played in arguments of this kind by Bayes's Theorem and joint probability tables. A good explanation for all of this is afforded by the expansion of any particular logic function via the disjunctive normal form (DNF). The DNF expansion is a useful heuristic emphasized in this exposition because such expansions point out where relevant 0s should be placed in the joint probability tables for logic functions involving any number of variables. It then becomes a straightforward exercise to rely on Boolean Algebra, Bayes's Theorem, and joint probability tables in extrapolating to Wolfram's cellular automata. Cellular automata are seen as purely deductive systems, just like classical logic, which probability theory is then able to generalize. Thus, any uncertainties which we might like to introduce into the discussion about cellular automata are handled with ease via the familiar inferential path. Most importantly, the difficult problem of predicting what cellular automata will do in the far future is treated like any inferential prediction problem.
Cellular automata modeling of weld solidification structure
Dress, W.B.; Zacharia, T.; Radhakrishnan, B.
1993-12-31
The authors explore the use of cellular automata in modeling arc-welding processes. A brief discussion of cellular automata and their previous use in micro-scale solidification simulations is presented. Macro-scale thermal calculations for arc-welding at a thin plate are shown to give good quantitative and qualitative results. Combining the two calculations in a single cellular array provides a realistic simulation of grain growth in a welding process. Results of simulating solidification in a moving melt pool in a poly-crystalline alloy sheet are presented.
Cellular-automata method for phase unwrapping
Ghiglia, D.C.; Mastin, G.A.; Romero, L.A.
1987-01-01
Research into two-dimensional phase unwrapping has uncovered interesting and troublesome inconsistencies that cause path-dependent results. Cellular automata, which are simple, discrete mathematical systems, offered promise of computation in nondirectional, parallel manner. A cellular automaton was discovered that can unwrap consistent phase data in n dimensions in a path-independent manner and can automatically accommodate noise-induced (pointlike) inconsistencies and arbitrary boundary conditions (region partitioning). For data with regional (nonpointlike) inconsistencies, no phase-unwrapping algorithm will converge, including the cellular-automata approach. However, the automata method permits more simple visualization of the regional inconsistencies. Examples of its behavior on one- and two-dimensional data are presented.
Infrared image enhancement using Cellular Automata
NASA Astrophysics Data System (ADS)
Qi, Wei; Han, Jing; Zhang, Yi; Bai, Lian-fa
2016-05-01
Image enhancement is a crucial technique for infrared images. The clear image details are important for improving the quality of infrared images in computer vision. In this paper, we propose a new enhancement method based on two priors via Cellular Automata. First, we directly learn the gradient distribution prior from the images via Cellular Automata. Second, considering the importance of image details, we propose a new gradient distribution error to encode the structure information via Cellular Automata. Finally, an iterative method is applied to remap the original image based on two priors, further improving the quality of enhanced image. Our method is simple in implementation, easy to understand, extensible to accommodate other vision tasks, and produces more accurate results. Experiments show that the proposed method performs better than other methods using qualitative and quantitative measures.
Fuzzy cellular automata models in immunology
NASA Astrophysics Data System (ADS)
Ahmed, E.
1996-10-01
The self-nonself character of antigens is considered to be fuzzy. The Chowdhury et al. cellular automata model is generalized accordingly. New steady states are found. The first corresponds to a below-normal help and suppression and is proposed to be related to autoimmune diseases. The second corresponds to a below-normal B-cell level.
Dynamical Systems Perspective of Wolfram's Cellular Automata
NASA Astrophysics Data System (ADS)
Courbage, M.; Kamiński, B.
2013-01-01
Leon Chua, following Wolfram, devoted a big effort to understand deeply the wealth of complexity of the rules of all elementary one-dimensional cellular automata from the point of view of the nonlinear dynamicist. Here we complete this point of view by a dynamical system perspective, extending them to the limit of infinite number of sites.
Self-reproduction in small cellular automata
NASA Astrophysics Data System (ADS)
Byl, John
1989-01-01
Self-reproduction in cellular automata is discussed with reference to Langton's criteria as to what constitutes genuine self-reproduction. It is found that it is possible to construct self-reproducing structures that are substantially less complex than that presented by Langton.
Benchmark study between FIDAP and a cellular automata code
Akau, R.L.; Stockman, H.W.
1991-01-01
A fluid flow benchmark exercise was conducted to compare results between a cellular automata code and FIDAP. Cellular automata codes are free from gridding constraints, and are generally used to model slow (Reynolds number {approx} 1) flows around complex solid obstacles. However, the accuracy of cellular automata codes at higher Reynolds numbers, where inertial terms are significant, is not well-documented. In order to validate the cellular automata code, two fluids problems were investigated. For both problems, flow was assumed to be laminar, two-dimensional, isothermal, incompressible and periodic. Results showed that the cellular automata code simulated the overall behavior of the flow field. 7 refs., 12 figs.
Additive Cellular Automata and Volume Growth
NASA Astrophysics Data System (ADS)
Ward, Thomas B.
2000-09-01
A class of dynamical systems associated to rings of S-integers in rational function fields is described. General results about these systems give a rather complete description of the well-known dynamics in one-dimensional additive cellular automata with prime alphabet, including simple formulæ for the topological entropy and the number of periodic configurations. For these systems the periodic points are uniformly distributed along some subsequence with respect to the maximal measure, and in particular are dense. Periodic points may be constructed arbitrarily close to a given configuration, and rationality of the dynamical zeta function is characterized. Throughout the emphasis is to place this particular family of cellular automata into the wider context of S-integer dynamical systems, and to show how the arithmetic of rational function fields determines their behaviour. Using a covering space the dynamics of additive cellular automata are related to a form of hyperbolicity in completions of rational function fields. This expresses the topological entropy of the automata directly in terms of volume growth in the covering space.
NASA Astrophysics Data System (ADS)
Hickey, Joseph; L'Heureux, Ivan
2013-02-01
The constant surface tension assumption of the Classical Nucleation Theory (CNT) is known to be flawed. In order to probe beyond this limitation, we consider a microscopic, two-dimensional Lattice-Gas Automata (LGA) model of nucleation in a supersaturated system, with model input parameters Ess (solid particle-to-solid particle bonding energy), Esw (solid particle-to-water bonding energy), η (next-to-nearest-neighbor bonding coefficient in solid phase), and Cin (initial solute concentration). The LGA method has the advantages of easy implementation, low memory requirements, and fast computation speed. Analytical results for the system's concentration and the crystal radius as functions of time are derived and the former is fit to the simulation data in order to determine the equilibrium concentration. The “Mean First-Passage Time” technique is used to obtain the nucleation rate and critical nucleus size from the simulation data. The nucleation rate and supersaturation data are evaluated using a modification to the CNT that incorporates a two-dimensional radius-dependent surface tension term. The Tolman parameter, δ, which controls the radius dependence of the surface tension, decreases (increases) as a function of the magnitude of Ess (Esw), at fixed values of η and Esw (Ess). On the other hand, δ increases as η increases while Ess and Esw are held constant. The constant surface tension term of the CNT, Σ0, increases (decreases) with increasing magnitudes of Ess (Esw) at fixed values of Esw (Ess) and increases as η is increased. Σ0 increases linearly as a function of the change in energy during an attachment or detachment reaction, |ΔE|, however, with a slope less than that predicted for a crystal that is uniformly packed at maximum density. These results indicate an increase in the radius-dependent surface tension, Σ, with respect to increasing magnitude of the difference between Ess and Esw.
GARDENS OF EDEN OF ELEMENTARY CELLULAR AUTOMATA.
Barrett, C. L.; Chen, W. Y. C.; Reidys, C. M.
2001-01-01
Using de Bruijn graphs, we give a characterization of elementary cellular automata on the linear lattice that do not have any Gardens of Eden. It turns out that one can easily recoginze a CA that does not have any Gardens of Eden by looking at its de Bruijn graph. We also present a sufficient condition for the set of words accepted by a CA not to constitute a finite-complement language.
Cellular automata model for citrus variegated chlorosis.
Martins, M L; Ceotto, G; Alves, S G; Bufon, C C; Silva, J M; Laranjeira, F F
2000-11-01
A cellular automata model is proposed to analyze the progress of citrus variegated chlorosis epidemics in São Paulo orange plantations. In this model epidemiological and environmental features, such as motility of sharpshooter vectors that perform Lévy flights, level of plant hydric and nutritional stress, and seasonal climatic effects, are included. The observed epidemic data were quantitatively reproduced by the proposed model on varying the parameters controlling vector motility, plant stress, and initial population of diseased plants. PMID:11102058
Configurable Cellular Automata for Pseudorandom Number Generation
NASA Astrophysics Data System (ADS)
Quieta, Marie Therese; Guan, Sheng-Uei
This paper proposes a generalized structure of cellular automata (CA) — the configurable cellular automata (CoCA). With selected properties from programmable CA (PCA) and controllable CA (CCA), a new approach to cellular automata is developed. In CoCA, the cells are dynamically reconfigured at run-time via a control CA. Reconfiguration of a cell simply means varying the properties of that cell with time. Some examples of properties to be reconfigured are rule selection, boundary condition, and radius. While the objective of this paper is to propose CoCA as a new CA method, the main focus is to design a CoCA that can function as a good pseudorandom number generator (PRNG). As a PRNG, CoCA can be a suitable candidate as it can pass 17 out of 18 Diehard tests with 31 cells. CoCA PRNG's performance based on Diehard test is considered superior over other CA PRNG works. Moreover, CoCA opens new rooms for research not only in the field of random number generation, but in modeling complex systems as well.
Astrobiological complexity with probabilistic cellular automata.
Vukotić, Branislav; Ćirković, Milan M
2012-08-01
The search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling the astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous space of the input parameters. We perform a simple clustering analysis of typical astrobiological histories with "Copernican" choice of input parameters and discuss the relevant boundary conditions of practical importance for planning and guiding empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches. PMID:22832998
Astrobiological Complexity with Probabilistic Cellular Automata
NASA Astrophysics Data System (ADS)
Vukotić, Branislav; Ćirković, Milan M.
2012-08-01
The search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling the astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous space of the input parameters. We perform a simple clustering analysis of typical astrobiological histories with "Copernican" choice of input parameters and discuss the relevant boundary conditions of practical importance for planning and guiding empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.
Nonsynchronous updating in the multiverse of cellular automata.
Reia, Sandro M; Kinouchi, Osame
2015-04-01
In this paper we study updating effects on cellular automata rule space. We consider a subset of 6144 order-3 automata from the space of 262144 bidimensional outer-totalistic rules. We compare synchronous to asynchronous and sequential updatings. Focusing on two automata, we discuss how update changes destroy typical structures of these rules. Besides, we show that the first-order phase transition in the multiverse of synchronous cellular automata, revealed with the use of a recently introduced control parameter, seems to be robust not only to changes in update schema but also to different initial densities. PMID:25974442
Nonsynchronous updating in the multiverse of cellular automata
NASA Astrophysics Data System (ADS)
Reia, Sandro M.; Kinouchi, Osame
2015-04-01
In this paper we study updating effects on cellular automata rule space. We consider a subset of 6144 order-3 automata from the space of 262144 bidimensional outer-totalistic rules. We compare synchronous to asynchronous and sequential updatings. Focusing on two automata, we discuss how update changes destroy typical structures of these rules. Besides, we show that the first-order phase transition in the multiverse of synchronous cellular automata, revealed with the use of a recently introduced control parameter, seems to be robust not only to changes in update schema but also to different initial densities.
SELF-ORGANIZED CRITICALITY AND CELLULAR AUTOMATA
CREUTZ,M.
2007-01-01
Cellular automata provide a fascinating class of dynamical systems based on very simple rules of evolution yet capable of displaying highly complex behavior. These include simplified models for many phenomena seen in nature. Among other things, they provide insight into self-organized criticality, wherein dissipative systems naturally drive themselves to a critical state with important phenomena occurring over a wide range of length and the scales. This article begins with an overview of self-organized criticality. This is followed by a discussion of a few examples of simple cellular automaton systems, some of which may exhibit critical behavior. Finally, some of the fascinating exact mathematical properties of the Bak-Tang-Wiesenfeld sand-pile model [1] are discussed.
Weyl, Dirac and Maxwell Quantum Cellular Automata
NASA Astrophysics Data System (ADS)
Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo; Tosini, Alessandro
2015-10-01
Recent advances on quantum foundations achieved the derivation of free quantum field theory from general principles, without referring to mechanical notions and relativistic invariance. From the aforementioned principles a quantum cellular automata (QCA) theory follows, whose relativistic limit of small wave-vector provides the free dynamics of quantum field theory. The QCA theory can be regarded as an extended quantum field theory that describes in a unified way all scales ranging from an hypothetical discrete Planck scale up to the usual Fermi scale. The present paper reviews the automaton theory for the Weyl field, and the composite automata for Dirac and Maxwell fields. We then give a simple analysis of the dynamics in the momentum space in terms of a dispersive differential equation for narrowband wave-packets. We then review the phenomenology of the free-field automaton and consider possible visible effects arising from the discreteness of the framework. We conclude introducing the consequences of the automaton dispersion relation, leading to a deformed Lorentz covariance and to possible effects on the thermodynamics of ideal gases.
Particles and Patterns in Cellular Automata
Jen, E.; Das, R.; Beasley, C.E.
1999-06-03
This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). Our objective has been to develop tools for studying particle interactions in a class of dynamical systems characterized by discreteness, determinism, local interaction, and an inherently parallel form of evolution. These systems can be described by cellular automata (CA) and the behavior we studied has improved our understanding of the nature of patterns generated by CAs, their ability to perform global computations, and their relationship to continuous dynamical systems. We have also developed a rule-table mathematics that enables one to custom-design CA rule tables to generate patterns of specified types, or to perform specified computational tasks.
Complex dynamics of cellular automata rule 119
NASA Astrophysics Data System (ADS)
Chen, Fang-Fang; Chen, Fang-Yue
2009-03-01
In this paper, the dynamical behaviors of cellular automata rule 119 are studied from the viewpoint of symbolic dynamics in the bi-infinite symbolic sequence space Σ2. It is shown that there exists one Bernoulli-measure global attractor of rule 119, which is also the nonwandering set of the rule. Moreover, it is demonstrated that rule 119 is topologically mixing on the global attractor and possesses the positive topological entropy. Therefore, rule 119 is chaotic in the sense of both Li-Yorke and Devaney on the global attractor. It is interesting that rule 119, a member of Wolfram’s class II which was said to be simple as periodic before, actually possesses a chaotic global attractor in Σ2. Finally, it is noted that the method presented in this work is also applicable to studying the dynamics of other rules, especially the 112 Bernoulli-shift rules therein.
Traffic jam dynamics in stochastic cellular automata
Nagel, K. |; Schreckenberg, M.
1995-09-01
Simple models for particles hopping on a grid (cellular automata) are used to simulate (single lane) traffic flow. Despite their simplicity, these models are astonishingly realistic in reproducing start-stop-waves and realistic fundamental diagrams. One can use these models to investigate traffic phenomena near maximum flow. A so-called phase transition at average maximum flow is visible in the life-times of jams. The resulting dynamic picture is consistent with recent fluid-dynamical results by Kuehne/Kerner/Konhaeuser, and with Treiterer`s hysteresis description. This places CA models between car-following models and fluid-dynamical models for traffic flow. CA models are tested in projects in Los Alamos (USA) and in NRW (Germany) for large scale microsimulations of network traffic.
NASA Astrophysics Data System (ADS)
Vanag, Vladimir K.
1999-05-01
Spatially extended dynamical systems are ubiquitous and include such things as insect and animal populations; complex chemical, technological, and geochemical processes; humanity itself, and much more. It is clearly desirable to have a certain universal tool with which the highly complex behaviour of nonlinear dynamical systems can be analyzed and modelled. For this purpose, cellular automata seem to be good candidates. In the present review, emphasis is placed on the possibilities that various types of probabilistic cellular automata (PCA), such as DSMC (direct simulation Monte Carlo) and LGCA (lattice-gas cellular automata), offer. The methods are primarily designed for modelling spatially extended dynamical systems with inner fluctuations accounted for. For the Willamowskii-Roessler and Oregonator models, PCA applications to the following problems are illustrated: the effect of fluctuations on the dynamics of nonlinear systems; Turing structure formation; the effect of hydrodynamic modes on the behaviour of nonlinear chemical systems (stirring effects); bifurcation changes in the dynamical regimes of complex systems with restricted geometry or low spatial dimension; and the description of chemical systems in microemulsions.
Cellular automata based byte error correcting codes over finite fields
NASA Astrophysics Data System (ADS)
Köroğlu, Mehmet E.; Şiap, İrfan; Akın, Hasan
2012-08-01
Reed-Solomon codes are very convenient for burst error correction which occurs frequently in applications, but as the number of errors increase, the circuit structure of implementing Reed-Solomon codes becomes very complex. An alternative solution to this problem is the modular and regular structure of cellular automata which can be constructed with VLSI economically. Therefore, in recent years, cellular automata have became an important tool for error correcting codes. For the first time, cellular automata based byte error correcting codes analogous to extended Reed-Solomon codes over binary fields was studied by Chowdhury et al. [1] and Bhaumik et al. [2] improved the coding-decoding scheme. In this study cellular automata based double-byte error correcting codes are generalized from binary fields to primitive finite fields Zp.
Lattice gas cellular automation model for rippling and aggregation in myxobacteria
NASA Astrophysics Data System (ADS)
Alber, Mark S.; Jiang, Yi; Kiskowski, Maria A.
2004-05-01
A lattice gas cellular automation (LGCA) model is used to simulate rippling and aggregation in myxobacteria. An efficient way of representing cells of different cell size, shape and orientation is presented that may be easily extended to model later stages of fruiting body formation. This LGCA model is designed to investigate whether a refractory period, a minimum response time, a maximum oscillation period and non-linear dependence of reversals of cells on C-factor are necessary assumptions for rippling. It is shown that a refractory period of 2-3 min, a minimum response time of up to 1 min and no maximum oscillation period best reproduce rippling in the experiments of Myxococcus xanthus. Non-linear dependence of reversals on C-factor is critical at high cell density. Quantitative simulations demonstrate that the increase in wavelength of ripples when a culture is diluted with non-signaling cells can be explained entirely by the decreased density of C-signaling cells. This result further supports the hypothesis that levels of C-signaling quantitatively depend on and modulate cell density. Analysis of the interpenetrating high density waves shows the presence of a phase shift analogous to the phase shift of interpenetrating solitons. Finally, a model for swarming, aggregation and early fruiting body formation is presented.
Unstable vicinal crystal growth from cellular automata
NASA Astrophysics Data System (ADS)
Krasteva, A.; Popova, H.; KrzyŻewski, F.; Załuska-Kotur, M.; Tonchev, V.
2016-03-01
In order to study the unstable step motion on vicinal crystal surfaces we devise vicinal Cellular Automata. Each cell from the colony has value equal to its height in the vicinal, initially the steps are regularly distributed. Another array keeps the adatoms, initially distributed randomly over the surface. The growth rule defines that each adatom at right nearest neighbor position to a (multi-) step attaches to it. The update of whole colony is performed at once and then time increases. This execution of the growth rule is followed by compensation of the consumed particles and by diffusional update(s) of the adatom population. Two principal sources of instability are employed - biased diffusion and infinite inverse Ehrlich-Schwoebel barrier (iiSE). Since these factors are not opposed by step-step repulsion the formation of multi-steps is observed but in general the step bunches preserve a finite width. We monitor the developing surface patterns and quantify the observations by scaling laws with focus on the eventual transition from diffusion-limited to kinetics-limited phenomenon. The time-scaling exponent of the bunch size N is 1/2 for the case of biased diffusion and 1/3 for the case of iiSE. Additional distinction is possible based on the time-scaling exponents of the sizes of multi-step Nmulti, these are 0.36÷0.4 (for biased diffusion) and 1/4 (iiSE).
Quantum Features of Natural Cellular Automata
NASA Astrophysics Data System (ADS)
Elze, Hans-Thomas
We review the properties of discrete and integer-valued, hence "natural", cellular automata (CA), a particular class of which comprises "Hamiltonian CA" with equations of motion that bear strong similarities to Hamilton's equations, despite presenting discrete updating rules. The resulting dynamics is linear in the same sense as unitary evolution described by the Schrödinger equation. Employing Shannon's Sampling Theorem, we construct an invertible map between such CA and continuous quantum mechanical models which incorporate a fundamental discreteness scale. This leads to one-to-one correspondence of quantum mechanical and CA conservation laws. In order to illuminate the all-important issue of linearity, we presently introduce an extension of the class of CA incorporating nonlinearities. We argue that these imply non-local effects in the continuous quantum mechanical description of intrinsically local discrete CA, enforcing locality entails linearity. We recall the construction of admissible CA observables and the existence of solutions of the modified dispersion relation for stationary states, besides discussing next steps of the deconstruction of quantum mechanical models in terms of deterministic CA.
Cellular automata modelling of biomolecular networks dynamics.
Bonchev, D; Thomas, S; Apte, A; Kier, L B
2010-01-01
The modelling of biological systems dynamics is traditionally performed by ordinary differential equations (ODEs). When dealing with intracellular networks of genes, proteins and metabolites, however, this approach is hindered by network complexity and the lack of experimental kinetic parameters. This opened the field for other modelling techniques, such as cellular automata (CA) and agent-based modelling (ABM). This article reviews this emerging field of studies on network dynamics in molecular biology. The basics of the CA technique are discussed along with an extensive list of related software and websites. The application of CA to networks of biochemical reactions is exemplified in detail by the case studies of the mitogen-activated protein kinase (MAPK) signalling pathway, the FAS-ligand (FASL)-induced and Bcl-2-related apoptosis. The potential of the CA method to model basic pathways patterns, to identify ways to control pathway dynamics and to help in generating strategies to fight with cancer is demonstrated. The different line of CA applications presented includes the search for the best-performing network motifs, an analysis of importance for effective intracellular signalling and pathway cross-talk. PMID:20373215
On the Reversibility of 150 Wolfram Cellular Automata
NASA Astrophysics Data System (ADS)
Del Rey, A. Martín; Sánchez, G. Rodríguez
In this paper, the reversibility problem for 150 Wolfram cellular automata is tackled for null boundary conditions. It is explicitly shown that the reversibility depends on the number of cells of the cellular automaton. The inverse cellular automaton for each case is also computed.
Cellular Automata Ideas in Digital Circuits and Switching Theory.
ERIC Educational Resources Information Center
Siwak, Pawel P.
1985-01-01
Presents two examples which illustrate the usefulness of ideas from cellular automata. First, Lee's algorithm is recalled and its cellular nature shown. Then a problem from digraphs, which has arisen from analyzing predecessing configurations in the famous Conway's "game of life," is considered. (Author/JN)
Lempel-Ziv complexity analysis of one dimensional cellular automata.
Estevez-Rams, E; Lora-Serrano, R; Nunes, C A J; Aragón-Fernández, B
2015-12-01
Lempel-Ziv complexity measure has been used to estimate the entropy density of a string. It is defined as the number of factors in a production factorization of a string. In this contribution, we show that its use can be extended, by using the normalized information distance, to study the spatiotemporal evolution of random initial configurations under cellular automata rules. In particular, the transfer information from time consecutive configurations is studied, as well as the sensitivity to perturbed initial conditions. The behavior of the cellular automata rules can be grouped in different classes, but no single grouping captures the whole nature of the involved rules. The analysis carried out is particularly appropriate for studying the computational processing capabilities of cellular automata rules. PMID:26723145
Lempel-Ziv complexity analysis of one dimensional cellular automata
NASA Astrophysics Data System (ADS)
Estevez-Rams, E.; Lora-Serrano, R.; Nunes, C. A. J.; Aragón-Fernández, B.
2015-12-01
Lempel-Ziv complexity measure has been used to estimate the entropy density of a string. It is defined as the number of factors in a production factorization of a string. In this contribution, we show that its use can be extended, by using the normalized information distance, to study the spatiotemporal evolution of random initial configurations under cellular automata rules. In particular, the transfer information from time consecutive configurations is studied, as well as the sensitivity to perturbed initial conditions. The behavior of the cellular automata rules can be grouped in different classes, but no single grouping captures the whole nature of the involved rules. The analysis carried out is particularly appropriate for studying the computational processing capabilities of cellular automata rules.
The 3-dimensional cellular automata for HIV infection
NASA Astrophysics Data System (ADS)
Mo, Youbin; Ren, Bin; Yang, Wencao; Shuai, Jianwei
2014-04-01
The HIV infection dynamics is discussed in detail with a 3-dimensional cellular automata model in this paper. The model can reproduce the three-phase development, i.e., the acute period, the asymptotic period and the AIDS period, observed in the HIV-infected patients in a clinic. We show that the 3D HIV model performs a better robustness on the model parameters than the 2D cellular automata. Furthermore, we reveal that the occurrence of a perpetual source to successively generate infectious waves to spread to the whole system drives the model from the asymptotic state to the AIDS state.
Synchronization of One-Dimensional Stochastically Coupled Cellular Automata
NASA Astrophysics Data System (ADS)
Mrowinski, Maciej J.; Kosinski, Robert A.
In this work the authors study synchronization resulting from the asymmetric stochastic coupling between two one-dimensional chaotic cellular automata and provide a simple analytical model to explain this phenomenon. The authors also study synchronization in a more general case, using sets of rules with a different number of states and different values of Langton's parameter λ.
Return of the Quantum Cellular Automata: Episode VI
NASA Astrophysics Data System (ADS)
Carr, Lincoln D.; Hillberry, Logan E.; Rall, Patrick; Halpern, Nicole Yunger; Bao, Ning; Montangero, Simone
2016-05-01
There are now over 150 quantum simulators or analog quantum computers worldwide. Although exploring quantum phase transitions, many-body localization, and the generalized Gibbs ensemble are exciting and worthwhile endeavors, there are totally untapped directions we have not yet pursued. One of these is quantum cellular automata. In the past a principal goal of quantum cellular automata was to reproduce continuum single particle quantum physics such as the Schrodinger or Dirac equation from simple rule sets. Now that we begin to really understand entanglement and many-body quantum physics at a deeper level, quantum cellular automata present new possibilities. We explore several time evolution schemes on simple spin chains leading to high degrees of quantum complexity and nontrivial quantum dynamics. We explain how the 256 known classical elementary cellular automata reduce to just a few exciting quantum cases. Our analysis tools include mutual information based complex networks as well as more familiar quantifiers like sound speed and diffusion rate. Funded by NSF and AFOSR.
Boolean linear differential operators on elementary cellular automata
NASA Astrophysics Data System (ADS)
Martín Del Rey, Ángel
2014-12-01
In this paper, the notion of boolean linear differential operator (BLDO) on elementary cellular automata (ECA) is introduced and some of their more important properties are studied. Special attention is paid to those differential operators whose coefficients are the ECA with rule numbers 90 and 150.
Lattice gas hydrodynamics: Theory and simulations
Hasslacher, B.
1993-01-01
The first successful application of a microscopic analogy to create a skeleton cellular automaton and analyze it with statistical mechanical tools, was the work of Frisch, Hasslacher and Pomeau on the Navier-Stokes equation in two and three dimensions. This has become a very large research area with lattice gas models and methods being used for both fundamental investigations into the foundations of statistical mechanics and a large number of diverse applications. This present research was devoted to enlarging the fundamental scope of lattice gas models and proved quite successful. Since the beginning of this proposal, cellular automata have been constructed for statistical mechanical models, fluids, diffusion and shock systems in fundamental investigations. In applied areas, there are now excellent lattice gas models for complex flows through porous media, chemical reaction and combustion dynamics, multiphase flow systems, and fluid mixtures with natural boundaries. With extended cellular fluid models, one can do problems with arbitrary pairwise potentials. Recently, these have been applied to such problems as non-newtonian or polymeric liquids and a mixture of immiscible fluids passing through fractal or spongelike media in two and three dimensions. This proposal has contributed to and enlarged the scope of this work.
Lattice gas hydrodynamics: Theory and simulations
Hasslacher, B.
1993-01-01
The first successful application of a microscopic analogy to create a skeleton cellular automaton and analyze it with statistical mechanical tools, was the work of Frisch, Hasslacher and Pomeau on the Navier-Stokes equation in two and three dimensions. This has become a very large research area with lattice gas models and methods being used for both fundamental investigations into the foundations of statistical mechanics and a large number of diverse applications. This present research was devoted to enlarging the fundamental scope of lattice gas models and proved successful. Since the beginning of this proposal, cellular automata have been constructed for statistical mechanical models, fluids, diffusion and shock systems in fundamental investigations. In applied areas, there are now excellent lattice gas models for complex flows through porous media, chemical reaction and combustion dynamics, multiphase flow systems, and fluid mixtures with natural boundaries. With extended cellular fluid models, one can do problems with arbitrary pairwise potentials. Recently, these have been applied to such problems as non-newtonian or polymeric liquids and a mixture of immiscible fluids passing through fractal or spongelike media in two and three dimensions. This proposal has contributed to and enlarged the scope of this work.
Lattice-gas approach to semiconductor device simulation
NASA Astrophysics Data System (ADS)
Ancona, M. G.
1990-12-01
A new approach to semiconductor device simulation is presented which is based on a lattice-gas or cellular-automata model and is quite similar to methods recently explored in fluid dynamics. The approach obtains a stochastic solution to the diffusion-drift partial differential equations describing electron transport in semiconductors. The lattice-gas method appears to be fairly well-suited to electron transport simulation with its ability to handle complex geometry, its ease of programming and its stability being some key advantages. In addition, we show that the structure of the model itself—its Boolean character—leads to a partial inclusion of electron degeneracy effects. Finally, we make a preliminary assessment of the performance of the diffusion-drift lattice-gas model, finding it to be competitive with conventional approaches when its inherent parallelism is fully exploited.
Quantum dot spin cellular automata for realizing a quantum processor
NASA Astrophysics Data System (ADS)
Bayat, Abolfazl; Creffield, Charles E.; Jefferson, John H.; Pepper, Michael; Bose, Sougato
2015-10-01
We show how single quantum dots, each hosting a singlet-triplet qubit, can be placed in arrays to build a spin quantum cellular automaton. A fast (˜10 ns) deterministic coherent singlet-triplet filtering, as opposed to current incoherent tunneling/slow-adiabatic based quantum gates (operation time ˜300 ns), can be employed to produce a two-qubit gate through capacitive (electrostatic) couplings that can operate over significant distances. This is the coherent version of the widely discussed charge and nano-magnet cellular automata, and would increase speed, reduce dissipation, and perform quantum computation while interfacing smoothly with its classical counterpart. This combines the best of two worlds—the coherence of spin pairs known from quantum technologies, and the strength and range of electrostatic couplings from the charge-based classical cellular automata. Significantly our system has zero electric dipole moment during the whole operation process, thereby increasing its charge dephasing time.
Extended Self Organised Criticality in Asynchronously Tuned Cellular Automata
NASA Astrophysics Data System (ADS)
Gunji, Yukio-Pegio
2014-12-01
Systems at a critical point in phase transitions can be regarded as being relevant to biological complex behaviour. Such a perspective can only result, in a mathematical consistent manner, from a recursive structure. We implement a recursive structure based on updating by asynchronously tuned elementary cellular automata (AT ECA), and show that a large class of elementary cellular automata (ECA) can reveal critical behavior due to the asynchronous updating and tuning.We show that the obtained criticality coincides with the criticality in phase transitions of asynchronous ECA with respect to density decay, and that multiple distributed ECAs, synchronously updated, can emulate critical behavior in AT ECA. Our approach draws on concepts and tools from category and set theory, in particular on "adjunction dualities" of pairs of adjoint functors.
Construction of living cellular automata using the Physarum plasmodium
NASA Astrophysics Data System (ADS)
Shirakawa, Tomohiro; Sato, Hiroshi; Ishiguro, Shinji
2015-04-01
The plasmodium of Physarum polycephalum is a unicellular and multinuclear giant amoeba that has an amorphous cell body. To clearly observe how the plasmodium makes decisions in its motile and exploratory behaviours, we developed a new experimental system to pseudo-discretize the motility of the organism. In our experimental space that has agar surfaces arranged in a two-dimensional lattice, the continuous and omnidirectional movement of the plasmodium was limited to the stepwise one, and the direction of the locomotion was also limited to four neighbours. In such an experimental system, a cellular automata-like system was constructed using the living cell. We further analysed the exploratory behaviours of the plasmodium by duplicating the experimental results in the simulation models of cellular automata. As a result, it was revealed that the behaviours of the plasmodium are not reproduced by only local state transition rules; and for the reproduction, a kind of historical rule setting is needed.
Identifying patterns from one-rule-firing cellular automata.
Shin, Jae Kyun
2011-01-01
A new firing scheme for cellular automata in which only one rule is fired at a time produces myriad patterns. In addition to geometric patterns, natural patterns such as flowers and snow crystals were also generated. This study proposes an efficient method identifying the patterns using a minimal number of digits. Complexity of the generated patterns is discussed in terms of the shapes and colors of the patterns. PMID:21087150
A full computation-relevant topological dynamics classification of elementary cellular automata
NASA Astrophysics Data System (ADS)
Schüle, Martin; Stoop, Ruedi
2012-12-01
Cellular automata are both computational and dynamical systems. We give a complete classification of the dynamic behaviour of elementary cellular automata (ECA) in terms of fundamental dynamic system notions such as sensitivity and chaoticity. The "complex" ECA emerge to be sensitive, but not chaotic and not eventually weakly periodic. Based on this classification, we conjecture that elementary cellular automata capable of carrying out complex computations, such as needed for Turing-universality, are at the "edge of chaos."
Cellular automata method for phase unwrapping
Ghiglia, D.C.; Mastin, G.A.
1985-10-01
Research into phase unwrapping has led to the discovery of a cellular automaton that can unwrap phase in one- and two-dimensions. The extremely interesting behavior of the automaton and the aesthetically pleasing structure that evolves from repeated iterates will be presented.
Analytical Solution of Traffic Cellular Automata Model
NASA Astrophysics Data System (ADS)
Lo, Shih-Ching; Hsu, Chia-Hung
2009-08-01
Complex traffic system seems to be simulated successfully by cellular automaton (CA) models. Various models are developed to understand single-lane traffic, multilane traffic, lane-changing behavior and network traffic situations. However, the result of CA simulation can only be obtained after massive microscopic computation. Although, the mean field theory (MFT) has been studied to be the approximation of CA model, the MFT can only applied to the simple CA rules or small value of parameters. In this study, we simulate traffic flow by the NaSch model under different combination of parameters, which are maximal speed, dawdling probability and density. After that, the position of critical density, the slope of free-flow and congested regime are observed and modeled due to the simulated data. Finally, the coefficients of the model will be calibrated by the simulated data and the analytical solution of traffic CA is obtained.
Cellular Automata with network incubation in information technology diffusion
NASA Astrophysics Data System (ADS)
Guseo, Renato; Guidolin, Mariangela
2010-06-01
Innovation diffusion of network goods determines direct network externalities that depress sales for long periods and delay full benefits. We model this effect through a multiplicative dynamic market potential driven by a latent individual threshold embedded in a special Cellular Automata representation. The corresponding mean field approximation of its aggregate version is a Riccati equation with a closed form solution. This allows the detection of a change-point time separating an incubation period from a subsequent take-off due to a collective threshold (critical mass). Weighted nonlinear least squares are the main inferential methodology. An application is analysed with reference to USA fax machine diffusion.
A Programmable Cellular-Automata Polarized Dirac Vacuum
NASA Astrophysics Data System (ADS)
Osoroma, Drahcir S.
2013-09-01
We explore properties of a `Least Cosmological Unit' (LCU) as an inherent spacetime raster tiling or tessellating the unique backcloth of Holographic Anthropic Multiverse (HAM) cosmology as an array of programmable cellular automata. The HAM vacuum is a scale-invariant HD extension of a covariant polarized Dirac vacuum with `bumps' and `holes' typically described by extended electromagnetic theory corresponding to an Einstein energy-dependent spacetime metric admitting a periodic photon mass. The new cosmology incorporates a unique form of M-Theoretic Calabi-Yau-Poincaré Dodecadedral-AdS5-DS5space (PDS) with mirror symmetry best described by an HD extension of Cramer's Transactional Interpretation when integrated also with an HD extension of the de Broglie-Bohm-Vigier causal interpretation of quantum theory. We incorporate a unique form of large-scale additional dimensionality (LSXD) bearing some similarity to that conceived by Randall and Sundrum; and extend the fundamental basis of our model to the Unified Field, UF. A Sagnac Effect rf-pulsed incursive resonance hierarchy is utilized to manipulate and ballistically program the geometric-topological properties of this putative LSXD space-spacetime network. The model is empirically testable; and it is proposed that a variety of new technologies will arise from ballistic programming of tessellated LCU vacuum cellular automata.
From deterministic cellular automata to coupled map lattices
NASA Astrophysics Data System (ADS)
García-Morales, Vladimir
2016-07-01
A general mathematical method is presented for the systematic construction of coupled map lattices (CMLs) out of deterministic cellular automata (CAs). The entire CA rule space is addressed by means of a universal map for CAs that we have recently derived and that is not dependent on any freely adjustable parameters. The CMLs thus constructed are termed real-valued deterministic cellular automata (RDCA) and encompass all deterministic CAs in rule space in the asymptotic limit κ \\to 0 of a continuous parameter κ. Thus, RDCAs generalize CAs in such a way that they constitute CMLs when κ is finite and nonvanishing. In the limit κ \\to ∞ all RDCAs are shown to exhibit a global homogeneous fixed-point that attracts all initial conditions. A new bifurcation is discovered for RDCAs and its location is exactly determined from the linear stability analysis of the global quiescent state. In this bifurcation, fuzziness gradually begins to intrude in a purely deterministic CA-like dynamics. The mathematical method presented allows to get insight in some highly nontrivial behavior found after the bifurcation.
Simulation of root forms using cellular automata model
NASA Astrophysics Data System (ADS)
Winarno, Nanang; Prima, Eka Cahya; Afifah, Ratih Mega Ayu
2016-02-01
This research aims to produce a simulation program for root forms using cellular automata model. Stephen Wolfram in his book entitled "A New Kind of Science" discusses the formation rules based on the statistical analysis. In accordance with Stephen Wolfram's investigation, the research will develop a basic idea of computer program using Delphi 7 programming language. To best of our knowledge, there is no previous research developing a simulation describing root forms using the cellular automata model compared to the natural root form with the presence of stone addition as the disturbance. The result shows that (1) the simulation used four rules comparing results of the program towards the natural photographs and each rule had shown different root forms; (2) the stone disturbances prevent the root growth and the multiplication of root forms had been successfully modeled. Therefore, this research had added some stones, which have size of 120 cells placed randomly in the soil. Like in nature, stones cannot be penetrated by plant roots. The result showed that it is very likely to further develop the program of simulating root forms by 50 variations.
Cellular automata and complex dynamics of driven elastic media
Coppersmith, S.N.; Littlewodd, P.B.; Sibani, P.
1995-12-01
Several systems of importance in condensed matter physics can be modelled as an elastic medium in a disordered environment and driven by an external force. In the simplest cases, the equation of motion involves competition between a local non-linear potential (fluctuating in space) and elastic coupling, as well as relaxational (inertialess) dynamics. Despite a simple mathematical description, the interactions between many degrees of freedom lead to the emergence of time and length scales much longer than those set by the microscopic dynamics. Extensive computations have improved the understanding of the behavior of such models, but full solutions of the equations of motion for very large systems are time-consuming and may obscure important physical principles in a massive volume of output. The development of cellular automata models has been crucial, both in conceptual simplification and in allowing the collection of data on many replicas of very large systems. We will discuss how the marriage of cellular automata models and parallel computation on a MasPar MP-1216 computer has helped to elucidate the dynamical properties of these many-degree-of-freedom systems.
Physical modeling of traffic with stochastic cellular automata
Schreckenberg, M.; Nagel, K. |
1995-09-01
A new type of probabilistic cellular automaton for the physical description of single and multilane traffic is presented. In this model space, time and the velocity of the cars are represented by integer numbers (as usual in cellular automata) with local update rules for the velocity. The model is very efficient for both numerical simulations and analytical investigations. The numerical results from extensive simulations reproduce very well data taken from real traffic (e.g. fundamental diagrams). Several analytical results for the model are presented as well as new approximation schemes for stationary traffic. In addition the relation to continuum hydrodynamic theory (Lighthill-Whitham) and the follow-the-leader models is discussed. The model is part of an interdisciplinary research program in Northrhine-Westfalia (``NRW Forschungsverbund Verkehrssimulation``) for the construction of a large scale microsimulation model for network traffic, supported by the government of NRW.
Critical Probabilities and Convergence Time of Percolation Probabilistic Cellular Automata
NASA Astrophysics Data System (ADS)
Taggi, Lorenzo
2015-05-01
This paper considers a class of probabilistic cellular automata undergoing a phase transition with an absorbing state. Denoting by the neighbourhood of site , the transition probability is if or otherwise, . For any there exists a non-trivial critical probability that separates a phase with an absorbing state from a fluctuating phase. This paper studies how the neighbourhood affects the value of and provides lower bounds for . Furthermore, by using dynamic renormalization techniques, we prove that the expected convergence time of the processes on a finite space with periodic boundaries grows exponentially (resp. logarithmically) with the system size if (resp. ). This provides a partial answer to an open problem in Toom et al. (Stochastic Cellular Systems: Ergodicity, Memory, Morphogenesis, pp. 1-182. Manchester University Press, Manchester, 1990; Topics in Contemporary Probability and its Applications, pp. 117-157. CRC Press, Boca Raton, 1995).
Simulations of Living Cell Origins Using a Cellular Automata Model
NASA Astrophysics Data System (ADS)
Ishida, Takeshi
2014-04-01
Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.
Lattice gas hydrodynamics in two and three dimensions
Frisch, U.; d'Humieres, D.; Hasslacher, B.; Lallemand, P.; Pomeau, Y.; Rivet, J.P.
1986-01-01
Hydrodynamical phenomena can be simulated by discrete lattice gas models obeing cellular automata rules (U. Frisch, B. Hasslacher, and Y. Pomeau, Phys. Rev. Lett. 56, 1505, (1986); D. d'Humieres, P. Lallemand, and U. Frisch, Europhys. Lett. 2, 291, (1986)). It is here shown for a class of D-dimensional lattice gas models how the macrodynamical (large-scale) equations for the densities of microscopically conserved quantities can be systematically derived from the underlying exact ''microdynamical'' Boolean equations. With suitable restrictions on the crystallographic symmetries of the lattice and after proper limits are taken, various standard fluid dynamical equations are obtained, including the incompressible Navier-Stokes equations in two and three dimensions. The transport coefficients appearing in the macrodynamical equations are obtained using variants of fluctuation-dissipation and Boltzmann formalisms adapted to fully discrete situations.
Lattice gas and lattice Boltzmann computational physics
Chen, S.
1993-05-01
Recent developments of the lattice gas automata method and its extension to the lattice Boltzmann method have provided new computational schemes for solving a variety of partial differential equations and modeling different physics systems. The lattice gas method, regarded as the simplest microscopic and kinetic approach which generates meaningful macroscopic dynamics, is fully parallel and can be easily programmed on parallel machines. In this talk, the author will review basic principles of the lattice gas and lattice Boltzmann method, its mathematical foundation and its numerical implementation. A detailed comparison of the lattice Boltzmann method with the lattice gas technique and other traditional numerical schemes, including the finite-difference scheme and the pseudo-spectral method, for solving the Navier-Stokes hydrodynamic fluid flows, will be discussed. Recent achievements of the lattice gas and the the lattice Boltzmann method and their applications in surface phenomena, spinodal decomposition and pattern formation in chemical reaction-diffusion systems will be presented.
Quantifying a cellular automata simulation of electric vehicles
NASA Astrophysics Data System (ADS)
Hill, Graeme; Bell, Margaret; Blythe, Phil
2014-12-01
Within this work the Nagel-Schreckenberg (NS) cellular automata is used to simulate a basic cyclic road network. Results from SwitchEV, a real world Electric Vehicle trial which has collected more than two years of detailed electric vehicle data, are used to quantify the results of the NS automata, demonstrating similar power consumption behavior to that observed in the experimental results. In particular the efficiency of the electric vehicles reduces as the vehicle density increases, due in part to the reduced efficiency of EVs at low speeds, but also due to the energy consumption inherent in changing speeds. Further work shows the results from introducing spatially restricted speed restriction. In general it can be seen that induced congestion from spatially transient events propagates back through the road network and alters the energy and efficiency profile of the simulated vehicles, both before and after the speed restriction. Vehicles upstream from the restriction show a reduced energy usage and an increased efficiency, and vehicles downstream show an initial large increase in energy usage as they accelerate away from the speed restriction.
Definition and evolution of quantum cellular automata with two qubits per cell
Karafyllidis, Ioannis G.
2004-10-01
Studies of quantum computer implementations suggest cellular quantum computer architectures. These architectures can simulate the evolution of quantum cellular automata, which can possibly simulate both quantum and classical physical systems and processes. It is however known that except for the trivial case, unitary evolution of one-dimensional homogeneous quantum cellular automata with one qubit per cell is not possible. Quantum cellular automata that comprise two qubits per cell are defined and their evolution is studied using a quantum computer simulator. The evolution is unitary and its linearity manifests itself as a periodic structure in the probability distribution patterns.
A cellular automata approach for modeling surface water runoff
NASA Astrophysics Data System (ADS)
Jozefik, Zoltan; Nanu Frechen, Tobias; Hinz, Christoph; Schmidt, Heiko
2015-04-01
This abstract reports the development and application of a two-dimensional cellular automata based model, which couples the dynamics of overland flow, infiltration processes and surface evolution through sediment transport. The natural hill slopes are represented by their topographic elevation and spatially varying soil properties infiltration rates and surface roughness coefficients. This model allows modeling of Hortonian overland flow and infiltration during complex rainfall events. An advantage of the cellular automata approach over the kinematic wave equations is that wet/dry interfaces that often appear with rainfall overland flows can be accurately captured and are not a source of numerical instabilities. An adaptive explicit time stepping scheme allows for rainfall events to be adequately resolved in time, while large time steps are taken during dry periods to provide for simulation run time efficiency. The time step is constrained by the CFL condition and mass conservation considerations. The spatial discretization is shown to be first-order accurate. For validation purposes, hydrographs for non-infiltrating and infiltrating plates are compared to the kinematic wave analytic solutions and data taken from literature [1,2]. Results show that our cellular automata model quantitatively accurately reproduces hydrograph patterns. However, recent works have showed that even through the hydrograph is satisfyingly reproduced, the flow field within the plot might be inaccurate [3]. For a more stringent validation, we compare steady state velocity, water flux, and water depth fields to rainfall simulation experiments conducted in Thies, Senegal [3]. Comparisons show that our model is able to accurately capture these flow properties. Currently, a sediment transport and deposition module is being implemented and tested. [1] M. Rousseau, O. Cerdan, O. Delestre, F. Dupros, F. James, S. Cordier. Overland flow modeling with the Shallow Water Equation using a well balanced
Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity
Louis, S.J.; Raines, G.L.
2003-01-01
We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.
An Asynchronous Cellular Automata-Based Adaptive Illumination Facility
NASA Astrophysics Data System (ADS)
Bandini, Stefania; Bonomi, Andrea; Vizzari, Giuseppe; Acconci, Vito
The term Ambient Intelligence refers to electronic environments that are sensitive and responsive to the presence of people; in the described scenario the environment itself is endowed with a set of sensors (to perceive humans or other physical entities such as dogs, bicycles, etc.), interacting with a set of actuators (lights) that choose their actions (i.e. state of illumination) in an attempt improve the overall experience of these users. The model for the interaction and action of sensors and actuators is an asynchronous Cellular Automata (CA) with memory, supporting a self-organization of the system as a response to the presence and movements of people inside it. The paper will introduce the model, as well as an ad hoc user interface for the specification of the relevant parameters of the CA transition rule that determines the overall system behaviour.
Game level layout generation using evolved cellular automata
NASA Astrophysics Data System (ADS)
Pech, Andrew; Masek, Martin; Lam, Chiou-Peng; Hingston, Philip
2016-01-01
Design of level layouts typically involves the production of a set of levels which are different, yet display a consistent style based on the purpose of a particular level. In this paper, a new approach to the generation of unique level layouts, based on a target set of attributes, is presented. These attributes, which are learned automatically from an example layout, are used for the off-line evolution of a set of cellular automata rules. These rules can then be used for the real-time generation of level layouts that meet the target parameters. The approach is demonstrated on a set of maze-like level layouts. Results are presented to show the effect of various CA parameters and rule representation.
Narrow-band oscillations in probabilistic cellular automata.
Puljic, Marko; Kozma, Robert
2008-08-01
Dynamical properties of neural populations are studied using probabilistic cellular automata. Previous work demonstrated the emergence of critical behavior as the function of system noise and density of long-range axonal connections. Finite-size scaling theory identified critical properties, which were consistent with properties of a weak Ising universality class. The present work extends the studies to neural populations with excitatory and inhibitory interactions. It is shown that the populations can exhibit narrow-band oscillations when confined to a range of inhibition levels, with clear boundaries marking the parameter region of prominent oscillations. Phase diagrams have been constructed to characterize unimodal, bimodal, and quadromodal oscillatory states. The significance of these findings is discussed in the context of large-scale narrow-band oscillations in neural tissues, as observed in electroencephalographic and magnetoencephalographic measurements. PMID:18850928
Cellular automata simulation of medication-induced autoimmune diseases
NASA Astrophysics Data System (ADS)
Stauffer, Dietrich; Proykova, Ana
2004-01-01
We implement the cellular automata model proposed by Stauffer and Weisbuch in 1992 to describe the response of the immune system to antigens in the presence of medications. The model contains two thresholds, θ1 and θ2, suggested by de Boer, Segel, and Perelson to present the minimum field needed to stimulate the proliferation of the receptors and to suppress it, respectively. The influence of the drug is mimicked by increasing the second threshold, thus enhancing the immune response. If this increase is too strong, the immune response is triggered in the whole immune repertoire, causing it to attack the own body. This effect is seen in our simulations to depend both on the ratio of the thresholds and on their absolute values.
Dynamics of HIV infection on 2D cellular automata
NASA Astrophysics Data System (ADS)
Benyoussef, A.; HafidAllah, N. El; ElKenz, A.; Ez-Zahraouy, H.; Loulidi, M.
2003-05-01
We use a cellular automata approach to describe the interactions of the immune system with the human immunodeficiency virus (HIV). We study the evolution of HIV infection, particularly in the clinical latency period. The results we have obtained show the existence of four different behaviours in the plane of death rate of virus-death rate of infected T cell. These regions meet at a critical point, where the virus density and the infected T cell density remain invariant during the evolution of disease. We have introduced two kinds of treatments, the protease inhibitors and the RT inhibitors, in order to study their effects on the evolution of HIV infection. These treatments are powerful in decreasing the density of the virus in the blood and the delay of the AIDS onset.
An image encryption based on elementary cellular automata
NASA Astrophysics Data System (ADS)
Jin, Jun
2012-12-01
This paper presents a new image encryption/decryption scheme. The behavior of a number of elementary cellular automata (ECA) of length 8 with periodic boundary conditions is investigated. It is found in the state-transition diagram that some ECA rules result in state attractors which satisfies basic requirement of the encryption scheme that can perform encrypting function to transform the pixel values. The generation of these attractors depending only on the rule and initial state of the CA, without any additional hardware cost for the implementation, and requires minimized computational resources. Simulation results on some grayscale and color images show that the proposed image encryption method satisfies the properties of confusion and diffusion, execution speed and has perfect information concealing.
Mosquito population dynamics from cellular automata-based simulation
NASA Astrophysics Data System (ADS)
Syafarina, Inna; Sadikin, Rifki; Nuraini, Nuning
2016-02-01
In this paper we present an innovative model for simulating mosquito-vector population dynamics. The simulation consist of two stages: demography and dispersal dynamics. For demography simulation, we follow the existing model for modeling a mosquito life cycles. Moreover, we use cellular automata-based model for simulating dispersal of the vector. In simulation, each individual vector is able to move to other grid based on a random walk. Our model is also capable to represent immunity factor for each grid. We simulate the model to evaluate its correctness. Based on the simulations, we can conclude that our model is correct. However, our model need to be improved to find a realistic parameters to match real data.
Cellular automata simulation of traffic including cars and bicycles
NASA Astrophysics Data System (ADS)
Vasic, Jelena; Ruskin, Heather J.
2012-04-01
As 'greening' of all aspects of human activity becomes mainstream, transportation science is also increasingly focused around sustainability. Modal co-existence between motorised and non-motorised traffic on urban networks is, in this context, of particular interest for traffic flow modelling. The main modelling problems here are posed by the heterogeneity of vehicles, including size and dynamics, and by the complex interactions at intersections. Herein we address these with a novel technique, based on one-dimensional cellular automata components, for modelling network infrastructure and its occupancy by vehicles. We use this modelling approach, together with a corresponding vehicle behaviour model, to simulate combined car and bicycle traffic for two elemental scenarios-examples of components that would be used in the building of an arbitrary network. Results of simulations performed on these scenarios, (i) a stretch of road and (ii) an intersection causing conflict between cars and bicycles sharing a lane, are presented and analysed.
Density Effects in Cellular Automata Models of Granular Materials
NASA Astrophysics Data System (ADS)
Baxter, G. W.; Behringer, R. P.
1996-11-01
We have studied density waves in a two dimensional cellular automata model of the gravity-driven flow of ellipsoidal particles through a wedge-shaped hopper(G. W. Baxter and R. P. Behringer, PRA 42), 1017 (1990).. The density variations form above the apex of the hopper and move upward, opposite the grain motion, with a well defined velocity. The waves become more pronounced as they travel. Density waves and alignment of particles are competing effects. Nearest-neighbor interactions which lead to alignment of neighboring grains can destroy the density waves. The relationship of these results to previous studies of density waves in real granular materials will be discussed(G. W. Baxter, R. P. Behringer, T. Fagert, and G. A. Johnson, PRL 62), 2825 (1989)..
Are nonlinear discrete cellular automata compatible with quantum mechanics?
NASA Astrophysics Data System (ADS)
Elze, Hans-Thomas
2015-07-01
We consider discrete and integer-valued cellular automata (CA). A particular class of which comprises “Hamiltonian CA” with equations of motion that bear similarities to Hamilton's equations, while they present discrete updating rules. The dynamics is linear, quite similar to unitary evolution described by the Schrödinger equation. This has been essential in our construction of an invertible map between such CA and continuous quantum mechanical models, which incorporate a fundamental discreteness scale. Based on Shannon's sampling theory, it leads, for example, to a one-to-one relation between quantum mechanical and CA conservation laws. The important issue of linearity of the theory is examined here by incorporating higher-order nonlinearities into the underlying action. These produce inconsistent nonlocal (in time) effects when trying to describe continuously such nonlinear CA. Therefore, in the present framework, only linear CA and local quantum mechanical dynamics are compatible.
Renormalisation of 2D Cellular Automata with an Absorbing State
NASA Astrophysics Data System (ADS)
Weaver, Iain S.; Prügel-Bennett, Adam
2015-04-01
We describe a real-space renormalisation scheme for non-equilibrium probabilistic cellular automata (PCA) models, and apply it to a two-dimensional binary PCA. An exact renormalisation scheme is rare, and therefore we provide a method for computing the stationary probability distribution of states for such models with which to weight the renormalisation, effectively minimising the error in the scale transformation. While a mean-field approximation is trivial, we use the principle of maximum entropy to incorporate nearest-neighbour spin-correlations in the steady-state probability distribution. In doing so we find the fixed point of the renormalisation is modified by the steady-state approximation order.
Modeling the Sinoatrial Node by Cellular Automata with Irregular Topology
NASA Astrophysics Data System (ADS)
Makowiec, Danuta
The role of irregularity in intercellular connections is studied in the first natural human pacemaker called the sinoatrial node by modeling with the Greenberg-Hastings cellular automata. Facts from modern physiology about the sinoatrial node drive modeling. Heterogeneity between cell connections is reproduced by a rewiring procedure applied to a square lattice. The Greenberg-Hastings rule, representing the intrinsic cellular dynamics, is modified to imitate self-excitation of each pacemaker cell. Moreover, interactions with nearest neighbors are changed to heterogeneous ones by enhancing horizontal connections. Stationary states of the modeled system emerge as self-organized robust oscillatory states. Since the sinoatrial node role relies on a single cell cyclic activity, properties of single cells are studied. It appears that the strength and diversity of cellular oscillations depend directly on properties of intrinsic cellular dynamics. But these oscillations also depend on the underlying topology. Moderate nonuniformity of intercellular connections are found vital for proper function of the sinoatrial node, namely, for producing robust oscillatory states that are able to respond effectively to the autonomic system control.
Evolving cellular automata to perform computations. Final technical report
Crutchfield, J.P.; Mitchell, M.
1998-04-01
The overall goals of the project are to determine the usefulness of genetic algorithms (GAs) in designing spatially extended parallel systems to perform computational tasks and to develop theoretical frameworks both for understanding the computation in the systems evolved by the GA and for understanding the evolutionary process which successful systems are designed. In the original proposal the authors scheduled the first year of the project to be devoted to experimental grounding. During the first year they developed the simulation and graphics software necessary for doing experiments and analysis on one dimensional cellular automata (CAs), and they performed extensive experiments and analysis concerning two computational tasks--density classification and synchronization. Details of these experiments and results, and a list of resulting publications, were given in the 1994--1995 report. The authors scheduled the second year to be devoted to theoretical development. (A third year, to be funded by the National Science Foundation, will be devoted to applications.) Accordingly, most of the effort during the second year was spent on theory, both of GAs and of the CAs that they evolve. A central notion is that of the computational strategy of a CA, which they formalize in terms of domains, particles, and particle interactions. This formalization builds on the computational mechanics framework developed by Crutchfield and Hanson for understanding intrinsic computation in spatially extended dynamical systems. They have made significant progress in the following areas: (1) statistical dynamics of GAs; (2) formalizing particle based computation in cellular automata; and (3) computation in two-dimensional CAs.
Lattice gas hydrodynamics: Theory and simulations. Final report
Hasslacher, B.
1993-05-01
The first successful application of a microscopic analogy to create a skeleton cellular automaton and analyze it with statistical mechanical tools, was the work of Frisch, Hasslacher and Pomeau on the Navier-Stokes equation in two and three dimensions. This has become a very large research area with lattice gas models and methods being used for both fundamental investigations into the foundations of statistical mechanics and a large number of diverse applications. This present research was devoted to enlarging the fundamental scope of lattice gas models and proved quite successful. Since the beginning of this proposal, cellular automata have been constructed for statistical mechanical models, fluids, diffusion and shock systems in fundamental investigations. In applied areas, there are now excellent lattice gas models for complex flows through porous media, chemical reaction and combustion dynamics, multiphase flow systems, and fluid mixtures with natural boundaries. With extended cellular fluid models, one can do problems with arbitrary pairwise potentials. Recently, these have been applied to such problems as non-newtonian or polymeric liquids and a mixture of immiscible fluids passing through fractal or spongelike media in two and three dimensions. This proposal has contributed to and enlarged the scope of this work.
Quantum-cellular-automata quantum computing with endohedral fullerenes
NASA Astrophysics Data System (ADS)
Twamley, J.
2003-05-01
We present a scheme to perform universal quantum computation using global addressing techniques as applied to a physical system of endohedrally doped fullerenes. The system consists of an ABAB linear array of group-V endohedrally doped fullerenes. Each molecule spin site consists of a nuclear spin coupled via a hyperfine interaction to an electron spin. The electron spin of each molecule is in a quartet ground state S=3/2. Neighboring molecular electron spins are coupled via a magnetic dipole interaction. We find that an all-electron construction of a quantum cellular automaton is frustrated due to the degeneracy of the electronic transitions. However, we can construct a quantum-cellular-automata quantum computing architecture using these molecules by encoding the quantum information on the nuclear spins while using the electron spins as a local bus. We deduce the NMR and ESR pulses required to execute the basic cellular automaton operation and obtain a rough figure of merit for the number of gate operations per decoherence time. We find that this figure of merit compares well with other physical quantum computer proposals. We argue that the proposed architecture meets well the first four DiVincenzo criteria and we outline various routes toward meeting the fifth criterion: qubit readout.
Rule matrices, degree vectors, and preimages for cellular automata
Jen, E.
1989-01-01
Cellular automata are mathematical systems characterized by discreteness (in space, time, and state values), determinism, and local interaction. Few analytical techniques exist for such systems. The rule matrix and degree vectors of a cellular automaton -- both of which are determined a priori from the function defining the automaton, rather than a posteriori from simulations of its evolution -- are introduced here as tools for understanding certain qualitative features of automaton behavior. The rule matrix represents in convenient form the information contained in an automaton's rule table; the degree vectors are computed from the rule matrix, and reflect the extent to which the system is one-to-one'' versus many-to-one'' on restricted subspaces of the mapping. The rule matrix and degree vectors determine, for example, several aspects of the enumeration and prediction'' of preimages for spatial sequences evolving under the rule, where the preimages of a sequence S are defined to be the set of sequences mapped by the automaton rule onto S. 2 figs., 2 tabs.
1/ fα spectra in elementary cellular automata and fractal signals
NASA Astrophysics Data System (ADS)
Nagler, Jan; Claussen, Jens Christian
2005-06-01
We systematically compute the power spectra of the one-dimensional elementary cellular automata introduced by Wolfram. On the one hand our analysis reveals that one automaton displays 1/f spectra though considered as trivial, and on the other hand that various automata classified as chaotic or complex display no 1/f spectra. We model the results generalizing the recently investigated Sierpinski signal to a class of fractal signals that are tailored to produce 1/fα spectra. From the widespread occurrence of (elementary) cellular automata patterns in chemistry, physics, and computer sciences, there are various candidates to show spectra similar to our results.
Critical Behavior in Cellular Automata Animal Disease Transmission Model
NASA Astrophysics Data System (ADS)
Morley, P. D.; Chang, Julius
Using cellular automata model, we simulate the British Government Policy (BGP) in the 2001 foot and mouth epidemic in Great Britain. When clinical symptoms of the disease appeared in a farm, there is mandatory slaughter (culling) of all livestock in an infected premise (IP). Those farms in the neighboring of an IP (contiguous premise, CP), are also culled, aka nearest neighbor interaction. Farms where the disease may be prevalent from animal, human, vehicle or airborne transmission (dangerous contact, DC), are additionally culled, aka next-to-nearest neighbor interactions and lightning factor. The resulting mathematical model possesses a phase transition, whereupon if the physical disease transmission kernel exceeds a critical value, catastrophic loss of animals ensues. The nonlocal disease transport probability can be as low as 0.01% per day and the disease can still be in the high mortality phase. We show that the fundamental equation for sustainable disease transport is the criticality equation for neutron fission cascade. Finally, we calculate that the percentage of culled animals that are actually healthy is ≈30%.
Using Cellular Automata for Parking Recommendations in Smart Environments
Horng, Gwo-Jiun
2014-01-01
In this work, we propose an innovative adaptive recommendation mechanism for smart parking. The cognitive RF module will transmit the vehicle location information and the parking space requirements to the parking congestion computing center (PCCC) when the driver must find a parking space. Moreover, for the parking spaces, we use a cellular automata (CA) model mechanism that can adjust to full and not full parking lot situations. Here, the PCCC can compute the nearest parking lot, the parking lot status and the current or opposite driving direction with the vehicle location information. By considering the driving direction, we can determine when the vehicles must turn around and thus reduce road congestion and speed up finding a parking space. The recommendation will be sent to the drivers through a wireless communication cognitive radio (CR) model after the computation and analysis by the PCCC. The current study evaluates the performance of this approach by conducting computer simulations. The simulation results show the strengths of the proposed smart parking mechanism in terms of avoiding increased congestion and decreasing the time to find a parking space. PMID:25153671
Using cellular automata for parking recommendations in smart environments.
Horng, Gwo-Jiun
2014-01-01
In this work, we propose an innovative adaptive recommendation mechanism for smart parking. The cognitive RF module will transmit the vehicle location information and the parking space requirements to the parking congestion computing center (PCCC) when the driver must find a parking space. Moreover, for the parking spaces, we use a cellular automata (CA) model mechanism that can adjust to full and not full parking lot situations. Here, the PCCC can compute the nearest parking lot, the parking lot status and the current or opposite driving direction with the vehicle location information. By considering the driving direction, we can determine when the vehicles must turn around and thus reduce road congestion and speed up finding a parking space. The recommendation will be sent to the drivers through a wireless communication cognitive radio (CR) model after the computation and analysis by the PCCC. The current study evaluates the performance of this approach by conducting computer simulations. The simulation results show the strengths of the proposed smart parking mechanism in terms of avoiding increased congestion and decreasing the time to find a parking space. PMID:25153671
Study of hotspot repair using cellular automata method
NASA Astrophysics Data System (ADS)
Nagase, Norimasa; Takeuchi, Kanji; Sakurai, Mitsuo; Itoh, Takahisa; Okada, Tomoyuki
2014-07-01
In advanced semiconductor manufacturing, model-based optical proximity correction is commonly used to compensate for image errors. The final pattern is generated using correction values determined by lithography simulation. Image errors such as patterns with insufficient correction or patterns with excessive correction can be generated. These patterns with errors are called hotspots. Such errors are conventionally detected by lithography simulation of OPC patterns. When a hotspot is detected by lithography simulation, it has to be repaired manually or by repeated use of OPC tool. However, it is difficult to obtain correct pattern for a complicated shape, and the correction procedure may require a significant amount of additional processing. In order to solve this issue, we examine application of cellular automata (CA) method for hotspot correction. It is known that CA method can be used for weather or traffic analysis and prediction. In this report, we studied the CA method for deriving simple hotspot repair rule based on lattice cell-like models for light intensity distribution and OPC patterns. We will report on the results of hotspot correction technique with the OPC pattern using CA method.
A Study on Sequence Generation Powers of Small Cellular Automata
NASA Astrophysics Data System (ADS)
Kamikawa, Naoki; Umeo, Hiroshi
A model of cellular automata (CA) is considered to be a well-studied non-linear model of complex systems in which an infinite one-dimensional array of finite state machines (cells) updates itself in a synchronous manner according to a uniform local rule. A sequence generation problem on the CAs has been studied and many scholars proposed several real-time sequence generation algorithms for a variety of non-regular sequences such as prime, Fibonacci, and {2n|n=1,2,3,...} sequences etc. The paper describes the sequence generation powers of CAs having a small number of states, focusing on the CAs with one, two, and three internal states, respectively. The authors enumerate all of the sequences generated by two-state CAs and present several non-regular sequences that can be generated in real-time by three-state CAs, but not generated by any two-state CA. It is shown that there exists a sequence generation gap among the powers of those small CAs.
Modeling Second-Order Chemical Reactions using Cellular Automata
NASA Astrophysics Data System (ADS)
Hunter, N. E.; Barton, C. C.; Seybold, P. G.; Rizki, M. M.
2012-12-01
Cellular automata (CA) are discrete, agent-based, dynamic, iterated, mathematical computational models used to describe complex physical, biological, and chemical systems. Unlike the more computationally demanding molecular dynamics and Monte Carlo approaches, which use "force fields" to model molecular interactions, CA models employ a set of local rules. The traditional approach for modeling chemical reactions is to solve a set of simultaneous differential rate equations to give deterministic outcomes. CA models yield statistical outcomes for a finite number of ingredients. The deterministic solutions appear as limiting cases for conditions such as a large number of ingredients or a finite number of ingredients and many trials. Here we present a 2-dimensional, probabilistic CA model of a second-order gas phase reaction A + B → C, using a MATLAB basis. Beginning with a random distribution of ingredients A and B, formation of C emerges as the system evolves. The reaction rate can be varied based on the probability of favorable collisions of the reagents A and B. The model permits visualization of the conversion of reagents to products, and allows one to plot concentration vs. time for A, B and C. We test hypothetical reaction conditions such as: limiting reagents, the effects of reaction probabilities, and reagent concentrations on the reaction kinetics. The deterministic solutions of the reactions emerge as statistical averages in the limit of the large number of cells in the array. Modeling results for dynamic processes in the atmosphere will be presented.
A Cellular Automata occupant evacuation model considering gathering behavior
NASA Astrophysics Data System (ADS)
Zhao, Daoliang; Wang, Jinhui; Zhang, Xiaoliang; Wang, Xiaoqun
2015-01-01
A two-dimensional (2D) Cellular Automata (CA) random model is developed to simulate occupant evacuation considering gathering behavior. The movement process from random distribution to gathering state can be simulated based on the map of the position repulsive force. Evacuations with random distribution and gathering distribution are compared. Visual field means object area coverage considered by the individual in the current cell, representing by the radius of visual field, VR. The simulation results with VR = 1 and 2 have little difference while the simulation with VR = 3 can reasonably represent gathering process. When the occupant density is less than 0.64 people/m2, the time of gathering process increases very fast with the increase of density; when the density is larger than 1.28 people/m2, the time of gathering decreases with the increase of density. When the initial density is less than 1.44 people/m2, the evacuation times with random distribution are always less than those with gathering distribution. When the initial density is larger than 1.44 people/m2, the evacuation times with gathering or random distribution are almost the same. Our model can simulate the gathering and evacuation process with more than two rally points. The number and distribution of rally points can deeply affect the evacuation time.
Cellular automata model for traffic flow with safe driving conditions
NASA Astrophysics Data System (ADS)
María, Elena Lárraga; Luis, Alvarez-Icaza
2014-05-01
In this paper, a recently introduced cellular automata (CA) model is used for a statistical analysis of the inner microscopic structure of synchronized traffic flow. The analysis focuses on the formation and dissolution of clusters or platoons of vehicles, as the mechanism that causes the presence of this synchronized traffic state with a high flow. This platoon formation is one of the most interesting phenomena observed in traffic flows and plays an important role both in manual and automated highway systems (AHS). Simulation results, obtained from a single-lane system under periodic boundary conditions indicate that in the density region where the synchronized state is observed, most vehicles travel together in platoons with approximately the same speed and small spatial distances. The examination of velocity variations and individual vehicle gaps shows that the flow corresponding to the synchronized state is stable, safe and highly correlated. Moreover, results indicate that the observed platoon formation in real traffic is reproduced in simulations by the relation between vehicle headway and velocity that is embedded in the dynamics definition of the CA model.
Stochastic cellular automata model for wildland fire spread dynamics
NASA Astrophysics Data System (ADS)
Maduro Almeida, Rodolfo; Macau, Elbert E. N.
2011-03-01
A stochastic cellular automata model for wildland fire spread under flat terrain and no-wind conditions is proposed and its dynamics is characterized and analyzed. One of three possible states characterizes each cell: vegetation cell, burning cell and burnt cell. The dynamics of fire spread is modeled as a stochastic event with an effective fire spread probability S which is a function of three probabilities that characterize: the proportion of vegetation cells across the lattice, the probability of a burning cell becomes burnt, and the probability of the fire spread from a burning cell to a neighboring vegetation cell. A set of simulation experiments is performed to analyze the effects of different values of the three probabilities in the fire pattern. Monte-Carlo simulations indicate that there is a critical line in the model parameter space that separates the set of parameters which a fire can propagate from those for which it cannot propagate. Finally, the relevance of the model is discussed under the light of computational experiments that illustrate the capability of the model catches both the dynamical and static qualitative properties of fire propagation.
Robustness of a cellular automata model for the HIV infection
NASA Astrophysics Data System (ADS)
Figueirêdo, P. H.; Coutinho, S.; Zorzenon dos Santos, R. M.
2008-11-01
An investigation was conducted to study the robustness of the results obtained from the cellular automata model which describes the spread of the HIV infection within lymphoid tissues [R.M. Zorzenon dos Santos, S. Coutinho, Phys. Rev. Lett. 87 (2001) 168102]. The analysis focused on the dynamic behavior of the model when defined in lattices with different symmetries and dimensionalities. The results illustrated that the three-phase dynamics of the planar models suffered minor changes in relation to lattice symmetry variations and, while differences were observed regarding dimensionality changes, qualitative behavior was preserved. A further investigation was conducted into primary infection and sensitiveness of the latency period to variations of the model’s stochastic parameters over wide ranging values. The variables characterizing primary infection and the latency period exhibited power-law behavior when the stochastic parameters varied over a few orders of magnitude. The power-law exponents were approximately the same when lattice symmetry varied, but there was a significant variation when dimensionality changed from two to three. The dynamics of the three-dimensional model was also shown to be insensitive to variations of the deterministic parameters related to cell resistance to the infection, and the necessary time lag to mount the specific immune response to HIV variants. The robustness of the model demonstrated in this work reinforce that its basic hypothesis are consistent with the three-stage dynamic of the HIV infection observed in patients.
Some properties of the floor field cellular automata evacuation model
NASA Astrophysics Data System (ADS)
Gwizdałła, Tomasz M.
2015-02-01
We study the process of evacuation of pedestrians from the room with the given arrangement of doors and obstacles by using the cellular automata technique. The technique which became quite popular is characterized by the discretization of time as well as space. For such a discretized space we use so-called floor field model which generally corresponds to the description of every cell by some monotonic function of distance between this cell and the closest exit. We study several types of effects. We start from some general features of model like the kind of a neighborhood or the factors disrupting the motion. Then we analyze the influence of asymmetry and size on the evacuation time. Finally we show characteristics concerning different arrangements of exits and include a particular approach to the proxemics effects. The scaling analyses help us to distinguish these cases which just reflect the geometry of the system and those which depend also on the simulation properties. All calculations are performed for a wide range of initial densities corresponding to different occupation rates as described by the typical crowd counting techniques.
Cellular automata for traffic flow modeling. Final report
Benjaafar, S.; Dooley, K.; Setyawan, W.
1997-12-01
In this paper, the authors explore the usefulness of cellular automata to traffic flow modeling. The authors extend some of the existing CA models to capture characteristics of traffic flow that have not been possible to model using either conventional analytical models or existing simulation techniques. In particular, the authors examine higher moments of traffic flow and evaluate their effect on overall traffic performance. The behavior of these higher moments is found to be surprising, somewhat counter-intuitive, and to have important implications for design and control of traffic systems. For example, the authors show that the density of maximum throughput is near the density of maximum speed variance. Contrary to current practice, traffic should, therefore, be steered away from this density region. For deterministic systems the authors found traffic flow to possess a finite period which is highly sensitive to density in a non-monotonic fashion. The authors show that knowledge of this periodic behavior to be very useful in designing and controlling automated systems. These results are obtained for both single and two lane systems. For two lane systems, the authors also examine the relationship between lane changing behavior and flow performance. The authors show that the density of maximum land changing frequency occurs past the density of maximum throughput. Therefore, traffic should also be steered away from this density region.
Correlation velocities in heterogeneous bidirectional cellular automata traffic flow
NASA Astrophysics Data System (ADS)
Lakouari, N.; Bentaleb, K.; Ez-Zahraouy, H.; Benyoussef, A.
2015-12-01
Traffic flow behavior and velocity correlation in a bidirectional two lanes road are studied using Cellular Automata (CA) model within a mixture of fast and slow vehicles. The behaviors of the Inter-lane and Intra-lane Velocity Correlation Coefficients (V.C.C.) due to the interactions between vehicles in the same lane and the opposite lane as a function of the density are investigated. It is shown that high densities in one lane lead to large cluster in the second one, which decreases the Intra-lane velocity correlations and thereby form clusters in the opposite lane. Moreover, we have found that there is a critical density over which the Inter-lane V.C.C. occurs, but below which no Inter-lane V.C.C. happens. The spatiotemporal diagrams correspond to those regions are derived numerically. Furthermore, the effect of the overtaking probability in one lane on the Intra-lane V.C.C. in the other lane is also investigated. It is shown that the decrease of the overtaking probability in one lane decreases slightly the Intra-lane V.C.C. at intermediate density regimes in the other lane, which improves the current, as well as the Inter-lane V.C.C. decreases.
Gutowitz, H.A.
1988-11-17
In this lecture the map from a cellular automaton to a sequence of analytical approximations called the local structure theory is described. Connections are drawn between cellular automata and neural network models. It is suggested that the process by which a cellular automaton holds particular probability measures invariant is an appropriate model for biological memory. 20 figs.
A stochastic parameterization for deep convection using cellular automata
NASA Astrophysics Data System (ADS)
Bengtsson, L.; Steinheimer, M.; Bechtold, P.; Geleyn, J.
2012-12-01
Cumulus parameterizations used in most operational weather and climate models today are based on the mass-flux concept which took form in the early 1970's. In such schemes it is assumed that a unique relationship exists between the ensemble-average of the sub-grid convection, and the instantaneous state of the atmosphere in a vertical grid box column. However, such a relationship is unlikely to be described by a simple deterministic function (Palmer, 2011). Thus, because of the statistical nature of the parameterization challenge, it has been recognized by the community that it is important to introduce stochastic elements to the parameterizations (for instance: Plant and Craig, 2008, Khouider et al. 2010, Frenkel et al. 2011, Bentsson et al. 2011, but the list is far from exhaustive). There are undoubtedly many ways in which stochastisity can enter new developments. In this study we use a two-way interacting cellular automata (CA), as its intrinsic nature possesses many qualities interesting for deep convection parameterization. In the one-dimensional entraining plume approach, there is no parameterization of horizontal transport of heat, moisture or momentum due to cumulus convection. In reality, mass transport due to gravity waves that propagate in the horizontal can trigger new convection, important for the organization of deep convection (Huang, 1988). The self-organizational characteristics of the CA allows for lateral communication between adjacent NWP model grid-boxes, and temporal memory. Thus the CA scheme used in this study contain three interesting components for representation of cumulus convection, which are not present in the traditional one-dimensional bulk entraining plume method: horizontal communication, memory and stochastisity. The scheme is implemented in the high resolution regional NWP model ALARO, and simulations show enhanced organization of convective activity along squall-lines. Probabilistic evaluation demonstrate an enhanced spread in
Modeling pedestrian behaviors under attracting incidents using cellular automata
NASA Astrophysics Data System (ADS)
Chen, Yanyan; Chen, Ning; Wang, Yang; Wang, Zhenbao; Feng, Guochen
2015-08-01
Compared to vehicular flow, pedestrian flow is more complicated as it is free from the restriction of the lane and more flexible. Due to the lack of modeling pedestrian behaviors under attracting incidents (incidents which attract pedestrians around to gather), this paper proposes a new cellular automata model aiming to reproduce the behaviors induced by such attracting incidents. When attracting incidents occur, the proposed model will classify pedestrians around the incidents into three groups: the "unaffected" type, the "stopped" type and the "onlooking" type. The "unaffected" type represents the pedestrians who are not interested in the attracting incidents and its dynamics are the same as that under normal circumstances which are the main target in the previous works. The "stopped" type represents the pedestrians are somewhat interested in the attracting incidents, but unwilling to move close to the venues. Its dynamics are determined by "stopped" utility which can make the pedestrians stop for a while. The "onlooking" type represents the pedestrians who show strong interest in the attracting incidents and intend to move close to the venues to gain more information. The "onlooking" pedestrians will take a series of reactions to attracting incidents, such as approaching to the venues, stopping and watching the attracting incidents, leaving the venues, which have all been considered in the proposed model. The simulation results demonstrate that the proposed model can capture the macro-characteristics of pedestrian traffic flow under normal circumstances and possesses the fundamental characteristics of the pedestrian behaviors under attracting incidents around which a torus-shaped crowd is typically formed.
Validating Cellular Automata Lava Flow Emplacement Algorithms with Standard Benchmarks
NASA Astrophysics Data System (ADS)
Richardson, J. A.; Connor, L.; Charbonnier, S. J.; Connor, C.; Gallant, E.
2015-12-01
A major existing need in assessing lava flow simulators is a common set of validation benchmark tests. We propose three levels of benchmarks which test model output against increasingly complex standards. First, imulated lava flows should be morphologically identical, given changes in parameter space that should be inconsequential, such as slope direction. Second, lava flows simulated in simple parameter spaces can be tested against analytical solutions or empirical relationships seen in Bingham fluids. For instance, a lava flow simulated on a flat surface should produce a circular outline. Third, lava flows simulated over real world topography can be compared to recent real world lava flows, such as those at Tolbachik, Russia, and Fogo, Cape Verde. Success or failure of emplacement algorithms in these validation benchmarks can be determined using a Bayesian approach, which directly tests the ability of an emplacement algorithm to correctly forecast lava inundation. Here we focus on two posterior metrics, P(A|B) and P(¬A|¬B), which describe the positive and negative predictive value of flow algorithms. This is an improvement on less direct statistics such as model sensitivity and the Jaccard fitness coefficient. We have performed these validation benchmarks on a new, modular lava flow emplacement simulator that we have developed. This simulator, which we call MOLASSES, follows a Cellular Automata (CA) method. The code is developed in several interchangeable modules, which enables quick modification of the distribution algorithm from cell locations to their neighbors. By assessing several different distribution schemes with the benchmark tests, we have improved the performance of MOLASSES to correctly match early stages of the 2012-3 Tolbachik Flow, Kamchakta Russia, to 80%. We also can evaluate model performance given uncertain input parameters using a Monte Carlo setup. This illuminates sensitivity to model uncertainty.
Generic framework for mining cellular automata models on protein-folding simulations.
Diaz, N; Tischer, I
2016-01-01
Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined. PMID:27323045
A novel image encryption algorithm using chaos and reversible cellular automata
NASA Astrophysics Data System (ADS)
Wang, Xingyuan; Luan, Dapeng
2013-11-01
In this paper, a novel image encryption scheme is proposed based on reversible cellular automata (RCA) combining chaos. In this algorithm, an intertwining logistic map with complex behavior and periodic boundary reversible cellular automata are used. We split each pixel of image into units of 4 bits, then adopt pseudorandom key stream generated by the intertwining logistic map to permute these units in confusion stage. And in diffusion stage, two-dimensional reversible cellular automata which are discrete dynamical systems are applied to iterate many rounds to achieve diffusion on bit-level, in which we only consider the higher 4 bits in a pixel because the higher 4 bits carry almost the information of an image. Theoretical analysis and experimental results demonstrate the proposed algorithm achieves a high security level and processes good performance against common attacks like differential attack and statistical attack. This algorithm belongs to the class of symmetric systems.
Is there a sharp phase transition for deterministic cellular automata
Wootters, W.K. Los Alamos National Lab., NM Williams Coll., Williamstown, MA . Dept. of Physics); Langton, C.G. )
1990-01-01
Previous work has suggested that there is a kind of phase transition between deterministic automata exhibiting periodic behavior and those exhibiting chaotic behavior. However, unlike the usual phase transitions of physics, this transition takes place over a range of values of the parameter rather than at a specific value. The present paper asks whether the transition can be made sharp, either by taking the limit of an infinitely large rule table, or by changing the parameter in terms of which the space of automata is explored. We find strong evidence that, for the class of automata we consider, the transition does become sharp in the limit of an infinite number of symbols, the size of the neighborhood being held fixed. Our work also suggests an alternative parameter in terms of which it is likely that the transition will become fairly sharp even if one does not increase the number of symbols. In the course of our analysis, we find that mean field theory, which is our main tool, gives surprisingly good predictions of the statistical properties of the class of automata we consider. 18 refs., 6 figs.
A Cellular Automata Model for the Study of Landslides
NASA Astrophysics Data System (ADS)
Liucci, Luisa; Suteanu, Cristian; Melelli, Laura
2016-04-01
Power-law scaling has been observed in the frequency distribution of landslide sizes in many regions of the world, for landslides triggered by different factors, and in both multi-temporal and post-event datasets, thus indicating the universal character of this property of landslides and suggesting that the same mechanisms drive the dynamics of mass wasting processes. The reasons for the scaling behavior of landslide sizes are widely debated, since their understanding would improve our knowledge of the spatial and temporal evolution of this phenomenon. Self-Organized Critical (SOC) dynamics and the key role of topography have been suggested as possible explanations. The scaling exponent of the landslide size-frequency distribution defines the probability of landslide magnitudes and it thus represents an important parameter for hazard assessment. Therefore, another - still unanswered - important question concerns the factors on which its value depends. This paper investigates these issues using a Cellular Automata (CA) model. The CA uses a real topographic surface acquired from a Digital Elevation Model to represent the initial state of the system, where the states of cells are defined in terms of altitude. The stability criterion is based on the slope gradient. The system is driven to instability through a temporal decrease of the stability condition of cells, which may be thought of as representing the temporal weakening of soil caused by factors like rainfall. A transition rule defines the way in which instabilities lead to discharge from unstable cells to the neighboring cells, deciding upon the landslide direction and the quantity of mass involved. Both the direction and the transferred mass depend on the local topographic features. The scaling properties of the area-frequency distributions of the resulting landslide series are investigated for several rates of weakening and for different time windows, in order to explore the response of the system to model
Free Quantum Field Theory from Quantum Cellular Automata
NASA Astrophysics Data System (ADS)
Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo; Tosini, Alessandro
2015-10-01
After leading to a new axiomatic derivation of quantum theory (see D'Ariano et al. in Found Phys, 2015), the new informational paradigm is entering the domain of quantum field theory, suggesting a quantum automata framework that can be regarded as an extension of quantum field theory to including an hypothetical Planck scale, and with the usual quantum field theory recovered in the relativistic limit of small wave-vectors. Being derived from simple principles (linearity, unitarity, locality, homogeneity, isotropy, and minimality of dimension), the automata theory is quantum ab-initio, and does not assume Lorentz covariance and mechanical notions. Being discrete it can describe localized states and measurements (unmanageable by quantum field theory), solving all the issues plaguing field theory originated from the continuum. These features make the theory an ideal framework for quantum gravity, with relativistic covariance and space-time emergent solely from the interactions, and not assumed a priori. The paper presents a synthetic derivation of the automata theory, showing how the principles lead to a description in terms of a quantum automaton over a Cayley graph of a group. Restricting to Abelian groups we show how the automata recover the Weyl, Dirac and Maxwell dynamics in the relativistic limit. We conclude with some new routes about the more general scenario of non-Abelian Cayley graphs. The phenomenology arising from the automata theory in the ultra-relativistic domain and the analysis of corresponding distorted Lorentz covariance is reviewed in Bisio et al. (Found Phys 2015, in this same issue).
A comparative analysis of electronic and molecular quantum dot cellular automata
Umamahesvari, H. E-mail: ajithavijay1@gmail.com; Ajitha, D. E-mail: ajithavijay1@gmail.com
2015-06-24
This paper presents a comparative analysis of electronic quantum-dot cellular automata (EQCA) and Magnetic quantum dot Cellular Automata (MQCA). QCA is a computing paradigm that encodes and processes information by the position of individual electrons. To enhance the high dense and ultra-low power devices, various researches have been actively carried out to find an alternative way to continue and follow Moore’s law, so called “beyond CMOS technology”. There have been several proposals for physically implementing QCA, EQCA and MQCA are the two important QCAs reported so far. This paper provides a comparative study on these two QCAs.
A comparative analysis of electronic and molecular quantum dot cellular automata
NASA Astrophysics Data System (ADS)
Umamahesvari, H.; Ajitha, D.
2015-06-01
This paper presents a comparative analysis of electronic quantum-dot cellular automata (EQCA) and Magnetic quantum dot Cellular Automata (MQCA). QCA is a computing paradigm that encodes and processes information by the position of individual electrons. To enhance the high dense and ultra-low power devices, various researches have been actively carried out to find an alternative way to continue and follow Moore's law, so called "beyond CMOS technology". There have been several proposals for physically implementing QCA, EQCA and MQCA are the two important QCAs reported so far. This paper provides a comparative study on these two QCAs
Ecological risk assessment of genetically modified crops based on cellular automata modeling.
Yang, Jun; Wang, Zhi-Rui; Yang, De-Li; Yang, Qing; Yan, Jun; He, Ming-Feng
2009-01-01
The assessment of ecological risk in genetically modified (GM) biological systems is critically important for decision-making and public acceptance. Cellular automata (CA) provide a potential modeling and simulation framework for representing relationships and interspecies interactions both temporally and spatially. In this paper, a simple subsystem contains only four species: crop, target pest, non-target pest and enemy insect, and a three layer arrangement of LxL stochastic cellular automata with a periodic boundary were established. The simulation of this simplified system showed abundant and sufficient complexity in population assembly and densities, suggesting a prospective application in ecological risk assessment of GM crops. PMID:19477260
Cellular Automata Models Applied to the Study of Landslide Dynamics
NASA Astrophysics Data System (ADS)
Liucci, Luisa; Melelli, Laura; Suteanu, Cristian
2015-04-01
Landslides are caused by complex processes controlled by the interaction of numerous factors. Increasing efforts are being made to understand the spatial and temporal evolution of this phenomenon, and the use of remote sensing data is making significant contributions in improving forecast. This paper studies landslides seen as complex dynamic systems, in order to investigate their potential Self Organized Critical (SOC) behavior, and in particular, scale-invariant aspects of processes governing the spatial development of landslides and their temporal evolution, as well as the mechanisms involved in driving the system and keeping it in a critical state. For this purpose, we build Cellular Automata Models, which have been shown to be capable of reproducing the complexity of real world features using a small number of variables and simple rules, thus allowing for the reduction of the number of input parameters commonly used in the study of processes governing landslide evolution, such as those linked to the geomechanical properties of soils. This type of models has already been successfully applied in studying the dynamics of other natural hazards, such as earthquakes and forest fires. The basic structure of the model is composed of three modules: (i) An initialization module, which defines the topographic surface at time zero as a grid of square cells, each described by an altitude value; the surface is acquired from real Digital Elevation Models (DEMs). (ii) A transition function, which defines the rules used by the model to update the state of the system at each iteration. The rules use a stability criterion based on the slope angle and introduce a variable describing the weakening of the material over time, caused for example by rainfall. The weakening brings some sites of the system out of equilibrium thus causing the triggering of landslides, which propagate within the system through local interactions between neighboring cells. By using different rates of
The preservation of riparian zones and other environmentally sensitive areas has long been recognized as one of the most cost-effective methods of managing stormwater and providing a broad range of ecosystem services. In this research, a cellular automata (CA)—Markov chain model ...
Simulation of deformations in magnetic media by the movable cellular automata method
NASA Astrophysics Data System (ADS)
Usachev, Victor V.; Andriushchenko, Petr D.; Afremov, Leonid L.
2015-09-01
A deformable model of the magnetic medium is considered in the research paper. Simulating algorithms of the impact of the external magnetic field on the deformation of the magnetic medium have been developed on the basis of the movable cellular automata (MCA) method.
Simulating the immune response to the HIV-1 virus with cellular automata
NASA Astrophysics Data System (ADS)
Kougias, Ch. F.; Schulte, J.
1990-07-01
Two cellular automata models are presented which simulate the immune response to the HIV-1 virus at the early stage of the infection. The simple model A is based on the generalized nearest neighbor interaction, and the complex model B on the explicitly defined local interactions between the neighboring sites. These two models are discussed in the context of related work by Pandey.
Cellular automata with object-oriented features for parallel molecular network modeling.
Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan
2005-06-01
Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented. PMID:16117022
Order of the transition versus space dimension in a family of cellular automata
NASA Astrophysics Data System (ADS)
Bidaux, Roger; Boccara, Nini; Chaté, Hugues
1989-03-01
A mean-field theory of (probabilistic) cellular automata is developed and used to select a typical local rule whose mean-field analysis predicts first-order phase transitions. The corresponding automaton is then studied numerically on regular lattices for space dimensions d between 1 and 4. At odds with usual beliefs on two-state automata with one absorbing phase, first-order transitions are indeed exhibited as soon as d>1, with closer quantitative agreement with mean-field predictions for high space dimensions. For d=1, the transition is continuous, but with critical exponents different from those of directed percolation.
Simulation of the 1992 Tessina landslide by a cellular automata model and future hazard scenarios
NASA Astrophysics Data System (ADS)
Avolio, MV; Di Gregorio, Salvatore; Mantovani, Franco; Pasuto, Alessandro; Rongo, Rocco; Silvano, Sandro; Spataro, William
Cellular Automata are a powerful tool for modelling natural and artificial systems, which can be described in terms of local interactions of their constituent parts. Some types of landslides, such as debris/mud flows, match these requirements. The 1992 Tessina landslide has characteristics (slow mud flows) which make it appropriate for modelling by means of Cellular Automata, except for the initial phase of detachment, which is caused by a rotational movement that has no effect on the mud flow path. This paper presents the Cellular Automata approach for modelling slow mud/debris flows, the results of simulation of the 1992 Tessina landslide and future hazard scenarios based on the volumes of masses that could be mobilised in the future. They were obtained by adapting the Cellular Automata Model called SCIDDICA, which has been validated for very fast landslides. SCIDDICA was applied by modifying the general model to the peculiarities of the Tessina landslide. The simulations obtained by this initial model were satisfactory for forecasting the surface covered by mud. Calibration of the model, which was obtained from simulation of the 1992 event, was used for forecasting flow expansion during possible future reactivation. For this purpose two simulations concerning the collapse of about 1 million m 3 of material were tested. In one of these, the presence of a containment wall built in 1992 for the protection of the Tarcogna hamlet was inserted. The results obtained identified the conditions of high risk affecting the villages of Funes and Lamosano and show that this Cellular Automata approach can have a wide range of applications for different types of mud/debris flows.
Modeling Pseudorandom Sequence Generators using Cellular Automata: The Alternating Step Generator
NASA Astrophysics Data System (ADS)
Pazo-Robles, María Eugenia; Fúster-Sabater, Amparo
2007-12-01
Stream ciphers are pseudorandom bit generators whose output sequences are combined with the sensitive information by means of a mathematical function currently an addition module 2. The Alternating Step Generator is a pseudorandom sequence generator with good cryptographic properties and non-linear structure. In this work, we propose two different ways to model such a generator by using linear and discrete mathematical functions e.g. Cellular Automata. One of these ways deals with the realization of a linear model from a pair of basic automata provided by the Catell and Muzio algorithm. The other way is a new approach based on automata's addition consisting in the realization of a new automaton with non-primitive polynomial and short length. Both methods provide linear models able to generate the output sequence of the Alternating Step Generator.
Phase transitions in coupled map lattices and in associated probabilistic cellular automata.
Just, Wolfram
2006-10-01
Analytical tools are applied to investigate piecewise linear coupled map lattices in terms of probabilistic cellular automata. The so-called disorder condition of probabilistic cellular automata is closely related with attracting sets in coupled map lattices. The importance of this condition for the suppression of phase transitions is illustrated by spatially one-dimensional systems. Invariant densities and temporal correlations are calculated explicitly. Ising type phase transitions are found for one-dimensional coupled map lattices acting on repelling sets and for a spatially two-dimensional Miller-Huse-like system with stable long time dynamics. Critical exponents are calculated within a finite size scaling approach. The relevance of detailed balance of the resulting probabilistic cellular automaton for the critical behavior is pointed out. PMID:17155155
A heterogeneous lattice gas model for simulating pedestrian evacuation
NASA Astrophysics Data System (ADS)
Guo, Xiwei; Chen, Jianqiao; Zheng, Yaochen; Wei, Junhong
2012-02-01
Based on the cellular automata method (CA model) and the mobile lattice gas model (MLG model), we have developed a heterogeneous lattice gas model for simulating pedestrian evacuation processes in an emergency. A local population density concept is introduced first. The update rule in the new model depends on the local population density and the exit crowded degree factor. The drift D, which is one of the key parameters influencing the evacuation process, is allowed to change according to the local population density of the pedestrians. Interactions including attraction, repulsion, and friction between every two pedestrians and those between a pedestrian and the building wall are described by a nonlinear function of the corresponding distance, and the repulsion forces increase sharply as the distances get small. A critical force of injury is introduced into the model, and its effects on the evacuation process are investigated. The model proposed has heterogeneous features as compared to the MLG model or the basic CA model. Numerical examples show that the model proposed can capture the basic features of pedestrian evacuation, such as clogging and arching phenomena.
Quantum learning in a quantum lattice gas computer
NASA Astrophysics Data System (ADS)
Behrman, Elizabeth; Steck, James
2015-04-01
Quantum lattice gas is the logical generalization of quantum cellular automata. At low energy the dynamics are well described by the Gross-Pitaevskii equation in the mean field limit, which is an effective nonlinear interaction model of a Bose-Einstein condensate. In previous work, we have shown in simulation that both spatial and temporal models of quantum learning computers can be used to ``design'' non-trivial quantum algorithms. The advantages of quantum learning over the usual practice of using quantum gate building blocks are, first, the rapidity with which the problem can be solved, without having to decompose the problem; second, the fact that our technique can be used readily even when the problem, or the operator, is not well understood; and, third, that because the interactions are a natural part of the physical system, connectivity is automatic. The advantage to quantum learning obviously grows with the size and the complexity of the problem. We develop and present our learning algorithm as applied to the mean field lattice gas equation, and present a few preliminary results.
Quantum learning for a quantum lattice gas computer
NASA Astrophysics Data System (ADS)
Behrman, Elizabeth; Steck, James
2015-03-01
Quantum lattice gas is the logical generalization of quantum cellular automata. In low energy the dynamics are well described by the Gross-Pitaevskii equation in the mean field limit, which is an effective nonlinear interaction model of a Bose-Einstein condensate. In previous work, we have shown in simulation that both spatial and temporal models of quantum learning computers can be used to ``design'' non-trivial quantum algorithms. The advantages of quantum learning over the usual practice of using quantum gate building blocks are, first, the rapidity with which the problem can be solved, without having to decompose the problem; second, the fact that our technique can be used readily even when the problem, or the operator, is not well understood; and, third, that because the interactions are a natural part of the physical system, connectivity is automatic. The advantage to quantum learning obviously grows with the size and the complexity of the problem. We develop and present our learning algorithm as applied to the mean field lattice gas equation, and present a few preliminary results.
Lattice gas hydrodynamics: Theory and simulations. Final report, [February 1, 1989--March 31, 1991
Hasslacher, B.
1993-05-01
The first successful application of a microscopic analogy to create a skeleton cellular automaton and analyze it with statistical mechanical tools, was the work of Frisch, Hasslacher and Pomeau on the Navier-Stokes equation in two and three dimensions. This has become a very large research area with lattice gas models and methods being used for both fundamental investigations into the foundations of statistical mechanics and a large number of diverse applications. This present research was devoted to enlarging the fundamental scope of lattice gas models and proved successful. Since the beginning of this proposal, cellular automata have been constructed for statistical mechanical models, fluids, diffusion and shock systems in fundamental investigations. In applied areas, there are now excellent lattice gas models for complex flows through porous media, chemical reaction and combustion dynamics, multiphase flow systems, and fluid mixtures with natural boundaries. With extended cellular fluid models, one can do problems with arbitrary pairwise potentials. Recently, these have been applied to such problems as non-newtonian or polymeric liquids and a mixture of immiscible fluids passing through fractal or spongelike media in two and three dimensions. This proposal has contributed to and enlarged the scope of this work.
Stability of Cellular Automata Trajectories Revisited: Branching Walks and Lyapunov Profiles
NASA Astrophysics Data System (ADS)
Baetens, Jan M.; Gravner, Janko
2016-05-01
We study non-equilibrium defect accumulation dynamics on a cellular automaton trajectory: a branching walk process in which a defect creates a successor on any neighborhood site whose update it affects. On an infinite lattice, defects accumulate at different exponential rates in different directions, giving rise to the Lyapunov profile. This profile quantifies instability of a cellular automaton evolution and is connected to the theory of large deviations. We rigorously and empirically study Lyapunov profiles generated from random initial states. We also introduce explicit and computationally feasible variational methods to compute the Lyapunov profiles for periodic configurations, thus developing an analog of Floquet theory for cellular automata.
Chaos of elementary cellular automata rule 42 of Wolfram's class II.
Chen, Fang-Yue; Jin, Wei-Feng; Chen, Guan-Rong; Chen, Fang-Fang; Chen, Lin
2009-03-01
In this paper, the dynamics of elementary cellular automata rule 42 is investigated in the bi-infinite symbolic sequence space. Rule 42, a member of Wolfram's class II which was said to be simply as periodic before, actually defines a chaotic global attractor; that is, rule 42 is topologically mixing on its global attractor and possesses the positive topological entropy. Therefore, rule 42 is chaotic in the sense of both Li-Yorke and Devaney. Meanwhile, the characteristic function and the basin tree diagram of rule 42 are explored for some finite length of binary strings, which reveal its Bernoulli characteristics. The method presented in this work is also applicable to studying the dynamics of other rules, especially the 112 Bernoulli-shift rules of the elementary cellular automata. PMID:19335004
Topology regulates pattern formation capacity of binary cellular automata on graphs
NASA Astrophysics Data System (ADS)
Marr, Carsten; Hütt, Marc-Thorsten
2005-08-01
We study the effect of topology variation on the dynamic behavior of a system with local update rules. We implement one-dimensional binary cellular automata on graphs with various topologies by formulating two sets of degree-dependent rules, each containing a single parameter. We observe that changes in graph topology induce transitions between different dynamic domains (Wolfram classes) without a formal change in the update rule. Along with topological variations, we study the pattern formation capacities of regular, random, small-world and scale-free graphs. Pattern formation capacity is quantified in terms of two entropy measures, which for standard cellular automata allow a qualitative distinction between the four Wolfram classes. A mean-field model explains the dynamic behavior of random graphs. Implications for our understanding of information transport through complex, network-based systems are discussed.
Chaos of elementary cellular automata rule 42 of Wolfram's class II
NASA Astrophysics Data System (ADS)
Chen, Fang-Yue; Jin, Wei-Feng; Chen, Guan-Rong; Chen, Fang-Fang; Chen, Lin
2009-03-01
In this paper, the dynamics of elementary cellular automata rule 42 is investigated in the bi-infinite symbolic sequence space. Rule 42, a member of Wolfram's class II which was said to be simply as periodic before, actually defines a chaotic global attractor; that is, rule 42 is topologically mixing on its global attractor and possesses the positive topological entropy. Therefore, rule 42 is chaotic in the sense of both Li-Yorke and Devaney. Meanwhile, the characteristic function and the basin tree diagram of rule 42 are explored for some finite length of binary strings, which reveal its Bernoulli characteristics. The method presented in this work is also applicable to studying the dynamics of other rules, especially the 112 Bernoulli-shift rules of the elementary cellular automata.
A cellular automata model of traffic flow with variable probability of randomization
NASA Astrophysics Data System (ADS)
Zheng, Wei-Fan; Zhang, Ji-Ye
2015-05-01
Research on the stochastic behavior of traffic flow is important to understand the intrinsic evolution rules of a traffic system. By introducing an interactional potential of vehicles into the randomization step, an improved cellular automata traffic flow model with variable probability of randomization is proposed in this paper. In the proposed model, the driver is affected by the interactional potential of vehicles before him, and his decision-making process is related to the interactional potential. Compared with the traditional cellular automata model, the modeling is more suitable for the driver’s random decision-making process based on the vehicle and traffic situations in front of him in actual traffic. From the improved model, the fundamental diagram (flow-density relationship) is obtained, and the detailed high-density traffic phenomenon is reproduced through numerical simulation. Project supported by the National Natural Science Foundation of China (Grant Nos. 11172247, 61273021, 61373009, and 61100118).
Nishawala, Vinesh V.; Ostoja-Starzewski, Martin; Leamy, Michael J.; Demmie, Paul N.
2015-09-10
Peridynamics is a non-local continuum mechanics formulation that can handle spatial discontinuities as the governing equations are integro-differential equations which do not involve gradients such as strains and deformation rates. This paper employs bond-based peridynamics. Cellular Automata is a local computational method which, in its rectangular variant on interior domains, is mathematically equivalent to the central difference finite difference method. However, cellular automata does not require the derivation of the governing partial differential equations and provides for common boundary conditions based on physical reasoning. Both methodologies are used to solve a half-space subjected to a normal load, known as Lamb’s Problem. The results are compared with theoretical solution from classical elasticity and experimental results. Furthermore, this paper is used to validate our implementation of these methods.
An authenticated image encryption scheme based on chaotic maps and memory cellular automata
NASA Astrophysics Data System (ADS)
Bakhshandeh, Atieh; Eslami, Ziba
2013-06-01
This paper introduces a new image encryption scheme based on chaotic maps, cellular automata and permutation-diffusion architecture. In the permutation phase, a piecewise linear chaotic map is utilized to confuse the plain-image and in the diffusion phase, we employ the Logistic map as well as a reversible memory cellular automata to obtain an efficient and secure cryptosystem. The proposed method admits advantages such as highly secure diffusion mechanism, computational efficiency and ease of implementation. A novel property of the proposed scheme is its authentication ability which can detect whether the image is tampered during the transmission or not. This is particularly important in applications where image data or part of it contains highly sensitive information. Results of various analyses manifest high security of this new method and its capability for practical image encryption.
NASA Astrophysics Data System (ADS)
Li, Qi-Lang; Wong, S. C.; Min, Jie; Tian, Shuo; Wang, Bing-Hong
2016-08-01
This study examines the cellular automata traffic flow model, which considers the heterogeneity of vehicle acceleration and the delay probability of vehicles. Computer simulations are used to identify three typical phases in the model: free-flow, synchronized flow, and wide moving traffic jam. In the synchronized flow region of the fundamental diagram, the low and high velocity vehicles compete with each other and play an important role in the evolution of the system. The analysis shows that there are two types of bistable phases. However, in the original Nagel and Schreckenberg cellular automata traffic model, there are only two kinds of traffic conditions, namely, free-flow and traffic jams. The synchronized flow phase and bistable phase have not been found.
From QCA (Quantum Cellular Automata) to Organocatalytic Reactions with Stabilized Carbenium Ions.
Gualandi, Andrea; Mengozzi, Luca; Manoni, Elisabetta; Giorgio Cozzi, Pier
2016-06-01
What do quantum cellular automata (QCA), "on water" reactions, and SN 1-type organocatalytic transformations have in common? The link between these distant arguments is the practical access to useful intermediates and key products through the use of stabilized carbenium ions. Over 10 years, starting with a carbenium ion bearing a ferrocenyl group, to the 1,3-benzodithiolylium carbenium ion, our group has exploited the use of these intermediates in useful and practical synthetic transformations. In particular, we have applied the use of carbenium ions to stereoselective organocatalytic alkylation reactions, showing a possible solution for the "holy grail of organocatalysis". Examples of the use of these quite stabilized intermediates are now also considered in organometallic chemistry. On the other hand, the stable carbenium ions are also applied to tailored molecules adapted to quantum cellular automata, a new possible paradigm for computation. Carbenium ions are not a problem, they can be a/the solution! PMID:27062088
Coulomb coupling and the role of symmetries in quantum-dot arrays for cellular automata
Ramirez, F.; Cota, E.; Ulloa, S. E.
2000-07-15
Using a group-theoretical analysis of the symmetries of a quantum dot array, we investigate the role of defects on the energetics of the system and the resulting charge configurations (or polarization of the cell). We find that for the typical four- or five-element geometries proposed, even small asymmetries introduced by defects in the system, or variations in the local electrostatic environment, can give rise to large effects on the polarization of the ground state and the corresponding low-energy excitations. These shifts are likely to produce important effects in the operation of the cellular automata proposed using these quantum dots. In particular, we find that the sensitivity to polarization changes induced by a driver cell decreases dramatically, and the polarization values are no longer fully defined. These effects would both force the use of stronger driving fields, and may also complicate the dynamical behavior of the cellular automata. (c) 2000 The American Physical Society.
Spatial organization and evolution period of the epidemic model using cellular automata.
Liu, Quan-Xing; Jin, Zhen; Liu, Mao-Xing
2006-09-01
We investigate epidemic models with spatial structure based on the cellular automata method. The construction of the cellular automata is from the study by Weimar and Boon about the reaction-diffusion equations [Phys. Rev. E 49, 1749 (1994)]. Our results show that the spatial epidemic models exhibit the spontaneous formation of irregular spiral waves at large scales within the domain of chaos. Moreover, the irregular spiral waves grow stably. The system also shows a spatial period-2 structure at one dimension outside the domain of chaos. It is interesting that the spatial period-2 structure will break and transform into a spatial synchronous configuration in the domain of chaos. Our results confirm that populations embed and disperse more stably in space than they do in nonspatial counterparts. PMID:17025597
Nishawala, Vinesh V.; Ostoja-Starzewski, Martin; Leamy, Michael J.; Demmie, Paul N.
2015-09-10
Peridynamics is a non-local continuum mechanics formulation that can handle spatial discontinuities as the governing equations are integro-differential equations which do not involve gradients such as strains and deformation rates. This paper employs bond-based peridynamics. Cellular Automata is a local computational method which, in its rectangular variant on interior domains, is mathematically equivalent to the central difference finite difference method. However, cellular automata does not require the derivation of the governing partial differential equations and provides for common boundary conditions based on physical reasoning. Both methodologies are used to solve a half-space subjected to a normal load, known as Lamb’smore » Problem. The results are compared with theoretical solution from classical elasticity and experimental results. Furthermore, this paper is used to validate our implementation of these methods.« less
Efficient process development for bulk silicon etching using cellular automata simulation techniques
NASA Astrophysics Data System (ADS)
Marchetti, James; He, Yie; Than, Olaf; Akkaraju, Sandeep
1998-09-01
This paper describes cellular automata simulation techniques used to predict the anisotropic etching of single-crystal silicon. In particular, this paper will focus on the application of wet etching of silicon wafers using typical anisotropic etchants such as KOH, TMAH, and EDP. Achieving a desired final 3D geometry of etch silicon wafers often is difficult without requiring a number of fabrication design iterations. The result is wasted time and resources. AnisE, a tool to simulate anisotropic etching of silicon wafers using cellular automata simulation, was developed in order to efficiently prototype and manufacture MEMS devices. AnisE has been shown to effectively decrease device development time and costs by up to 50% and 60%, respectively.
An improved multi-value cellular automata model for heterogeneous bicycle traffic flow
NASA Astrophysics Data System (ADS)
Jin, Sheng; Qu, Xiaobo; Xu, Cheng; Ma, Dongfang; Wang, Dianhai
2015-10-01
This letter develops an improved multi-value cellular automata model for heterogeneous bicycle traffic flow taking the higher maximum speed of electric bicycles into consideration. The update rules of both regular and electric bicycles are improved, with maximum speeds of two and three cells per second respectively. Numerical simulation results for deterministic and stochastic cases are obtained. The fundamental diagrams and multiple states effects under different model parameters are analyzed and discussed. Field observations were made to calibrate the slowdown probabilities. The results imply that the improved extended Burgers cellular automata (IEBCA) model is more consistent with the field observations than previous models and greatly enhances the realism of the bicycle traffic model.
Supervised nuclear track detection of CR-39 detectors by cellular automata
NASA Astrophysics Data System (ADS)
Chahkandi Nejad, Hadi; Khayat, Omid; Mohammadi, Kheirollah; Tavakoli, Saeed
2014-05-01
In this paper, cellular automata are used to detect the nuclear tracks in the track images captured from the surface of CR-39 detectors. Parameters of the automaton as the states, neighborhood, rules and quality parameters are defined optimally for the track image data set under analysis. The presented method is a supervised computational algorithm which comprises a rule definition phase as the learning procedure. Parameter optimization is also performed to adapt the algorithm to the data set used.
a Predator-Prey Model Based on the Fully Parallel Cellular Automata
NASA Astrophysics Data System (ADS)
He, Mingfeng; Ruan, Hongbo; Yu, Changliang
We presented a predator-prey lattice model containing moveable wolves and sheep, which are characterized by Penna double bit strings. Sexual reproduction and child-care strategies are considered. To implement this model in an efficient way, we build a fully parallel Cellular Automata based on a new definition of the neighborhood. We show the roles played by the initial densities of the populations, the mutation rate and the linear size of the lattice in the evolution of this model.
An image encryption algorithm based on 3D cellular automata and chaotic maps
NASA Astrophysics Data System (ADS)
Del Rey, A. Martín; Sánchez, G. Rodríguez
2015-05-01
A novel encryption algorithm to cipher digital images is presented in this work. The digital image is rendering into a three-dimensional (3D) lattice and the protocol consists of two phases: the confusion phase where 24 chaotic Cat maps are applied and the diffusion phase where a 3D cellular automata is evolved. The encryption method is shown to be secure against the most important cryptanalytic attacks.
Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model
NASA Astrophysics Data System (ADS)
Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran
2014-09-01
Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.
A model for electrical tree growth in solid insulating materials using cellular automata
Danikas, M.G.; Karafyllidis, I.; Thanailakis, A.; Bruning, A.M.
1996-12-31
Models proposed to explain the breakdown mechanisms of the solid insulating materials are based, among others, on electromagnetic theory, avalanche theory and fractals. In this paper the breakdown of insulating materials is simulated using von Neumann`s Cellular Automata (CAs). An algorithm for solid dielectric breakdown simulation based on CAs is presented with a point/plane electrode arrangement. The algorithm is also used to simulate breakdown in a solid dielectric having a spherical void.
Incremental Learning of Cellular Automata for Parallel Recognition of Formal Languages
NASA Astrophysics Data System (ADS)
Nakamura, Katsuhiko; Imada, Keita
Parallel language recognition by cellular automata (CAs) is currently an important subject in computation theory. This paper describes incremental learning of one-dimensional, bounded, one-way, cellular automata (OCAs) that recognize formal languages from positive and negative sample strings. The objectives of this work are to develop automatic synthesis of parallel systems and to contribute to the theory of real-time recognition by cellular automata. We implemented methods to learn the rules of OCAs in the Occam system, which is based on grammatical inference of context-free grammars (CFGs) implemented in Synapse. An important feature of Occam is incremental learning by a rule generation mechanism called bridging and the search for rule sets. The bridging looks for and fills gaps in incomplete space-time transition diagrams for positive samples. Another feature of our approach is that the system synthesizes minimal or semi-minimal rule sets of CAs. This paper reports experimental results on learning several OCAs for fundamental formal languages including sets of balanced parentheses and palindromes as well as the set {a n b n c n | n ≥ 1}.
Synchronization, TIGoRS, and Information Flow in Complex Systems: Dispositional Cellular Automata.
Sulis, William H
2016-04-01
Synchronization has a long history in physics where it refers to the phase matching of two identical oscillators. This notion has been extensively studied in physics as well as in biology, where it has been applied to such widely varying phenomena as the flashing of fireflies and firing of neurons in the brain. Human behavior, however, may be recurrent but it is not oscillatory even though many physiological systems do exhibit oscillatory tendencies. Moreover, much of human behaviour is collaborative and cooperative, where the individual behaviours may be distinct yet contemporaneous (if not simultaneous) and taken collectively express some functionality. In the context of behaviour, the important aspect is the repeated co-occurrence in time of behaviours that facilitate the propagation of information or of functionality, regardless of whether or not these behaviours are similar or identical. An example of this weaker notion of synchronization is transient induced global response synchronization (TIGoRS). Previous work has shown that TIGoRS is a ubiquitous phenomenon among complex systems, enabling them to stably parse environmental transients into salient units to which they stably respond. This leads to the notion of Sulis machines, which emergently generate a primitive linguistic structure through their dynamics. This article reviews the notion of TIGoRS and its expression in several complex systems models including tempered neural networks, driven cellular automata and cocktail party automata. The emergent linguistics of Sulis machines are discussed. A new class of complex systems model, the dispositional cellular automaton is introduced. A new metric for TIGoRS, the excess synchronization, is introduced and applied to the study of TIGoRS in dispositional cellular automata. It is shown that these automata exhibit a nonlinear synchronization response to certain perturbing transients. PMID:27033136
Lattice Gas Model with Nonlocal Interactions
NASA Astrophysics Data System (ADS)
Das, Shankar P.
We analyze the nature of the hydrodynamic modes in a Lattice Gas Automata (LGA) model defined on a hexagonal lattice and having nonlocal interactions of attractive and repulsive type simultaneously. The model is similar in spirit to the liquid gas model of Appert and Zaleski [Phys. Rev. Lett. 64, 1 (1990)]. The phase diagram for the model is computed using the kinetic pressure. The dynamics is studied with a mean field type approach in the Boltzmann approximation ignoring effects of correlated collisions. We compute the transport coefficients and the speed of sound propagation. The presence of attractive interactions show increase in the transport coefficients at intermediate densities.
NASA Astrophysics Data System (ADS)
Javaheri Javid, Mohammad Ali; Blackwell, Tim; Zimmer, Robert; Majid al-Rifaie, Mohammad
2016-04-01
Shannon entropy fails to discriminate structurally different patterns in two-dimensional images. We have adapted information gain measure and Kolmogorov complexity to overcome the shortcomings of entropy as a measure of image structure. The measures are customised to robustly quantify the complexity of images resulting from multi-state cellular automata (CA). Experiments with a two-dimensional multi-state cellular automaton demonstrate that these measures are able to predict some of the structural characteristics, symmetry and orientation of CA generated patterns.
Noise-enhanced performance of ratchet cellular automata.
Babic, Dusan; Bechinger, Clemens
2005-04-15
We present the first experimental realization of a ratchet cellular automaton (RCA) which has recently been suggested as an alternative approach for performing logical operations with interacting (quasi)particles. Our study was performed with interacting colloidal particles which serve as a model system for other dissipative systems, i.e., magnetic vortices on a superconductor or ions in dissipative optical arrays. We demonstrate that noise can enhance the efficiency of information transport in RCA and consequently enables their optimal operation at finite temperatures. PMID:15904122
A cellular automata model of Ebola virus dynamics
NASA Astrophysics Data System (ADS)
Burkhead, Emily; Hawkins, Jane
2015-11-01
We construct a stochastic cellular automaton (SCA) model for the spread of the Ebola virus (EBOV). We make substantial modifications to an existing SCA model used for HIV, introduced by others and studied by the authors. We give a rigorous analysis of the similarities between models due to the spread of virus and the typical immune response to it, and the differences which reflect the drastically different timing of the course of EBOV. We demonstrate output from the model and compare it with clinical data.
Classifying elementary cellular automata using compressibility, diversity and sensitivity measures
NASA Astrophysics Data System (ADS)
Ninagawa, Shigeru; Adamatzky, Andrew
2014-10-01
An elementary cellular automaton (ECA) is a one-dimensional, synchronous, binary automaton, where each cell update depends on its own state and states of its two closest neighbors. We attempt to uncover correlations between the following measures of ECA behavior: compressibility, sensitivity and diversity. The compressibility of ECA configurations is calculated using the Lempel-Ziv (LZ) compression algorithm LZ78. The sensitivity of ECA rules to initial conditions and perturbations is evaluated using Derrida coefficients. The generative morphological diversity shows how many different neighborhood states are produced from a single nonquiescent cell. We found no significant correlation between sensitivity and compressibility. There is a substantial correlation between generative diversity and compressibility. Using sensitivity, compressibility and diversity, we uncover and characterize novel groupings of rules.
A new small-world network created by Cellular Automata
NASA Astrophysics Data System (ADS)
Ruan, Yuhong; Li, Anwei
2016-08-01
In this paper, we generate small-world networks by the Cellular Automaton based on starting with one-dimensional regular networks. Besides the common properties of small-world networks with small average shortest path length and large clustering coefficient, the small-world networks generated in this way have other properties: (i) The edges which are cut in the regular network can be controlled that whether the edges are reconnected or not, and (ii) the number of the edges of the small-world network model equals the number of the edges of the original regular network. In other words, the average degree of the small-world network model equals to the average degree of the original regular network.
Cellular automata model based on GIS and urban sprawl dynamics simulation
NASA Astrophysics Data System (ADS)
Mu, Fengyun; Zhang, Zengxiang
2005-10-01
The simulation of land use change process needs the support of Geographical Information System (GIS) and other relative technologies. While the present commercial GIS lack capabilities of distribution, prediction, and simulation of spatial-temporal data. Cellular automata (CA) provide dynamically modeling "from bottom-to-top" framework and posses the capability of modeling spatial-temporal evolvement process of a complicated geographical system, which is composed of a fourfold: cells, states, neighbors and rules. The simplicity and flexibility make CA have the ability to simulate a variety of behaviors of complex systems. One of the most potentially useful applications of cellular automata from the point of view of spatial planning is their use in simulations of urban sprawl at local and regional level. The paper firstly introduces the principles and characters of the cellular automata, and then discusses three methods of the integration of CA and GIS. The paper analyses from a practical point of view the factors that effect urban activities in the science of spatial decision-making. The status of using CA to dynamic simulates of urban expansion at home and abroad is analyzed. Finally, the problems and tendencies that exist in the application of CA model are detailed discussed, such as the quality of the data that the CA needs, the self-organization of the CA roots in the mutual function among the elements of the system, the partition of the space scale, the time calibration of the CA and the integration of the CA with other modular such as artificial nerve net modular and population modular etc.
Calculation of impulse responses with a cellular automata algorithm
NASA Astrophysics Data System (ADS)
Barjau, Ana
2001-05-01
The air columns in musical instruments usually have a predominant dimension and thus are very often modeled as 1D systems where uniparametric waves propagate. Different algorithms can be found in the literature to simulate this propagation. The more widely used are finite difference schemes and delay lines. A finite difference scheme (FD) is a numerical integration of a differential formulation (the wave equation), while delay lines (DL) use analytical exact solutions of the wave equation over finite lengths. A new and different approach is that of a cellular automaton (CA) scheme. The underlying philosophy is opposite those of FD and DL, as the starting point is not the wave equation. In a CA approach, the phenomenon to be studied is reduced to a few simple physical laws that are applied to a set of cells representing the physical system (in the present case, the propagation medium). In this paper, a CA will be proposed to obtain the impulse response of different bore geometries. The results will be compared to those obtained with other algorithms.
Fluctuation in option pricing using cellular automata based market models
NASA Astrophysics Data System (ADS)
Gao, Yuying; Beni, Gerardo
2005-05-01
A new agent-based Cellular Automaton (CA) computational algorithm for option pricing is proposed. CAs have been extensively used in modeling complex dynamical systems but not in modeling option prices. Compared with traditional tools, which rely on guessing volatilities to calculate option prices, the CA model is directly addressing market mechanisms and simulates price fluctuation from aggregation of actions made by interacting individual market makers in a large population. This paper explores whether CA models can provide reasonable good answers to pricing European options. The Black-Scholes model and the Binomial Tree model are used for comparison. Comparison reveals that CA models perform reasonably well in pricing options, reproducing overall characteristics of random walk based model, while at the same time providing plausible results for the 'fat-tail' phenomenon observed in many markets. We also show that the binomial tree model can be obtained from a CA rule. Thus, CA models are suitable tools to generalize the standard theories of option pricing.
An evaluation of cellular automata applied to ganglia dissolution
NASA Astrophysics Data System (ADS)
Johns, M. L.; Gladden, L. F.
2002-12-01
The ability of a three-dimensional (3-D) cellular automaton (CA) approach to describe or mimic the dissolution of entrapped octanol ganglia, trapped in a porous media, into a mobile aqueous phase has been directly assessed using detailed 3-D visualizations of the dissolution process, as provided by magnetic resonance imaging (MRI). In the 3-D CA, both time and space are made discrete with the state of each geometric site being updated after each time increment according to the state of all neighboring sites. Good agreement is produced by a direct 3-D comparison of the CA results with the corresponding images of the dissolving ganglia. These experimental images are also supplemented by 3-D velocity maps of the mobile aqueous phase produced using either MRI or by a lattice-Boltzmann simulation. The velocity maps are used to validate the assumption that a consideration of the local velocity field is essential for an accurate description of the ganglia dissolution process. Based on this analysis, an appropriate length scale is proposed for the region, required to be considered in the respective vicinity of each ganglion, when describing their dissolution using a CA approach.
Symbolic Computation Using Cellular Automata-Based Hyperdimensional Computing.
Yilmaz, Ozgur
2015-12-01
This letter introduces a novel framework of reservoir computing that is capable of both connectionist machine intelligence and symbolic computation. A cellular automaton is used as the reservoir of dynamical systems. Input is randomly projected onto the initial conditions of automaton cells, and nonlinear computation is performed on the input via application of a rule in the automaton for a period of time. The evolution of the automaton creates a space-time volume of the automaton state space, and it is used as the reservoir. The proposed framework is shown to be capable of long-term memory, and it requires orders of magnitude less computation compared to echo state networks. As the focus of the letter, we suggest that binary reservoir feature vectors can be combined using Boolean operations as in hyperdimensional computing, paving a direct way for concept building and symbolic processing. To demonstrate the capability of the proposed system, we make analogies directly on image data by asking, What is the automobile of air? PMID:26496041
The two populations’ cellular automata model with predation based on the Penna model
NASA Astrophysics Data System (ADS)
He, Mingfeng; Lin, Jing; Jiang, Heng; Liu, Xin
2002-09-01
In Penna's single-species asexual bit-string model of biological ageing, the Verhulst factor has too strong a restraining effect on the development of the population. Danuta Makowiec gave an improved model based on the lattice, where the restraining factor of the four neighbours take the place of the Verhulst factor. Here, we discuss the two populations’ Penna model with predation on the planar lattice of two dimensions. A cellular automata model containing movable wolves and sheep has been built. The results show that both the quantity of the wolves and the sheep fluctuate in accordance with the law that one quantity increases while the other one decreases.
NASA Astrophysics Data System (ADS)
Enayatifar, Rasul; Sadaei, Hossein Javedani; Abdullah, Abdul Hanan; Lee, Malrey; Isnin, Ismail Fauzi
2015-08-01
Currently, there are many studies have conducted on developing security of the digital image in order to protect such data while they are sending on the internet. This work aims to propose a new approach based on a hybrid model of the Tinkerbell chaotic map, deoxyribonucleic acid (DNA) and cellular automata (CA). DNA rules, DNA sequence XOR operator and CA rules are used simultaneously to encrypt the plain-image pixels. To determine rule number in DNA sequence and also CA, a 2-dimension Tinkerbell chaotic map is employed. Experimental results and computer simulations, both confirm that the proposed scheme not only demonstrates outstanding encryption, but also resists various typical attacks.
The Design of Fault Tolerant Quantum Dot Cellular Automata Based Logic
NASA Technical Reports Server (NTRS)
Armstrong, C. Duane; Humphreys, William M.; Fijany, Amir
2002-01-01
As transistor geometries are reduced, quantum effects begin to dominate device performance. At some point, transistors cease to have the properties that make them useful computational components. New computing elements must be developed in order to keep pace with Moore s Law. Quantum dot cellular automata (QCA) represent an alternative paradigm to transistor-based logic. QCA architectures that are robust to manufacturing tolerances and defects must be developed. We are developing software that allows the exploration of fault tolerant QCA gate architectures by automating the specification, simulation, analysis and documentation processes.
The Development of Design Tools for Fault Tolerant Quantum Dot Cellular Automata Based Logic
NASA Technical Reports Server (NTRS)
Armstrong, Curtis D.; Humphreys, William M.
2003-01-01
We are developing software to explore the fault tolerance of quantum dot cellular automata gate architectures in the presence of manufacturing variations and device defects. The Topology Optimization Methodology using Applied Statistics (TOMAS) framework extends the capabilities of the A Quantum Interconnected Network Array Simulator (AQUINAS) by adding front-end and back-end software and creating an environment that integrates all of these components. The front-end tools establish all simulation parameters, configure the simulation system, automate the Monte Carlo generation of simulation files, and execute the simulation of these files. The back-end tools perform automated data parsing, statistical analysis and report generation.
The Effect of Mixed Vehicles on Traffic Flow in Two Lane Cellular Automata Model
NASA Astrophysics Data System (ADS)
Jia, Bin; Jiang, Rui; Gao, Zi-You; Zhao, Xiao-Mei
In real traffic, the traffic system is usually composed of different types of vehicles, which have different parameters. How these parameters, especially the lengths of the vehicles, influence the traffic behaviors and transportation capability has seldom been investigated. In this paper, we study the mixed traffic system using the cellular automata traffic flow model. The simulation results show that when the road occupancy rate is large, increasing the fraction of long vehicles can apparently, improve the transportation capability. The influence of slow vehicles fraction on the average velocity of vehicles has been discussed, and it is found that the influences are very different when the difference of vehicle length is considered or not.
Simple and Flexible Self-Reproducing Structures in Asynchronous Cellular Automata and Their Dynamics
NASA Astrophysics Data System (ADS)
Huang, Xin; Lee, Jia; Yang, Rui-Long; Zhu, Qing-Sheng
2013-03-01
Self-reproduction on asynchronous cellular automata (ACAs) has attracted wide attention due to the evident artifacts induced by synchronous updating. Asynchronous updating, which allows cells to undergo transitions independently at random times, might be more compatible with the natural processes occurring at micro-scale, but the dark side of the coin is the increment in the complexity of an ACA in order to accomplish stable self-reproduction. This paper proposes a novel model of self-timed cellular automata (STCAs), a special type of ACAs, where unsheathed loops are able to duplicate themselves reliably in parallel. The removal of sheath cannot only allow various loops with more flexible and compact structures to replicate themselves, but also reduce the number of cell states of the STCA as compared to the previous model adopting sheathed loops [Y. Takada, T. Isokawa, F. Peper and N. Matsui, Physica D227, 26 (2007)]. The lack of sheath, on the other hand, often tends to cause much more complicated interactions among loops, when all of them struggle independently to stretch out their constructing arms at the same time. In particular, such intense collisions may even cause the emergence of a mess of twisted constructing arms in the cellular space. By using a simple and natural method, our self-reproducing loops (SRLs) are able to retract their arms successively, thereby disentangling from the mess successfully.
Nakajima, Kohei; Haruna, Taichi
2011-09-01
In this paper, we propose a new class of cellular automata based on the modification of its state space. It is introduced to model a computation which is exposed to an environment. We formalized the computation as extension and projection processes of its state space and resulting misidentifications of the state. This is motivated to embed the role of an environment into the system itself, which naturally induces self-organized internal perturbations rather than the usual external perturbations. Implementing this structure into the elementary cellular automata, we characterized its effect by means of input entropy and power spectral analysis. As a result, the cellular automata with this structure showed robust class IV behavior and a 1/f power spectrum in a wide range of rule space comparative to the notion of the edge of chaos. PMID:21600265
Computing cellular automata spectra under fixed boundary conditions via limit graphs
NASA Astrophysics Data System (ADS)
Ruivo, Eurico L. P.; de Oliveira, Pedro P. B.
2016-01-01
Cellular automata are fully discrete complex systems with parallel and homogeneous behavior studied both from the theoretical and modeling viewpoints. The limit behaviors of such systems are of particular interest, as they give insight into their emerging properties. One possible approach to investigate such limit behaviors is the analysis of the growth of graphs describing the finite time behavior of a rule in order to infer its limit behavior. Another possibility is to study the Fourier spectrum describing the average limit configurations obtained by a rule. While the former approach gives the characterization of the limit configurations of a rule, the latter yields a qualitative and quantitative characterisation of how often particular blocks of states are present in these limit configurations. Since both approaches are closely related, it is tempting to use one to obtain information about the other. Here, limit graphs are automatically adjusted by configurations directly generated by their respective rules, and use the graphs to compute the spectra of their rules. We rely on a set of elementary cellular automata rules, on lattices with fixed boundary condition, and show that our approach is a more reliable alternative to a previously described method from the literature.
Stair evacuation simulation based on cellular automata considering evacuees’ walk preferences
NASA Astrophysics Data System (ADS)
Ding, Ning; Zhang, Hui; Chen, Tao; Peter, B. Luh
2015-06-01
As a physical model, the cellular automata (CA) model is widely used in many areas, such as stair evacuation. However, existing CA models do not consider evacuees’ walk preferences nor psychological status, and the structure of the basic model is unapplicable for the stair structure. This paper is to improve the stair evacuation simulation by addressing these issues, and a new cellular automata model is established. Several evacuees’ walk preference and how evacuee’s psychology influences their behaviors are introduced into this model. Evacuees’ speeds will be influenced by these features. To validate this simulation, two fire drills held in two high-rise buildings are video-recorded. It is found that the simulation results are similar to the fire drill results. The structure of this model is simple, and it is easy to further develop and utilize in different buildings with various kinds of occupants. Project supported by the National Basic Research Program of China (Grant No. 2012CB719705) and the National Natural Science Foundation of China (Grant Nos. 91224008, 91024032, and 71373139).
Calibrating Cellular Automata of Land Use/cover Change Models Using a Genetic Algorithm
NASA Astrophysics Data System (ADS)
Mas, J. F.; Soares-Filho, B.; Rodrigues, H.
2015-08-01
Spatially explicit land use / land cover (LUCC) models aim at simulating the patterns of change on the landscape. In order to simulate landscape structure, the simulation procedures of most computational LUCC models use a cellular automata to replicate the land use / cover patches. Generally, model evaluation is based on assessing the location of the simulated changes in comparison to the true locations but landscapes metrics can also be used to assess landscape structure. As model complexity increases, the need to improve calibration and assessment techniques also increases. In this study, we applied a genetic algorithm tool to optimize cellular automata's parameters to simulate deforestation in a region of the Brazilian Amazon. We found that the genetic algorithm was able to calibrate the model to simulate more realistic landscape in term of connectivity. Results show also that more realistic simulated landscapes are often obtained at the expense of the location coincidence. However, when considering processes such as the fragmentation impacts on biodiversity, the simulation of more realistic landscape structure should be preferred to spatial coincidence performance.
NASA Astrophysics Data System (ADS)
Xue, Yuan; Qian, Yong-Sheng; Guang, Xiao-Ping; Zeng, Jun-Wei; Jia, Zhi-Long; Wang, Xin
2013-05-01
With the application of the dynamic control system, Cellular Automata model has become a valued tool for the simulation of human behavior and traffic flow. As an integrated kind of railway signal-control pattern, the four-aspect color light automatic block signaling has accounted for 50% in the signal-control system in China. Thus, it is extremely important to calculate correctly its carrying capacity under the automatic block signaling. Based on this fact the paper proposes a new kind of "cellular automata model" for the four-aspect color light automatic block signaling under different speed states. It also presents rational rules for the express trains with higher speed overtaking trains with lower speed in a same or adjacent section and the departing rules in some intermediate stations. In it, the state of mixed-speed trains running in the section composed of many stations is simulated with CA model, and the train-running diagram is acquired accordingly. After analyzing the relevant simulation results, the needed data are achieved herewith for the variation of section carrying capacity, the average train delay, the train speed with the change of mixed proportion, as well as the distance between the adjacent stations.
Fault-tolerance and thermal characteristics of quantum-dot cellular automata devices
NASA Astrophysics Data System (ADS)
Anduwan, G. A.; Padgett, B. D.; Kuntzman, M.; Hendrichsen, M. K.; Sturzu, I.; Khatun, M.; Tougaw, P. D.
2010-06-01
We present fault tolerant properties of various quantum-dot cellular automata (QCA) devices. Effects of temperatures and dot displacements on the operation of the fundamental devices such as a binary wire, logical gates, a crossover, and an exclusive OR (XOR) have been investigated. A Hubbard-type Hamiltonian and intercellular Hartree approximation have been used for modeling, and a uniform random distribution has been implemented for the defect simulations. The breakdown characteristics of all the devices are almost the same except the crossover. Results show that the success of any device is significantly dependent on both the fabrication defects and temperatures. We have observed unique characteristic features of the crossover. It is highly sensitive to defects of any magnitude. Results show that the presence of a crossover in a XOR design is a major factor for its failure. The effects of temperature and defects in the crossover device are pronounced and have significant impact on larger and complicated QCA devices.
Design of Efficient Full Adder in Quantum-Dot Cellular Automata
Sen, Bibhash; Sikdar, Biplab K.
2013-01-01
Further downscaling of CMOS technology becomes challenging as it faces limitation of feature size reduction. Quantum-dot cellular automata (QCA), a potential alternative to CMOS, promises efficient digital design at nanoscale. Investigations on the reduction of QCA primitives (majority gates and inverters) for various adders are limited, and very few designs exist for reference. As a result, design of adders under QCA framework is gaining its importance in recent research. This work targets developing multi-layered full adder architecture in QCA framework based on five-input majority gate proposed here. A minimum clock zone (2 clock) with high compaction (0.01 μm2) for a full adder around QCA is achieved. Further, the usefulness of such design is established with the synthesis of high-level logic. Experimental results illustrate the significant improvements in design level in terms of circuit area, cell count, and clock compared to that of conventional design approaches. PMID:23844385
Modelling the role of nucleation on recrystallization kinetics: A cellular automata approach
NASA Astrophysics Data System (ADS)
Tripathy, Haraprasanna; Rai, Arun Kumar; Hajra, Raj Narayan; Raju, Subramanian; Saibaba, Saroja
2016-05-01
In present study, a two dimensional cellular automata (CA) simulation has been carried out to study the effect of nucleation mode on the kinetics of recrystallization and microstructure evolution in an austenitic stainless steel. Two different nucleation modes i.e. site saturation and continuous nucleation with interface control growth mechanism has been considered in this modified CA algorithm. The observed Avrami exponent for both nucleation modes shows a better agreement with the theoretical predicted values. The site saturated nucleation mode shows a nearly consistent value of Avrami exponent, whereas in the case of continuous nucleation the exponent shows a little variation during transformation. The simulations in the present work can be applied for the optimization of microstructure and properties in austenitic steels.
Temperature Effects on Olive Fruit Fly Infestation in the FlySim Cellular Automata Model
NASA Astrophysics Data System (ADS)
Bruno, Vincenzo; Baldacchini, Valerio; di Gregorio, Salvatore
FlySim is a Cellular Automata model developed for simulating infestation of olive fruit flies (Bactrocera Oleae) on olive (Olea europaea) groves. The flies move into the groves looking for mature olives where eggs are spawn. This serious agricultural problem is mainly tackled by using chemical agents at the first signs of the infestation, but organic productions with no or few chemicals are strongly requested by the market. Oil made with infested olives is poor in quality, nor olives are suitable for selling in stores. The FlySim model simulates the diffusion of flies looking for mature olives and the growing of flies due to atmospheric conditions. Foreseeing an infestation is the best way to prevent it and to reduce the need of chemicals in agriculture. In this work we investigated the effects of temperature on olive fruit flies and resulting infestation during late spring and summer.
Ca-Pri a Cellular Automata Phenomenological Research Investigation: Simulation Results
NASA Astrophysics Data System (ADS)
Iannone, G.; Troisi, A.
2013-05-01
Following the introduction of a phenomenological cellular automata (CA) model capable to reproduce city growth and urban sprawl, we develop a toy model simulation considering a realistic framework. The main characteristic of our approach is an evolution algorithm based on inhabitants preferences. The control of grown cells is obtained by means of suitable functions which depend on the initial condition of the simulation. New born urban settlements are achieved by means of a logistic evolution of the urban pattern while urban sprawl is controlled by means of the population evolution function. In order to compare model results with a realistic urban framework we have considered, as the area of study, the island of Capri (Italy) in the Mediterranean Sea. Two different phases of the urban evolution on the island have been taken into account: a new born initial growth as induced by geographic suitability and the simulation of urban spread after 1943 induced by the population evolution after this date.
Hologram authentication based on a secure watermarking algorithm using cellular automata.
Hwang, Wen-Jyi; Chan, Hao-Tang; Cheng, Chau-Jern
2014-09-20
A secure watermarking algorithm for hologram authentication is presented in this paper. The algorithm exploits the noise-like feature of holograms to randomly embed a watermark in the domain of the discrete cosine transform with marginal degradation in transparency. The pseudo random number (PRN) generators based on a cellular automata algorithm with asymmetrical and nonlocal connections are used for the random hiding. Each client has its own unique PRN generators for enhancing the watermark security. In the proposed algorithm, watermarks are also randomly generated to eliminate the requirements of prestoring watermarks in the clients and servers. An authentication scheme is then proposed for the algorithm with random watermark generation and hiding. PMID:25322138
NASA Astrophysics Data System (ADS)
Adabi, Sepideh; Adabi, Sahar; Rezaee, Ali
According to the traditional definition of Wireless Sensor Networks (WSNs), static sensors have limited the feasibility of WSNs in some kind of approaches, so the mobility was introduced in WSN. Mobile nodes in a WSN come equipped with battery and from the point of deployment, this battery reserve becomes a valuable resource since it cannot be replenished. Hence, maximizing the network lifetime by minimizing the energy is an important challenge in Mobile WSN. Energy conservation can be accomplished by different approaches. In this paper, we presented an energy conservation solution based on Cellular Automata. The main objective of this solution is based on dynamically adjusting the transmission range and switching between operational states of the sensor nodes.
NASA Astrophysics Data System (ADS)
Kohring, G. A.; Stauffer, D.
Geometric parallelization was tested on the Intel Hypercube with 32 MIMD processors of 1860 type, each with 16 Mbytes of distributed memory. We applied it to Ising models in two and three dimensions as well as to neural networks and two-dimensional hydrodynamic cellular automata. For system sizes suited to this machine, up to 60960*60960 and 1410*1410*1408 Ising spins, we found nearly hundred percent parallel efficiency in spite of the needed inter-processor communications. For small systems, the observed deviations from full efficiency were compared with the scaling concepts of Heermann and Burkitt and of Jakobs and Gerling. For Ising models, we determined the Glauber kinetic exponent z≃2.18 in two dimensions and confirmed the stretched exponential relaxation of the magnetization towards the spontaneous magnetization below Tc. For three dimensions we found z≃2.09 and simple exponential relaxation.
NASA Astrophysics Data System (ADS)
Ren, Gang; Jiang, Hang; Chen, Jingxu; Huang, Zhengfeng; Lu, Lili
2016-06-01
This paper presents a cellular automata (CA) model to elucidate the straight-through movements of the heterogeneous bicycle traffic at signalized intersection. The CA model, via simulation, particularly exposits the dispersion phenomenon existing in the straight-through bicycle traffic. The nonlane-based cycling behavior and diverse bicycle properties are also incorporated in the CA model. A series of simulations are conducted to reveal the travel process, bicycles interaction and influence of the dispersion phenomenon. The simulation results show that the dispersion phenomenon significantly results in more bicycles interactions in terms of spilling maneuvers and overtaking maneuvers during the straight-through movements. Meanwhile, the dispersion phenomenon could contribute to the efficiency of the bicycle traffic, and straight-through bicycles need less time to depart the intersection under the circumstance of dispersion phenomenon. The simulation results are able to provide specific guideline for reasonably utilizing the dispersion phenomenon to improve the operational efficiency of straight-through bicycle traffic.
Emergence of density dynamics by surface interpolation in elementary cellular automata
NASA Astrophysics Data System (ADS)
Seck-Tuoh-Mora, Juan Carlos; Medina-Marin, Joselito; Martínez, Genaro J.; Hernández-Romero, Norberto
2014-04-01
A classic problem in elementary cellular automata (ECAs) is the specification of numerical tools to represent and study their dynamical behaviour. Mean field theory and basins of attraction have been commonly used; however, although the first case gives the long term estimation of density, frequently it does not show an adequate approximation for the step-by-step temporal behaviour; mainly for non-trivial behaviour. In the second case, basins of attraction display a complete representation of the evolution of an ECA, but they are limited up to configurations of 32 cells; and for the same ECA, one can obtain tens of basins to analyse. This paper is devoted to represent the dynamics of density in ECAs for hundreds of cells using only two surfaces calculated by the nearest-neighbour interpolation. A diversity of surfaces emerges in this analysis. Consequently, we propose a surface and histogram based classification for periodic, chaotic and complex ECA.
Conflict game in evacuation process: A study combining Cellular Automata model
NASA Astrophysics Data System (ADS)
Zheng, Xiaoping; Cheng, Yuan
2011-03-01
The game-theoretic approach is an essential tool in the research of conflicts of human behaviors. The aim of this study is to research crowd dynamic conflicts during evacuation processes. By combining a conflict game with a Cellular Automata model, the following factors such as rationality, herding effect and conflict cost are taken into the research on frequency of each strategy of evacuees, and evacuation time. Results from Monte Carlo simulations show that (i) in an emergency condition, rationality leads to “vying” behaviors and inhibited “polite” behavior; (ii) high herding causes a crowd of high rationality (especially in normal circumstances) to become more “vying” in behavior; (iii) the high-rationality crowd is shown to spend more evacuation time than a low-rationality crowd in emergency situations. This study provides a new perspective to understand conflicts in evacuation processes as well as the rationality of evacuees.
Occupants’ behavior of going with the crowd based on cellular automata occupant evacuation model
NASA Astrophysics Data System (ADS)
Zhao, Daoliang; Yang, Lizhong; Li, Jian
2008-06-01
Occupant behavior which is very complex affects evacuation efficiency and route choice a lot. The psychology and behavior of going with the crowd is very common in daily life and also in occupant evacuation. In this paper, a two-dimensional Cellular Automata model is applied to simulate the process of evacuation considering the psychology of going with the crowd with different room structure or occupant density. The psychology of going with the crowd (the abbreviation is GWC) is classified into directional GWC ( DGWC) and spatial GWC ( SGWC). The influence of two such kinds of psychology on occupant evacuation is discussed in order to provide some useful guidance on the emergency management of evacuation.
Scale-invariant cellular automata and self-similar Petri nets
NASA Astrophysics Data System (ADS)
Schaller, M.; Svozil, K.
2009-05-01
Two novel computing models based on an infinite tessellation of space-time are introduced. They consist of recursively coupled primitive building blocks. The first model is a scale-invariant generalization of cellular automata, whereas the second one utilizes self-similar Petri nets. Both models are capable of hypercomputations and can, for instance, “solve” the halting problem for Turing machines. These two models are closely related, as they exhibit a step-by-step equivalence for finite computations. On the other hand, they differ greatly for computations that involve an infinite number of building blocks: the first one shows indeterministic behavior, whereas the second one halts. Both models are capable of challenging our understanding of computability, causality, and space-time.
Modeling of the competition life cycle using the software complex of cellular automata PyCAlab
NASA Astrophysics Data System (ADS)
Berg, D. B.; Beklemishev, K. A.; Medvedev, A. N.; Medvedeva, M. A.
2015-11-01
The aim of the work is to develop a numerical model of the life cycle of competition on the basis of software complex cellular automata PyCAlab. The model is based on the general patterns of growth of various systems in resource-limited settings. At examples it is shown that the period of transition from an unlimited growth of the market agents to the stage of competitive growth takes quite a long time and may be characterized as monotonic. During this period two main strategies of competitive selection coexist: 1) capture of maximum market space with any reasonable costs; 2) saving by reducing costs. The obtained results allow concluding that the competitive strategies of companies must combine two mentioned types of behavior, and this issue needs to be given adequate attention in the academic literature on management. The created numerical model may be used for market research when developing of the strategies for promotion of new goods and services.
Non-probabilistic cellular automata-enhanced stereo vision simultaneous localization and mapping
NASA Astrophysics Data System (ADS)
Nalpantidis, Lazaros; Sirakoulis, Georgios Ch; Gasteratos, Antonios
2011-11-01
In this paper, a visual non-probabilistic simultaneous localization and mapping (SLAM) algorithm suitable for area measurement applications is proposed. The algorithm uses stereo vision images as its only input and processes them calculating the depth of the scenery, detecting occupied areas and progressively building a map of the environment. The stereo vision-based SLAM algorithm embodies a stereo correspondence algorithm that is tolerant to illumination differentiations, the robust scale- and rotation-invariant feature detection and matching speeded-up robust features method, a computationally effective v-disparity image calculation scheme, a novel map-merging module, as well as a sophisticated cellular automata-based enhancement stage. A moving robot equipped with a stereo camera has been used to gather image sequences and the system has autonomously mapped and measured two different indoor areas.
Khan, Muhammad Sadiq Ali; Yousuf, Sidrah
2016-03-01
Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each electrical activity during cardiac cycle should be monitor non-invasively for the assessment of "Action Potential" (regular) and "Arrhythmia" (irregular) rhythms. Many heart diseases can easily be examined through Automata model like Cellular Automata concepts. This paper deals with the different states of cardiac rhythms using cellular automata with the comparison of neural network also provides fast and highly effective stimulation for the contraction of cardiac muscles on the Atria in the result of genesis of electrical spark or wave. The specific formulated model named as "States of automaton Proposed Model for CEA (Cardiac Electrical Activity)" by using Cellular Automata Methodology is commonly shows the three states of cardiac tissues conduction phenomena (i) Resting (Relax and Excitable state), (ii) ARP (Excited but Absolutely refractory Phase i.e. Excited but not able to excite neighboring cells) (iii) RRP (Excited but Relatively Refractory Phase i.e. Excited and able to excite neighboring cells). The result indicates most efficient modeling with few burden of computation and it is Action Potential during the pumping of blood in cardiac cycle. PMID:27087101
Takesue, Shinji )
1989-08-01
This is the first part of a series devoted to the study of thermodynamic behavior of large dynamical systems with the use of a family of full-discrete and conservative models named elementary reversible cellular automata (ERCAs). In this paper, basic properties such as conservation laws and phase space structure are investigated in preparation for the later studies. ERCAs are a family of one-dimensional reversible cellular automata having two Boolean variables on each site. Reflection and Boolean conjugation symmetries divide them into 88 equivalence classes. For each rule, additive conserved quantities written in a certain form are regarded as a kind of energy, if they exist. By the aid of the discreteness of the variables, every ERCA satisfies the Liouville theorem or the preservation of phase space volume. Thus, if an energy exists in the above sense, statistical mechanics of the model can formally be constructed. If a locally defined quantity is conserved, however, it prevents the realization of statistical mechanics. The existence of such a quantity is examined for each class and a number of rules which have at least one energy but no local conservation laws are selected as hopeful candidates for the realization of thermodynamic behavior. In addition, the phase space structure of ERCAs is analyzed by enumerating cycles exactly in the phase space for systems of comparatively small sizes. As a result, it is revealed that a finite ERCA is not ergodic, that is, a large number of orbits coexist on an energy surface. It is argued that this fact does not necessarily mean the failure of thermodynamic behavior on the basis of an analogy with the ergodic nature of infinite systems.
Raines, G.L.; Zientek, M.L.; Causey, J.D.; Boleneus, D.E.
2002-01-01
For public land management in Idaho and western Montana, the U.S. Forest Service (USFS) has requested that the U.S. Geological Survey (USGS) predict where mineral-related activity will occur in the next decade. Cellular automata provide an approach to simulation of this human activity. Cellular automata (CA) are defined by an array of cells, which evolve by a simple transition rule, the automaton. Based on exploration trends, we assume that future exploration will focus in areas of past exploration. Spatial-temporal information about mineral-related activity, that is permits issued by USFS and Bureau of Land Management (BLM) in the last decade, and spatial information about undiscovered resources, provide a basis to calibrate a CA. The CA implemented is a modified annealed voting rule that simulates mineral-related activity with spatial and temporal resolution of 1 mi2 and 1 year based on activity from 1989 to 1998. For this CA, the state of the economy and exploration technology is assumed constant for the next decade. The calibrated CA reproduces the 1989-1998-permit activity with an agreement of 94%, which increases to 98% within one year. Analysis of the confusion matrix and kappa correlation statistics indicates that the CA underestimates high activity and overestimates low activity. Spatially, the major differences between the actual and calculated activity are that the calculated activity occurs in a slightly larger number of small patches and is slightly more uneven than the actual activity. Using the calibrated CA in a Monte Carlo simulation projecting from 1998 to 2010, an estimate of the probability of mineral activity shows high levels of activity in Boise, Caribou, Elmore, Lincoln, and western Valley counties in Idaho and Beaverhead, Madison, and Stillwater counties in Montana, and generally low activity elsewhere. ?? 2002 International Association for Mathematical Geology.
NASA Astrophysics Data System (ADS)
Afshar, M. H.; Rohani, M.
2012-01-01
In this article, cellular automata based hybrid methods are proposed for the optimal design of sewer networks and their performance is compared with some of the common heuristic search methods. The problem of optimal design of sewer networks is first decomposed into two sub-optimization problems which are solved iteratively in a two stage manner. In the first stage, the pipe diameters of the network are assumed fixed and the nodal cover depths of the network are determined by solving a nonlinear sub-optimization problem. A cellular automata (CA) method is used for the solution of the optimization problem with the network nodes considered as the cells and their cover depths as the cell states. In the second stage, the nodal cover depths calculated from the first stage are fixed and the pipe diameters are calculated by solving a second nonlinear sub-optimization problem. Once again a CA method is used to solve the optimization problem of the second stage with the pipes considered as the CA cells and their corresponding diameters as the cell states. Two different updating rules are derived and used for the CA of the second stage depending on the treatment of the pipe diameters. In the continuous approach, the pipe diameters are considered as continuous variables and the corresponding updating rule is derived mathematically from the original objective function of the problem. In the discrete approach, however, an adhoc updating rule is derived and used taking into account the discrete nature of the pipe diameters. The proposed methods are used to optimally solve two sewer network problems and the results are presented and compared with those obtained by other methods. The results show that the proposed CA based hybrid methods are more efficient and effective than the most powerful search methods considered in this work.
A Cellular Automata Based Model for Simulating Surface Hydrological Processes in Catchments
NASA Astrophysics Data System (ADS)
Shao, Qi; Baumgartl, Thomas; Huang, Longbin; Weatherley, Dion
2014-05-01
The Runoff Model Based on Cellular Automata (RunCA) has been developed to simulate the surface hydrological processes at the catchment scale by integrating basic cellular automata (CA) rules with fundamental measureable hydraulic properties. In this model, a two-dimensional lattice composed of a series of rectangular cells was employed to cover the study area. Runoff production within each cell was simulated by determining its water depth based on the rainfall, interception, infiltration and the balance between inflows and outflows. Particularly different infiltration equations were incorporated to make the model applicable for both single rainfall event (short term simulation) and multiple rainfall events (long term simulation). The distribution of water flow among cells was determined by applying CA transition rules based on the improved minimization-of-difference algorithm and the calculated spatially and temporally varied flow velocities according to the Manning's equation. RunCA was tested and validated at two catchments (Pine Glen Basin and Snow Shoe Basin, USA) with data taken from literature. The predicted hydrographs agreed well with the measured results. Simulated flow maps also demonstrated the model capability in capturing both the spatial and temporal variations in the runoff process. Model sensitivity analysis results showed that the simulated hydrographs were mostly influenced by the input parameters that represent the final steady infiltration rate, as well as the model settings of time step and cell size. Compared to some conventional distributed hydrologic models that calculate the runoff routing process by solving complex continuity equations, this model integrates a novel method and is expected to be more computationally efficient as it is based on simple CA transition rules when determining the flow distribution.
RunCA: A cellular automata model for simulating surface runoff at different scales
NASA Astrophysics Data System (ADS)
Shao, Qi; Weatherley, Dion; Huang, Longbin; Baumgartl, Thomas
2015-10-01
The Runoff Model Based on Cellular Automata (RunCA) has been developed to simulate surface runoff at different scales by integrating basic cellular automata (CA) rules with fundamental measureable hydraulic properties. In this model, a two-dimensional lattice composed of a series of rectangular cells was employed to cover the study area. Runoff production within each cell was simulated by determining the cell state (height) that consists of both cell elevation and water depth. The distribution of water flow among cells was determined by applying CA transition rules based on the minimization-of-difference algorithm and the calculated spatially varied flow velocities. RunCA was verified and validated by three steps. Good agreement with the analytical solution was achieved under simplified conditions in the first step. Then, results from runoff experiments on small laboratory plots (2 m × 1 m) showed that the model was able to well predict the hydrographs, with the mean Nash-Sutcliffe efficiency greater than 0.90. RunCA was also applied to a large scale site (Pine Glen Basin, USA) with data taken from literature. The predicted hydrograph agreed well with the measured results. Simulated flow maps in this basin also demonstrated the model capability in capturing both the spatial and temporal variations in the runoff process. Model sensitivity analysis results showed that the calculated total runoff and total infiltration were most sensitive to the input parameters representing the final steady infiltration rate at both scales. The Manning's roughness coefficient and the setting of cell size did not affect the results much at the small plot scale, but had large influences at the large basin scale.
Modelling approaches for coastal simulation based on cellular automata: the need and potential.
Dearing, J A; Richmond, N; Plater, A J; Wolf, J; Prandle, D; Coulthard, T J
2006-04-15
The paper summarizes the theoretical and practical needs for cellular automata (CA)-type models in coastal simulation, and describes early steps in the development of a CA-based model for estuarine sedimentation. It describes the key approaches and formulae used for tidal, wave and sediment processes in a prototype integrated cellular model for coastal simulation designed to simulate estuary sedimentary responses during the tidal cycle in the short-term and climate driven changes in sea-level in the long-term. Results of simple model testing for both one-dimensional and two-dimensional models, and a preliminary parameterization for the Blackwater Estuary, UK, are shown. These reveal a good degree of success in using a CA-type model for water and sediment transport as a function of water level and wave height, but tidal current vectors are not effectively simulated in the approach used. The research confirms that a CA-type model for the estuarine sediment system is feasible, with a real prospect for coupling to existing catchment and nearshore beach/cliff models to produce integrated coastal simulators of sediment response to climate, sea-level change and human actions. PMID:16537155
Phenomenological study of irregular cellular automata based on Lyapunov exponents and Jacobians.
Baetens, Jan M; De Baets, Bernard
2010-09-01
Originally, cellular automata (CA) have been defined upon regular tessellations of the n-dimensional Euclidean space, while CA on irregular tessellations have received only little attention from the scientific community, notwithstanding serious shortcomings are associated with the former manner of subdividing Rn. In this paper we present a profound phenomenological study of two-state, two-dimensional irregular CA from a dynamical systems viewpoint. We opted to exploit properly defined quantitative measures instead of resorting to qualitative methods for discriminating between behavioral classes. As such, we employ Lyapunov exponents, measuring the divergence rate of close trajectories in phase space, and Jacobians, formulated using Boolean derivatives and expressing the sensitivity of a cellular automaton to its inputs. Both are stated for two-state CA on irregular tessellations, enabling us to characterize these discrete dynamical systems, and advancing us to propose a classification scheme for this CA family. In addition, a relationship between these quantitative measures is established in extension of the insights already developed for the classical CA paradigm. Finally, we discuss the repercussions on the CA dynamics that arise when the geometric variability of the spatial entities is taken into account during the CA simulation. PMID:20887052
NASA Astrophysics Data System (ADS)
González, Ramón E. R.; de Figueirêdo, Pedro Hugo; Coutinho, Sérgio
2013-10-01
We study a cellular automata model to test the timing of antiretroviral therapy strategies for the dynamics of infection with human immunodeficiency virus (HIV). We focus on the role of virus diffusion when its population is included in previous cellular automata model that describes the dynamics of the lymphocytes cells population during infection. This inclusion allows us to consider the spread of infection by the virus-cell interaction, beyond that which occurs by cell-cell contagion. The results show an acceleration of the infectious process in the absence of treatment, but show better efficiency in reducing the risk of the onset of AIDS when combined antiretroviral therapies are used even with drugs of low effectiveness. Comparison of results with clinical data supports the conclusions of this study.
NASA Astrophysics Data System (ADS)
Acedo, L.; Villanueva-Oller, J.; Moraño, J. A.; Villanueva, R.-J.
2013-01-01
The Berkeley Open Infrastructure for Network Computing (BOINC) has become the standard open source solution for grid computing in the Internet. Volunteers use their computers to complete an small part of the task assigned by a dedicated server. We have developed a BOINC project called Neurona@Home whose objective is to simulate a cellular automata random network with, at least, one million neurons. We consider a cellular automata version of the integrate-and-fire model in which excitatory and inhibitory nodes can activate or deactivate neighbor nodes according to a set of probabilistic rules. Our aim is to determine the phase diagram of the model and its behaviour and to compare it with the electroencephalographic signals measured in real brains.
NASA Astrophysics Data System (ADS)
Wang, Xianmin; Niu, Ruiqing; Wu, Ke
2011-07-01
Remote sensing provides a new idea and an advanced method for lithology identification, but lithology identification by remote sensing is quite difficult because 1. the disciplines of lithology identification in a concrete region are often quite different from the experts' experience; 2. in the regions with flourishing vegetation, lithology information is poor, so it is very difficult to identify the lithologies by remote sensing images. At present, the studies on lithology identification by remote sensing are primarily conducted on the regions with low vegetation coverage and high rock bareness. And there is no mature method of lithology identification in the regions with flourishing vegetation. Traditional methods lacking in the mining and extraction of the various complicated lithology information from a remote sensing image, often need much manual intervention and possess poor intelligence and accuracy. An intelligent method proposed in this paper for lithology identification based on support vector machine (SVM) and adaptive cellular automata (ACA) is expected to solve the above problems. The method adopted Landsat-7 ETM+ images and 1:50000 geological map as the data origins. It first derived the lithology identification factors on three aspects: 1. spectra, 2. texture and 3. vegetation cover. Second, it plied the remote sensing images with the geological map and established the SVM to obtain the transition rules according to the factor values of the samples. Finally, it established an ACA model to intelligently identify the lithologies according to the transition and neighborhood rules. In this paper an ACA model is proposed and compared with the traditional one. Results of 2 real-world examples show that: 1. The SVM-ACA method obtains a good result of lithology identification in the regions with flourishing vegetation; 2. it possesses high accuracies of lithology identification (with the overall accuracies of 92.29% and 85.54%, respectively, in the two
Moustafa, Ahmed; Younes, Ahmed; Hassan, Yasser F.
2015-01-01
Quantum-dot cellular automata (QCA) are nanoscale digital logic constructs that use electrons in arrays of quantum dots to carry out binary operations. In this paper, a basic building block for QCA will be proposed. The proposed basic building block can be customized to implement classical gates, such as XOR and XNOR gates, and reversible gates, such as CNOT and Toffoli gates, with less cell count and/or better latency than other proposed designs. PMID:26345412
Moustafa, Ahmed; Younes, Ahmed; Hassan, Yasser F
2015-01-01
Quantum-dot cellular automata (QCA) are nanoscale digital logic constructs that use electrons in arrays of quantum dots to carry out binary operations. In this paper, a basic building block for QCA will be proposed. The proposed basic building block can be customized to implement classical gates, such as XOR and XNOR gates, and reversible gates, such as CNOT and Toffoli gates, with less cell count and/or better latency than other proposed designs. PMID:26345412
Dynamics of the HIV infection under antiretroviral therapy: A cellular automata approach
NASA Astrophysics Data System (ADS)
González, Ramón E. R.; Coutinho, Sérgio; Zorzenon dos Santos, Rita Maria; de Figueirêdo, Pedro Hugo
2013-10-01
The dynamics of human immunodeficiency virus infection under antiretroviral therapy is investigated using a cellular automata model where the effectiveness of each drug is self-adjusted by the concentration of CD4+ T infected cells present at each time step. The effectiveness of the drugs and the infected cell concentration at the beginning of treatment are the control parameters of the cell population’s dynamics during therapy. The model allows describing processes of mono and combined therapies. The dynamics that emerges from this model when considering combined antiretroviral therapies reproduces with fair qualitative agreement the phases and different time scales of the process. As observed in clinical data, the results reproduce the significant decrease in the population of infected cells and a concomitant increase of the population of healthy cells in a short timescale (weeks) after the initiation of treatment. Over long time scales, early treatment with potent drugs may lead to undetectable levels of infection. For late treatment or treatments starting with a low density of CD4+ T healthy cells it was observed that the treatment may lead to a steady state in which the T cell counts are above the threshold associated with the onset of AIDS. The results obtained are validated through comparison to available clinical trial data.
Takada, Ryu; Munetaka, Daigo; Kobayashi, Shoji; Suemitsu, Yoshikazu; Nara, Shigetoshi
2007-09-01
Chaotic dynamics in a recurrent neural network model and in two-dimensional cellular automata, where both have finite but large degrees of freedom, are investigated from the viewpoint of harnessing chaos and are applied to motion control to indicate that both have potential capabilities for complex function control by simple rule(s). An important point is that chaotic dynamics generated in these two systems give us autonomous complex pattern dynamics itinerating through intermediate state points between embedded patterns (attractors) in high-dimensional state space. An application of these chaotic dynamics to complex controlling is proposed based on an idea that with the use of simple adaptive switching between a weakly chaotic regime and a strongly chaotic regime, complex problems can be solved. As an actual example, a two-dimensional maze, where it should be noted that the spatial structure of the maze is one of typical ill-posed problems, is solved with the use of chaos in both systems. Our computer simulations show that the success rate over 300 trials is much better, at least, than that of a random number generator. Our functional simulations indicate that both systems are almost equivalent from the viewpoint of functional aspects based on our idea, harnessing of chaos. PMID:19003512
Cellular Automata Modeling of Decarburization of Metal Droplets in Basic Oxygen Steelmaking
NASA Astrophysics Data System (ADS)
Ankit; Kundu, T. K.
2016-02-01
In steelmaking, a supersonic jet is blown over the bath to refine the hot metal to produce steel. The refining process primarily consists of removal of impurities from the hot metal to a permissible level. The impact of oxygen jet on the surface of the hot metal bath results in ejection of droplets, which mix with slag and form emulsion. The formed emulsion plays an important role in refining reactions kinetics and understanding of this process is required todevelopimproved process control model for the steel industry. In this paper, cellular automata technique has been explored to simulate decarburization in emulsion caused by interfacial reactions between the metal droplets and slag. In the course of the work, a framework has also been developed to quantify the contribution of carbon monoxide, generated by decarburization, in bloating of metal droplets and formation of halo around the droplets. The model has incorporated diffusion and decarburization reaction based on probabilities to study the evolution of the system. Simulations with varying parameters have been performed and decarburization trends obtained are comparable with the experimentally determined data reported in literatures.
Electrical substation service-area estimation using Cellular Automata: An initial report
Fenwick, J.W.; Dowell, L.J.
1998-07-01
The service areas for electric power substations can be estimated using a Cellular Automata (CA) model. The CA model is a discrete, iterative process whereby substations acquire service area by claiming neighboring cells. The service area expands from a substation until a neighboring substation service area is met or the substation`s total capacity or other constraints are reached. The CA-model output is dependent on the rule set that defines cell interactions. The rule set is based on a hierarchy of quantitative metrics that represent real-world factors such as land use and population density. Together, the metrics determine the rate of cell acquisition and the upper bound for service area size. Assessing the CA-model accuracy requires comparisons to actual service areas. These actual service areas can be extracted from distribution maps. Quantitative assessment of the CA-model accuracy can be accomplished by a number of methods. Some are as simple as finding the percentage of cells predicted correctly, while others assess a penalty based on the distance from an incorrectly predicted cell to its correct service area. This is an initial report of a work in progress.
Accurate reliability analysis method for quantum-dot cellular automata circuits
NASA Astrophysics Data System (ADS)
Cui, Huanqing; Cai, Li; Wang, Sen; Liu, Xiaoqiang; Yang, Xiaokuo
2015-10-01
Probabilistic transfer matrix (PTM) is a widely used model in the reliability research of circuits. However, PTM model cannot reflect the impact of input signals on reliability, so it does not completely conform to the mechanism of the novel field-coupled nanoelectronic device which is called quantum-dot cellular automata (QCA). It is difficult to get accurate results when PTM model is used to analyze the reliability of QCA circuits. To solve this problem, we present the fault tree models of QCA fundamental devices according to different input signals. After that, the binary decision diagram (BDD) is used to quantitatively investigate the reliability of two QCA XOR gates depending on the presented models. By employing the fault tree models, the impact of input signals on reliability can be identified clearly and the crucial components of a circuit can be found out precisely based on the importance values (IVs) of components. So this method is contributive to the construction of reliable QCA circuits.
Quasi-classical modeling of molecular quantum-dot cellular automata multidriver gates
2012-01-01
Molecular quantum-dot cellular automata (mQCA) has received considerable attention in nanoscience. Unlike the current-based molecular switches, where the digital data is represented by the on/off states of the switches, in mQCA devices, binary information is encoded in charge configuration within molecular redox centers. The mQCA paradigm allows high device density and ultra-low power consumption. Digital mQCA gates are the building blocks of circuits in this paradigm. Design and analysis of these gates require quantum chemical calculations, which are demanding in computer time and memory. Therefore, developing simple models to probe mQCA gates is of paramount importance. We derive a semi-classical model to study the steady-state output polarization of mQCA multidriver gates, directly from the two-state approximation in electron transfer theory. The accuracy and validity of this model are analyzed using full quantum chemistry calculations. A complete set of logic gates, including inverters and minority voters, are implemented to provide an appropriate test bench in the two-dot mQCA regime. We also briefly discuss how the QCADesigner tool could find its application in simulation of mQCA devices. PMID:22647345
NASA Astrophysics Data System (ADS)
Ding, H. L.; He, Y. Z.; Liu, L. F.; Ding, W. J.
2006-08-01
The microstructure and morphology evolution of grain growth were studied by 3D simulation using the cellular automata (CA) model based on the lowest-energy principle. In the present CA model, the transition of cells during the grain growth has a typical physical meaning due to the application of the lowest-energy principle. The results show that the kinetics of grain growth follows Burke equation with the growth exponent as 2. The average number of grain faces is 13.6 and the highest frequency of grain faces is 10 faces. The grain size distribution follows Weibull function. The relationship between the number of faces of a grain and the average number of faces of its adjacent grains follows the Aboav-Weaire law. There is a correlation between the topologies of the simulated 2D and 3D grain growth. The average number of sides per face for all grains is 5.65 and the average number of sides per face is about equal to 6 when the grain aces is larger than 35.
A cellular automata model for avascular solid tumor growth under the effect of therapy
NASA Astrophysics Data System (ADS)
Reis, E. A.; Santos, L. B. L.; Pinho, S. T. R.
2009-04-01
Tumor growth has long been a target of investigation within the context of mathematical and computer modeling. The objective of this study is to propose and analyze a two-dimensional stochastic cellular automata model to describe avascular solid tumor growth, taking into account both the competition between cancer cells and normal cells for nutrients and/or space and a time-dependent proliferation of cancer cells. Gompertzian growth, characteristic of some tumors, is described and some of the features of the time-spatial pattern of solid tumors, such as compact morphology with irregular borders, are captured. The parameter space is studied in order to analyze the occurrence of necrosis and the response to therapy. Our findings suggest that transitions exist between necrotic and non-necrotic phases (no-therapy cases), and between the states of cure and non-cure (therapy cases). To analyze cure, the control and order parameters are, respectively, the highest probability of cancer cell proliferation and the probability of the therapeutic effect on cancer cells. With respect to patterns, it is possible to observe the inner necrotic core and the effect of the therapy destroying the tumor from its outer borders inwards.
Setny, Piotr; Zacharias, Martin
2010-07-01
A simple, semiheuristic solvation model based on a discrete, BCC grid of solvent cells has been presented. The model utilizes a mean field approach for the calculation of solute-solvent and solvent-solvent interaction energies and a cellular automata based algorithm for the prediction of solvent distribution in the presence of solute. The construction of the effective Hamiltonian for a solvent cell provides an explicit coupling between orientation-dependent water-solute electrostatic interactions and water-water hydrogen bonding. The water-solute dispersion interaction is also explicitly taken into account. The model does not depend on any arbitrary definition of the solute-solvent interface nor does it use a microscopic surface tension for the calculation of nonpolar contributions to the hydration free energies. It is demonstrated that the model provides satisfactory predictions of hydration free energies for drug-like molecules and is able to reproduce the distribution of buried water molecules within protein structures. The model is computationally efficient and is applicable to arbitrary molecules described by atomistic force field. PMID:20552986
NASA Astrophysics Data System (ADS)
Aono, Masashi; Gunji, Yukio-Pegio
2004-08-01
How can non-algorithmic/non-deterministic computational syntax be computed? "The hyperincursive system" introduced by Dubois is an anticipatory system embracing the contradiction/uncertainty. Although it may provide a novel viewpoint for the understanding of complex systems, conventional digital computers cannot run faithfully as the hyperincursive computational syntax specifies, in a strict sense. Then is it an imaginary story? In this paper we try to argue that it is not. We show that a model of complex systems "Elementary Conflictable Cellular Automata (ECCA)" proposed by Aono and Gunji is embracing the hyperincursivity and the nonlocality. ECCA is based on locality-only type settings basically as well as other CA models, and/but at the same time, each cell is required to refer to globality-dominant regularity. Due to this contradictory locality-globality loop, the time evolution equation specifies that the system reaches the deadlock/infinite-loop. However, we show that there is a possibility of the resolution of these problems if the computing system has parallel and/but non-distributed property like an amoeboid organism. This paper is an introduction to "the slime mold computing" that is an attempt to cultivate an unconventional notion of computation.
NASA Astrophysics Data System (ADS)
Egger, Jan; Nimsky, Christopher
2016-03-01
Due to the aging population, spinal diseases get more and more common nowadays; e.g., lifetime risk of osteoporotic fracture is 40% for white women and 13% for white men in the United States. Thus the numbers of surgical spinal procedures are also increasing with the aging population and precise diagnosis plays a vital role in reducing complication and recurrence of symptoms. Spinal imaging of vertebral column is a tedious process subjected to interpretation errors. In this contribution, we aim to reduce time and error for vertebral interpretation by applying and studying the GrowCut - algorithm for boundary segmentation between vertebral body compacta and surrounding structures. GrowCut is a competitive region growing algorithm using cellular automata. For our study, vertebral T2-weighted Magnetic Resonance Imaging (MRI) scans were first manually outlined by neurosurgeons. Then, the vertebral bodies were segmented in the medical images by a GrowCut-trained physician using the semi-automated GrowCut-algorithm. Afterwards, results of both segmentation processes were compared using the Dice Similarity Coefficient (DSC) and the Hausdorff Distance (HD) which yielded to a DSC of 82.99+/-5.03% and a HD of 18.91+/-7.2 voxel, respectively. In addition, the times have been measured during the manual and the GrowCut segmentations, showing that a GrowCutsegmentation - with an average time of less than six minutes (5.77+/-0.73) - is significantly shorter than a pure manual outlining.
Modelling the shrub encroachment in a grassland with a Cellular Automata Model
NASA Astrophysics Data System (ADS)
Caracciolo, D.; Noto, L. V.; Istanbulluoglu, E.
2014-09-01
Arid and semi-arid grasslands of southwestern North America have changed dramatically over the last 150 years as a result of shrub encroachment, i.e. the increase in density, cover and biomass of indigenous shrubby plants in grasslands. Numerous studies have documented the expansion of shrublands in the southwestern American grasslands; in particular shrub encroachment has occurred strongly in part of the northern Chihuahuan desert since 1860. This encroachment has been simulated using an ecohydrological Cellular Automata model, CATGraSS. It is a spatially distributed model driven by spatially explicit irradiance and runs on a fine-resolution gridded domain. Plant competition is modelled by keeping track of mortality and establishment of plants; both are calculated probabilistically based on soil moisture stress. For this study CATGraSS has been improved with a stochastic fire module and a grazing function. The model has been implemented in a small area in Sevilleta National Wildlife Refuge (SNWR), characterized by two vegetation types (grass savanna and creosote bush shrub), considering as encroachment causes the fire return period increase, the grazing increase, the seed dispersal caused by animals, the role of wind direction and plant type competition. The model is able to reproduce the encroachment that has occurred in SNWR, simulating an increase of the shrub from 2% in 1860 to the current shrub percentage, 42%, and highlighting among the most influential factors the reduced fire frequency and the increased grazing intensity.
Nanopatterned graphene quantum dots as building blocks for quantum cellular automata
NASA Astrophysics Data System (ADS)
Wang, Z. F.; Liu, Feng
2011-10-01
Quantum cellular automata (QCA) is an innovative approach that incorporates quantum entities in classical computation processes. Binary information is encoded in different charge states of the QCA cells and transmitted by the inter-cell Coulomb interaction. Despite the promise of QCA, however, it remains a challenge to identify suitable building blocks for the construction of QCA. Graphene has recently attracted considerable attention owing to its remarkable electronic properties. The planar structure makes it feasible to pattern the whole device architecture in one sheet, compatible with the existing electronics technology. Here, we demonstrate theoretically a new QCA architecture built upon nanopatterned graphene quantum dots (GQDs). Using the tight-binding model, we determine the phenomenological cell parameters and cell-cell response functions of the GQD-QCA to characterize its performance. Furthermore, a GQD-QCA architecture is designed to demonstrate the functionalities of a fundamental majority gate. Our results show great potential in manufacturing high-density ultrafast QCA devices from a single nanopatterned graphene sheet.
A scale-invariant cellular-automata model for distributed seismicity
NASA Technical Reports Server (NTRS)
Barriere, Benoit; Turcotte, Donald L.
1991-01-01
In the standard cellular-automata model for a fault an element of stress is randomly added to a grid of boxes until a box has four elements, these are then redistributed to the adjacent boxes on the grid. The redistribution can result in one or more of these boxes having four or more elements in which case further redistributions are required. On the average added elements are lost from the edges of the grid. The model is modified so that the boxes have a scale-invariant distribution of sizes. The objective is to model a scale-invariant distribution of fault sizes. When a redistribution from a box occurs it is equivalent to a characteristic earthquake on the fault. A redistribution from a small box (a foreshock) can trigger an instability in a large box (the main shock). A redistribution from a large box always triggers many instabilities in the smaller boxes (aftershocks). The frequency-size statistics for both main shocks and aftershocks satisfy the Gutenberg-Richter relation with b = 0.835 for main shocks and b = 0.635 for aftershocks. Model foreshocks occur 28 percent of the time.
Quasi-classical modeling of molecular quantum-dot cellular automata multidriver gates.
Rahimi, Ehsan; Nejad, Shahram Mohammad
2012-01-01
Molecular quantum-dot cellular automata (mQCA) has received considerable attention in nanoscience. Unlike the current-based molecular switches, where the digital data is represented by the on/off states of the switches, in mQCA devices, binary information is encoded in charge configuration within molecular redox centers. The mQCA paradigm allows high device density and ultra-low power consumption. Digital mQCA gates are the building blocks of circuits in this paradigm. Design and analysis of these gates require quantum chemical calculations, which are demanding in computer time and memory. Therefore, developing simple models to probe mQCA gates is of paramount importance. We derive a semi-classical model to study the steady-state output polarization of mQCA multidriver gates, directly from the two-state approximation in electron transfer theory. The accuracy and validity of this model are analyzed using full quantum chemistry calculations. A complete set of logic gates, including inverters and minority voters, are implemented to provide an appropriate test bench in the two-dot mQCA regime. We also briefly discuss how the QCADesigner tool could find its application in simulation of mQCA devices. PMID:22647345
NASA Astrophysics Data System (ADS)
Dolce, Donatello; Perali, Andrea
2015-07-01
Cellular Automata (CA) are represented at an effective level as intrinsic periodic phenomena, classical in the essence, reproducing the complete coherence (perfect recurrences) associated to pure quantum behaviours in condensed matter systems. By means of this approach it is possible to obtain a consistent, novel derivation of SuperConductivity (SC) essential phenomenology and of the peculiar quantum behaviour of electrons in graphene physics and Carbon Nanotubes (CNs), in which electrons cyclic dynamics simulate CA. In this way we will derive, from classical arguments, the essential electronic properties of these — or similar — graphene systems, such as energy bands and density of states. Similarly, in the second part of the paper, we will derive the fundamental phenomenology of SC by means of fundamental quantum dynamics and geometrical considerations, directly derived from the CA evolution law, rather than on empirical microscopical characteristics of the materials as in the standard approaches. This allows for a novel heuristic interpretation of the related gauge symmetry breaking and of the occurrence of high temperature superconductivity by means of simple considerations on the competition of quantum recurrence and thermal noise.
Cellular automata-based modelling and simulation of biofilm structure on multi-core computers.
Skoneczny, Szymon
2015-01-01
The article presents a mathematical model of biofilm growth for aerobic biodegradation of a toxic carbonaceous substrate. Modelling of biofilm growth has fundamental significance in numerous processes of biotechnology and mathematical modelling of bioreactors. The process following double-substrate kinetics with substrate inhibition proceeding in a biofilm has not been modelled so far by means of cellular automata. Each process in the model proposed, i.e. diffusion of substrates, uptake of substrates, growth and decay of microorganisms and biofilm detachment, is simulated in a discrete manner. It was shown that for flat biofilm of constant thickness, the results of the presented model agree with those of a continuous model. The primary outcome of the study was to propose a mathematical model of biofilm growth; however a considerable amount of focus was also placed on the development of efficient algorithms for its solution. Two parallel algorithms were created, differing in the way computations are distributed. Computer programs were created using OpenMP Application Programming Interface for C++ programming language. Simulations of biofilm growth were performed on three high-performance computers. Speed-up coefficients of computer programs were compared. Both algorithms enabled a significant reduction of computation time. It is important, inter alia, in modelling and simulation of bioreactor dynamics. PMID:26606102
A solution to the biodiversity paradox by logical deterministic cellular automata.
Kalmykov, Lev V; Kalmykov, Vyacheslav L
2015-06-01
The paradox of biological diversity is the key problem of theoretical ecology. The paradox consists in the contradiction between the competitive exclusion principle and the observed biodiversity. The principle is important as the basis for ecological theory. On a relatively simple model we show a mechanism of indefinite coexistence of complete competitors which violates the known formulations of the competitive exclusion principle. This mechanism is based on timely recovery of limiting resources and their spatio-temporal allocation between competitors. Because of limitations of the black-box modeling there was a problem to formulate the exclusion principle correctly. Our white-box multiscale model of two-species competition is based on logical deterministic individual-based cellular automata. This approach provides an automatic deductive inference on the basis of a system of axioms, and gives a direct insight into mechanisms of the studied system. It is one of the most promising methods of artificial intelligence. We reformulate and generalize the competitive exclusion principle and explain why this formulation provides a solution of the biodiversity paradox. In addition, we propose a principle of competitive coexistence. PMID:25980478
A cellular automata-based model of Earth's magnetosphere in relation with Dst index
NASA Astrophysics Data System (ADS)
Banerjee, Adrija; Bej, Amaresh; Chatterjee, T. N.
2015-05-01
The disturbance storm time (Dst) index, a measure of the strength of a geomagnetic storm, is difficult to predict by some conventional methods due to its abstract structural complexity and stochastic nature though a timely geomagnetic storm warning could save society from huge economic losses and hours of related hazards. Self-organized criticality and the concept of many-body interactive nonlinear system can be considered an explanation for the fundamental mechanism of the nonstationary geomagnetic disturbances controlled by the perturbed interplanetary conditions. The present paper approaches this natural phenomena by a sandpile-like cellular automata-based model of magnetosphere, taking the real-time solar wind and both the direction and magnitude of the B-Z component of the real-time interplanetary magnetic field as the system-controlling input parameters. Moreover, three new parameters had been introduced in the model which modify the functional relationships between the variables and regulate the dynamical behavior of the model to closely approximate the actual geomagnetic fluctuations. The statistical similarities between the dynamics of the model and that of the actual Dst index series during the entire 22nd solar cycle signifies the acceptability of the model.
The Cellular Automata for modelling of spreading of lava flow on the earth surface
NASA Astrophysics Data System (ADS)
Jarna, A.
2012-12-01
Volcanic risk assessment is a very important scientific, political and economic issue in densely populated areas close to active volcanoes. Development of effective tools for early prediction of a potential volcanic hazard and management of crises are paramount. However, to this date volcanic hazard maps represent the most appropriate way to illustrate the geographical area that can potentially be affected by a volcanic event. Volcanic hazard maps are usually produced by mapping out old volcanic deposits, however dynamic lava flow simulation gaining popularity and can give crucial information to corroborate other methodologies. The methodology which is used here for the generation of volcanic hazard maps is based on numerical simulation of eruptive processes by the principle of Cellular Automata (CA). The python script is integrated into ArcToolbox in ArcMap (ESRI) and the user can select several input and output parameters which influence surface morphology, size and shape of the flow, flow thickness, flow velocity and length of lava flows. Once the input parameters are selected, the software computes and generates hazard maps on the fly. The results can be exported to Google Maps (.klm format) to visualize the results of the computation. For validation of the simulation code are used data from a real lava flow. Comparison of the simulation results with real lava flows mapped out from satellite images will be presented.
The cellular automata for modelling of spreading of lava flow on the earth surface
NASA Astrophysics Data System (ADS)
Jarna, Alexandra; Cirbus, Juraj
2013-04-01
Volcanic risk assessment is a very important scientific, political and economic issue in densely populated areas close to active volcanoes. Development of effective tools for early prediction of a potential volcanic hazard and management of crises are paramount. However, to this date volcanic hazard maps represent the most appropriate way to illustrate the geographical area that can potentially be affected by a volcanic event. Volcanic hazard maps are usually produced by mapping out old volcanic deposits, however dynamic lava flow simulation gaining popularity and can give crucial information to corroborate other methodologies. The methodology which is used here for the generation of volcanic hazard maps is based on numerical simulation of eruptive processes by the principle of Cellular Automata (CA). The python script is integrated into ArcToolbox in ArcMap (ESRI) and the user can select several input and output parameters which influence surface morphology, size and shape of the flow, flow thickness, flow velocity and length of lava flows. Once the input parameters are selected, the software computes and generates hazard maps on the fly. The results can be exported to Google Maps (.klm format) to visualize the results of the computation. For validation of the simulation code are used data from a real lava flow.
Firing patterns in a random network cellular automata model of the brain
NASA Astrophysics Data System (ADS)
Acedo, L.; Lamprianidou, E.; Moraño, J.-A.; Villanueva-Oller, J.; Villanueva, R.-J.
2015-10-01
One of the main challenges in the simulation of even reduced areas of the brain is the presence of a large number of neurons and a large number of connections among them. Even from a theoretical point of view, the behaviour of dynamical models of complex networks with high connectivity is unknown, precisely because the cost of computation is still unaffordable and it will likely be in the near future. In this paper we discuss the simulation of a cellular automata network model of the brain including up to one million sites with a maximum average of three hundred connections per neuron. This level of connectivity was achieved thanks to a distributed computing environment based on the BOINC (Berkeley Open Infrastructure for Network Computing) platform. Moreover, in this work we consider the interplay among excitatory neurons (which induce the excitation of their neighbours) and inhibitory neurons (which prevent resting neurons from firing and induce firing neurons to pass to the refractory state). Our objective is to classify the normal (noisy but asymptotically constant patterns) and the abnormal (high oscillations with spindle-like behaviour) patterns of activity in the model brain and their stability and parameter ranges in order to determine the role of excitatory and inhibitory compensatory effects in healthy and diseased individuals.
Periodic forcing in a three-level cellular automata model for a vector-transmitted disease
NASA Astrophysics Data System (ADS)
Santos, L. B. L.; Costa, M. C.; Pinho, S. T. R.; Andrade, R. F. S.; Barreto, F. R.; Teixeira, M. G.; Barreto, M. L.
2009-07-01
A periodically forced two-dimensional cellular automata model is used to reproduce and analyze the complex spatiotemporal patterns observed in the transmission of vector infectious diseases. The system, which comprises three population levels, is introduced to describe complex features of the dynamics of the vector-transmitted dengue epidemics, known to be very sensitive to seasonal variables. The three coupled levels represent the human, the adult, and immature vector populations. The dynamics includes external seasonality forcing, human and mosquito mobility, and vector control effects. The model parameters, even if bounded to well-defined intervals obtained from reported data, can be selected to reproduce specific epidemic outbursts. In the current study, explicit results are obtained by comparison with actual data retrieved from the time series of dengue epidemics in two cities in Brazil. The results show fluctuations that are not captured by mean-field models. It also reveals the qualitative behavior of the spatiotemporal patterns of the epidemics. In the extreme situation of the absence of external periodic drive, the model predicts a completely distinct long-time evolution. The model is robust in the sense that it is able to reproduce the time series of dengue epidemics of different cities, provided that the forcing term takes into account the local rainfall modulation. Finally, an analysis is provided of the effect of the dependence between epidemics threshold and vector control actions, both in the presence and absence of human mobility factor.
Bennett clocking of quantum-dot cellular automata and the limits to binary logic scaling
NASA Astrophysics Data System (ADS)
Lent, Craig S.; Liu, Mo; Lu, Yuhui
2006-08-01
We examine power dissipation in different clocking schemes for molecular quantum-dot cellular automata (QCA) circuits. 'Landauer clocking' involves the adiabatic transition of a molecular cell from the null state to an active state carrying data. Cell layout creates devices which allow data in cells to interact and thereby perform useful computation. We perform direct solutions of the equation of motion for the system in contact with the thermal environment and see that Landauer's Principle applies: one must dissipate an energy of at least kBT per bit only when the information is erased. The ideas of Bennett can be applied to keep copies of the bit information by echoing inputs to outputs, thus embedding any logically irreversible circuit in a logically reversible circuit, at the cost of added circuit complexity. A promising alternative which we term 'Bennett clocking' requires only altering the timing of the clocking signals so that bit information is simply held in place by the clock until a computational block is complete, then erased in the reverse order of computation. This approach results in ultralow power dissipation without additional circuit complexity. These results offer a concrete example in which to consider recent claims regarding the fundamental limits of binary logic scaling.
NASA Astrophysics Data System (ADS)
Jokar Arsanjani, Jamal; Helbich, Marco; Kainz, Wolfgang; Darvishi Boloorani, Ali
2013-04-01
This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-economic variables dealing with urban sprawl were operationalised to create a probability surface of spatiotemporal states of built-up land use for the years 2006, 2016, and 2026. For validation, the model was evaluated by means of relative operating characteristic values for different sets of variables. The approach was calibrated for 2006 by cross comparing of actual and simulated land use maps. The achieved outcomes represent a match of 89% between simulated and actual maps of 2006, which was satisfactory to approve the calibration process. Thereafter, the calibrated hybrid approach was implemented for forthcoming years. Finally, future land use maps for 2016 and 2026 were predicted by means of this hybrid approach. The simulated maps illustrate a new wave of suburban development in the vicinity of Tehran at the western border of the metropolis during the next decades.
Studies of vehicle lane-changing to avoid pedestrians with cellular automata
NASA Astrophysics Data System (ADS)
Li, Xiang; Sun, Jian-Qiao
2015-11-01
This paper presents studies of interactions between vehicles and crossing pedestrians. A cellular automata system model of the traffic is developed, which includes a number of subsystem models such as the single-lane vehicle model, pedestrian model, interaction model and lane-changing model. The random street crossings of pedestrians are modeled as a Poisson process. The drivers of the passing vehicles are assumed to follow a safety-rule in order not to hit the pedestrians. The results of both single and multiple car simulations are presented. We have found that in general, the traffic can benefit from vehicle lane-changing to avoid road-crossing pedestrians. The traffic flow and average vehicle speed can be increased, which leads to higher traffic efficiency. The interactions between vehicles and pedestrians are reduced, which results in shorter vehicle decelerating time due to pedestrians and less switches of the driving mode, thus leads to the better energy economy. The traffic safety can be improved in the perspective of both vehicles and pedestrians. Finally, pedestrians can cross road faster. The negative effect of lane-changing is that pedestrians have to stay longer between the lanes in the crossing.
Evolutionary Design of one-dimensional Rule Changing cellular automata using genetic algorithms
NASA Astrophysics Data System (ADS)
Yun, Wu; Kanoh, Hitoshi
In this paper we propose a new method to obtain transition rules of one-dimensional two-state cellular automata (CAs) using genetic algorithms (GAs). CAs have the advantages of producing complex systems from the interaction of simple elements, and have attracted increased research interest. However, the difficulty of designing CAs' transition rules to perform a particular task has severely limited their applications. The evolutionary design of CA rules has been studied by the EVCA group in detail. A GA was used to evolve CAs for two tasks: density classification and synchronization problems. That GA was shown to have discovered rules that gave rise to sophisticated emergent computational strategies. Sipper has studied a cellular programming algorithm for 2-state non-uniform CAs, in which each cell may contain a different rule. Meanwhile, Land and Belew proved that the perfect two-state rule for performing the density classification task does not exist. However, Fuks´ showed that a pair of human written rules performs the task perfectly when the size of neighborhood is one. In this paper, we consider a pair of rules and the number of rule iterations as a chromosome, whereas the EVCA group considers a rule as a chromosome. The present method is meant to reduce the complexity of a given problem by dividing the problem into smaller ones and assigning a distinct rule to each one. Experimental results for the two tasks prove that our method is more efficient than a conventional method. Some of the obtained rules agree with the human written rules shown by Fuks´. We also grouped 1000 rules with high fitness into 4 classes according to the Langton's λ parameter. The rules obtained by the proposed method belong to Class- I, II, III or IV, whereas most of the rules by the conventional method belong to Class-IV only. This result shows that the combination of simple rules can perform complex tasks.
Lattice gas simulations of replicating domains
Dawson, S.P.; Hasslacher, B.; Pearson, J.E.
1993-12-31
We use the lattice gas cellular automation (LGCA) developed to simulate a process of pattern-formation recently observed in reaction-diffusion systems. We study the reaction mechanism, which is an extension of the Selkov model for glycolytic oscillations. We are able to reproduce the self-replicating domains observed in this work. We use the LGCA simulation to estimate the smallest length-scale on which this process can occur under conditions encountered in the cell. These estimates are similar to those obtained for Turing patterns in the same setting.
NASA Astrophysics Data System (ADS)
Pardo-Iguzquiza, Eulogio; Juan Collados Lara, Antonio; Pulido-Velazquez, David
2016-04-01
The snow availability in Alpine catchments is essential for the economy of these areas. It plays an important role in tourist development but also in the management of the Water Resources Snow is an important water resource in many river basins with mountains in the catchment area. The determination of the snow water equivalent requires the estimation of the evolution of the snow pack (cover area, thickness and snow density) along the time. Although there are complex physical models of the dynamics of the snow pack, sometimes the data available are scarce and a stochastic model like the cellular automata (CA) can be of great practical interest. CA can be used to model the dynamics of growth and wane of the snow pack. The CA is calibrated with historical data. This requires the determination of transition rules that are capable of modeling the evolution of the spatial pattern of snow cover area. Furthermore, CA requires the definition of states and neighborhoods. We have included topographical variables and climatological variables in order to define the state of each pixel. The evolution of snow cover in a pixel depends on its state, the state of the neighboring pixels and the transition rules. The calibration of the CA is done using daily MODIS data, available for the period 24/02/2002 to present with a spatial resolution of 500 m, and the LANDSAT information available with a sixteen-day periodicity from 1984 to the present and with spatial resolution of 30 m. The methodology has been applied to estimation of the snow cover area of Sierra Nevada mountain range in the Southern of Spain to obtain snow cover area daily information with 500 m spatial resolution for the period 1980-2014. Acknowledgments: This research has been partially supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank NASA DAAC and LANDSAT project for the data provided for this study.
NASA Astrophysics Data System (ADS)
Huang, Hua-mei; Zhang, Li-quan; Guan, Yu-juan; Wang, Dong-hui
2008-03-01
Biological invasion has received considerable attention recently because of increasing impacts on local ecosystems. Expansion of Spartina alterniflora, a non-native species, on the intertidal mudflats of Jiuduansha Shoals at the Yangtze River Estuary is a prime example of a spatially-structured invasion in a relatively simple habitat, for which strategic control efforts can be modeled and applied. Here, we developed a Cellular Automata (CA) model, in conjunction with Remote Sensing and Geographical Information Systems, to simulate the expanding process of S. alterniflora for a period of 8 years after being introduced to the new shoals, and to study the interactions between spatial pattern and ecosystem processes for the saltmarsh vegetation. The results showed that the CA model could simulate the population dynamics of S. alterniflora and Phragmites australis on the Jiuduansha Shoals successfully. The results strongly support the hypothesis of space pre-emption as well as range expansion with simple advancing wave fronts for these two species. In the Yangtze River Estuary, the native species P. australis shares the same niche with the exotic species S. alterniflora. However, the range expansion rate of P. australis was much slower than that of S. alterniflora. With the accretion of the Jiuduansha Shoals due to the large quantity of sediments deposited by the Yangtze River, a rapid range expansion of S. alterniflora is predicted to last for a long period into future. This study indicated the potential for this approach to provide valuable insights into population and community ecology of invasive species, which could be very important for wetland biodiversity conservation and resource management in the Yangtze River Estuary and other such impacted areas.
Coarse-graining of cellular automata, emergence, and the predictability of complex systems
NASA Astrophysics Data System (ADS)
Israeli, Navot; Goldenfeld, Nigel
2006-02-01
We study the predictability of emergent phenomena in complex systems. Using nearest-neighbor, one-dimensional cellular automata (CA) as an example, we show how to construct local coarse-grained descriptions of CA in all classes of Wolfram’s classification. The resulting coarse-grained CA that we construct are capable of emulating the large-scale behavior of the original systems without accounting for small-scale details. Several CA that can be coarse-grained by this construction are known to be universal Turing machines; they can emulate any CA or other computing devices and are therefore undecidable. We thus show that because in practice one only seeks coarse-grained information, complex physical systems can be predictable and even decidable at some level of description. The renormalization group flows that we construct induce a hierarchy of CA rules. This hierarchy agrees well with apparent rule complexity and is therefore a good candidate for a complexity measure and a classification method. Finally we argue that the large-scale dynamics of CA can be very simple, at least when measured by the Kolmogorov complexity of the large-scale update rule, and moreover exhibits a novel scaling law. We show that because of this large-scale simplicity, the probability of finding a coarse-grained description of CA approaches unity as one goes to increasingly coarser scales. We interpret this large-scale simplicity as a pattern formation mechanism in which large-scale patterns are forced upon the system by the simplicity of the rules that govern the large-scale dynamics.
NASA Astrophysics Data System (ADS)
Chen, Qingcai; Shi, Jianghong; Liu, Xiaowei; Wu, Wei; Liu, Bo; Zhang, Hui
2013-03-01
A cellular automata model (CA model) was used to simulate the soil column leaching process of estrogens during the processes of migration and transformation. The results of the simulated leaching experiment showed that the first-order degradation rates of 17α-ethynylestradiol (EE2), 17β-estradiol (E2) and estrone (E1) were 0.131 h- 1 for E2, 0.099 h- 1 for E1 and 0.064 h- 1 for EE2 in the EE2 and E2 leaching process, and the first-order sorption rates were 5.94 h- 1 for E2, 5.63 h- 1 for EE2, 3.125 h- 1 for E1. Their sorption rates were positively correlated with the n-octanol/water partition coefficients. When the diffusion rate was low, its impact on the simulation results was insignificant. The increase in sorption and degradation rates caused the decrease in the total estrogens that leached. In addition, increasing the sorption rate could delay the emerging time of the maximum concentration of estrogen that leached, whereas increasing the degradation rate could shorten the emerging time of the maximum concentration of estrogen that leached. The comparison made between the experimental data and the simulation results of the CA model and the HYDRUS-1D software showed that the establishment of one-component and multi-component CA models could simulate EE2 and E2 soil column leaching processes, and the CA models achieve an intuitive, dynamic, and visual simulation.
NASA Astrophysics Data System (ADS)
Zheng, Zhi-Zhen; Wang, Ai-Ling
2009-02-01
Spatially explicit models have become widely used in today's mathematical ecology and epidemiology to study the persistence of populations. For simplicity, population dynamics is often analysed by using ordinary differential equations (ODEs) or partial differential equations (PDEs) in the one-dimensional (1D) space. An important question is to predict species extinction or persistence rate by mean of computer simulation based on the spatial model. Recently, it has been reported that stable turbulent and regular waves are persistent based on the spatial susceptible-infected-resistant-susceptible (SIRS) model by using the cellular automata (CA) method in the two-dimensional (2D) space [Proc. Natl. Acad. Sci. USA 101, 18246 (2004)]. In this paper, we address other important issues relevant to phase transitions of epidemic persistence. We are interested in assessing the significance of the risk of extinction in 1D space. Our results show that the 2D space can considerably increase the possibility of persistence of spread of epidemics when the degree distribution of the individuals is uniform, i.e. the pattern of 2D spatial persistence corresponding to extinction in a 1D system with the same parameters. The trade-offs of extinction and persistence between the infection period and infection rate are observed in the 1D case. Moreover, near the trade-off (phase transition) line, an independent estimation of the dynamic exponent can be performed, and it is in excellent agreement with the result obtained by using the conjectured relationship of directed percolation. We find that the introduction of a short-range diffusion and a long-range diffusion among the neighbourhoods can enhance the persistence and global disease spread in the space.
NASA Astrophysics Data System (ADS)
Caracciolo, Domenico; Istanbulluoglu, Erkan; Noto, Leonardo V.
2014-05-01
Arid grasslands of southwestern North America have changed dramatically over the last 150 years as a result of the shrub encroachment, i.e. the increase in density and biomass of indigenous shrubby plants in grasslands. Numerous studies have documented the expansion of shrublands in the southwestern America Grasslands; in particular the encroachment of shrubs in american deserts has strongly occurred in the Chihuahuan deserts from 1860. The Sevilleta National Wildlife Refuge (SNWR), located in the northern Chihuahuan desert shows a dramatic encroachment front of creosote bush (i.e., shrub) into native desert grassland. This encroachment has been here simulated using an Ecohydrological Cellular Automata Model, CATGraSS. CATGraSS is a spatially distributed model driven by spatially explicit irradiance and runs on a fine-resolution gridded domain. In the model, each cell can hold a single plant type or can represent bare soil. Plant competition is modeled by keeping track of mortality and establishment of plants, both calculated probabilistically based on soil moisture stress. For this study, the model is improved with a stochastic fire and a grazing function, and its plant establishment algorithm is modified. CATGraSS is implemented in a small area (7.3 km2) in SNWR, characterized by two vegetation types: grass savanna and creosote bush. The causes that have been considered for the encroachment in this case study are: the fire return period increase, the grazing increase, the seed dispersal caused by animals, the role of wind direction and the shrub-grass inhibition effect. The model is able to reproduce the encroachment occurred in the SNWR basin, simulating an increasing of the shrub from 2% in 1860 to 42% (i.e., current shrub percentage) in 2010 highlighting as more influent factors the reduced fire frequency and the increased grazing intensity. For the future management and encroachment control, the reduction of the fire return period and the grazing removal
Chen, Qingcai; Shi, Jianghong; Liu, Xiaowei; Wu, Wei; Liu, Bo; Zhang, Hui
2013-03-01
A cellular automata model (CA model) was used to simulate the soil column leaching process of estrogens during the processes of migration and transformation. The results of the simulated leaching experiment showed that the first-order degradation rates of 17α-ethynylestradiol (EE2), 17β-estradiol (E2) and estrone (E1) were 0.131 h(-1) for E2, 0.099 h(-1) for E1 and 0.064 h(-1) for EE2 in the EE2 and E2 leaching process, and the first-order sorption rates were 5.94 h(-1) for E2, 5.63 h(-1) for EE2, 3.125 h(-1) for E1. Their sorption rates were positively correlated with the n-octanol/water partition coefficients. When the diffusion rate was low, its impact on the simulation results was insignificant. The increase in sorption and degradation rates caused the decrease in the total estrogens that leached. In addition, increasing the sorption rate could delay the emerging time of the maximum concentration of estrogen that leached, whereas increasing the degradation rate could shorten the emerging time of the maximum concentration of estrogen that leached. The comparison made between the experimental data and the simulation results of the CA model and the HYDRUS-1D software showed that the establishment of one-component and multi-component CA models could simulate EE2 and E2 soil column leaching processes, and the CA models achieve an intuitive, dynamic, and visual simulation. PMID:23376816
NASA Astrophysics Data System (ADS)
Mozumder, Chandan K.
The objective in crashworthiness design is to generate plastically deformable energy absorbing structures which can satisfy the prescribed force-displacement (FD) response. The FD behavior determines the reaction force, displacement and the internal energy that the structure should withstand. However, attempts to include this requirement in structural optimization problems remain scarce. The existing commercial optimization tools utilize models under static loading conditions because of the complexities associated with dynamic/impact loading. Due to the complexity of a crash event and the consequent time required to numerically analyze the dynamic response of the structure, classical methods (i.e., gradient-based and direct) are not well developed to solve this undertaking. This work presents an approach under the framework of the hybrid cellular automaton (HCA) method to solve the above challenge. The HCA method has been successfully applied to nonlinear transient topology optimization for crashworthiness design. In this work, the HCA algorithm has been utilized to develop an efficient methodology for synthesizing shell-based sheet metal structures with optimal material thickness distribution under a dynamic loading event using topometry optimization. This method utilizes the cellular automata (CA) computing paradigm and nonlinear transient finite element analysis (FEA) via ls-dyna. In this method, a set field variables is driven to their target states by changing a convenient set of design variables (e.g., thickness). These rules operate locally in cells within a lattice that only know local conditions. The field variables associated with the cells are driven to a setpoint to obtain the desired structure. This methodology is used to design for structures with controlled energy absorption with specified buckling zones. The peak reaction force and the maximum displacement are also constrained to meet the desired safety level according to passenger safety
Optimal design of variable-stiffness fiber-reinforced composites using cellular automata
NASA Astrophysics Data System (ADS)
Setoodeh, Shahriar
The growing number of applications of composite materials in aerospace and naval structures along with advancements in manufacturing technologies demand continuous innovations in the design of composite structures. In the traditional design of composite laminates, fiber orientation angles are constant for each layer and are usually limited to 0, 90, and +/-45 degrees. To fully benefit from the directional properties of composite laminates, such limitations have to be removed. The concept of variable-stiffness laminates allows the stiffness properties to vary spatially over the laminate. Through tailoring of fiber orientations and laminate thickness spatially in an optimal fashion, mechanical properties of a part can be improved. In this thesis, the optimal design of variable-stiffness fiber-reinforced composite laminates is studied using an emerging numerical engineering optimization scheme based on the cellular automata paradigm. A cellular automaton (CA) based design scheme uses local update rule for both field variables (displacements) and design variables (lay-up configuration and laminate density measure) in an iterative fashion to convergence to an optimal design. In the present work, the displacements are updated based on the principle of local equilibrium and the design variables are updated according to the optimality criteria for minimum compliance design. A closed form displacement update rule for constant thickness isotropic continua is derived, while for the general anisotropic continua with variable thickness a numeric update rule is used. Combined lay-up and topology design of variable-stiffness flat laminates is performed under the action of in-plane loads and bending loads. An optimality criteria based formulation is used to obtain local design rules for minimum compliance design subject to a volume constraint. It is shown that the design rule splits into a two step application. In the first step an optimal lay-up configuration is computed and in
Diemer, K.L.
1992-01-01
Lattice gas automata models for hydrodynamics offer a method for simulating fluids in between the standard molecular dynamic models and finite difference schemes. The algorithm is especially suited to low Mach number flow around complex boundaries and can be implemented in a fully parallelizable, memory efficient manner using only boolean operations. The simplest lattice gas automata is reviewed. The modification of the standard Chapmann-Enskog expansion lattice gas case is reviewed. In the long wavelength and long time limit, the incompressible Navier-Stokes equation is derived. Analytic calculations of shear viscosity [eta], mean free path [lambda], and a reduced Reynolds number R are presented for a number of 2D and 3D lattice gas models. Comparisons of lattice gas results with analytical predictions and other numerical methods are reviewed. This is followed by a discussion of the zero velocity limit used in deriving the above analytic results. Lattice gas hydrodynamic models for flows through porous media in two and three dimensions are described. The computational method easily handles arbitrary boundaries and a large range of Reynolds numbers. Darcy's law is confirmed for Poiseuille flow and for complicated boundary flows. Lattice gas simulation results for permeability for one geometry are compared with experimental results and found to agree to within 10%. Lattice gas hydrodynamic models for two dimensional binary fluids are described. The scaling of the correlation function during late stage growth is examined. The domain growth kinetics during this period is also explored and compared with the work of Furukawa. A local lattice gas model for binary fluids with an adjustable parameter [lambda] which allows degree of miscibility is introduced. For [lambda] < [lambda][sub c] the fluids are immiscible while for [lambda] > [lambda][sub c] the fluids are miscible. Theoretical and numerical studies on the diffusive properties of this lattice gas are presented.
Yang, Qing-Sheng; Qiao, Ji-Gang; Ai, Bin
2013-09-01
Taking the Dongguan City with rapid urbanization as a case, and selecting landscape ecological security level as evaluation criterion, the urbanization cellular number of 1 km x 1 km ecological security cells was obtained, and imbedded into the transition rules of cellular automata (CA) as the restraint term to control urban development, establish ecological security urban CA, and simulate ecological security urban development pattern. The results showed the integrated landscape ecological security index of the City decreased from 0.497 in 1998 to 0.395 in 2005, indicating that the ecological security at landscape scale was decreased. The CA-simulated integrated ecological security index of the City in 2005 was increased from the measured 0.395 to 0.479, showing that the simulated urban landscape ecological pressure from human became lesser, ecological security became better, and integrated landscape ecological security became higher. CA could be used as an effective tool in researching urban ecological security. PMID:24417120
Simulation of debris flow events in Sicily by cellular automata model SCIDDICA_SS3
NASA Astrophysics Data System (ADS)
Cancelliere, A.; Lupiano, V.; Peres, D. J.; Stancanelli, L.; Avolio, M.; Foti, E.; Di Gregorio, S.
2013-12-01
Debris flow models are widely used for hazard mapping or for evaluating the effectiveness of risk mitigation measures. Several models analyze the dynamics of debris flow runout solving Partial Differential Equations. In use of such models, difficulties arise in estimating kinematic geotechnical soil parameters for real phenomena. In order to overcome such difficulties, alternative semi-empirical approaches can be employed, such as macroscopic Cellular Automata (CA). In particular, for CA simulation purposes, the runout of debris flows emerges from local interactions in a dynamical system, subdivided into elementary parts, whose state evolves within a spatial and temporal discretum. The attributes of each cell (substates) describe physical characteristics. For computational reasons, the natural phenomenon is splitted into a number of elementary processes, whose proper composition makes up the CA transition function. By simultaneously applying this function to all the cells, the evolution of the phenomenon can be simulated in terms of modifications of the substates. In this study, we present an application of the macroscopic CA semi-empirical model SCIDDICA_SS3 to the Peloritani Mountains area in Sicily island, Italy. The model was applied using detailed data from the 1 October 2009 debris flow event, which was triggered by a rainfall event of about 250 mm falling in 9 hours, that caused the death of 37 persons. This region is characterized by river valleys with large hillslope angles (30°-60°), catchment basins of small extensions (0.5-12 km2) and soil composed by metamorphic material, which is easy to be eroded. CA usage implies a calibration phase, that identifies an optimal set of parameters capable of adequately play back the considered case, and a validation phase, that tests the model on a sufficient (and different) number of cases similar in terms of physical and geomorphological properties. The performance of the model can be measured in terms of a fitness
NASA Astrophysics Data System (ADS)
Vanwalleghem, T.; Jiménez-Hornero, F. J.; Giráldez, J. V.; Laguna, A.
2009-04-01
The process of tillage translocation is well studied and can be described adequately by different existing models. Nevertheless, in complex environments such as olive orchards, characterized by numerous obstacles, application of such conventional tillage erosion models is not straightforward. However, these obstacles have important effects on the spatial pattern of soil redistribution and on resulting soil properties. In this kind of environment, cellular automata could provide a valuable alternative. This study aims at developing a cellular automata model for tillage translocation (CATT) that can take into account such obstacles and at exploring its possibilities and limitations. A simple model was developed, which main parameters are tillage direction, speed and depth. Firstly, the modeĺs outcome was tested against existing 137Cs inventories for a study site in the Belgian loam belt. The observed spatial soil redistribution patterns could be adequately represented by the CATT model. Secondly, a sensitivity analysis was performed to explore the effect of input uncertainty on several selected model outputs. The variance-based extended FAST method was used to determine first and total order sensitivity indices. Tillage depth was identified as the input parameter that determined most of the output variance, followed respectively by tillage direction and speed. The difference between the total and first-order sensitivity indices, between 0.8 and 2, indicated that, in spite of the simple model structure, the model behaves non-linearly with respect to some of the model output variables. Higher-order interactions were especially important for determining the proportion of eroding and deposition cells. Finally, simulations were performed to analyse the model behaviour in complex landscapes, applying it to a field with protruding obstacles (e.g. olive trees). The model adequately represented some morphological features observed in the olive orchards, such as mounds around
NASA Astrophysics Data System (ADS)
van Wijk, Mark T.; Rodriguez-Iturbe, Ignacio
2002-09-01
Water is a key resource in determining the composition and structure of savanna ecosystems. In this study we present a simple cellular automata model in which death and reproduction chances of trees and grasses are based on the dynamical description of plant water stress by a probabilistic ecohydrological point model, using the parameterization for a Texas savanna. The results show that the model behavior, despite its simplicity, can be linked to ecological reality: the model yields a dynamic tree-grass coexistence driven by the annual rainfall, and the space-time behavior shows that both random and clustered tree distributions for periods up to 100 years can be observed. Both temporal and spatial model output display fractal characteristics suggesting the possibility of a self-organized critical dynamics. Thus power law behavior is observed in both the spectral density function and the cluster size distribution. The presence of spatial fractal characteristic opens avenues for more thorough model testing.
Christie, John A; Forrest, Ryan P; Corcelli, Steven A; Wasio, Natalie A; Quardokus, Rebecca C; Brown, Ryan; Kandel, S Alex; Lu, Yuhui; Lent, Craig S; Henderson, Kenneth W
2015-12-14
The preparation of 7-Fc(+) -8-Fc-7,8-nido-[C2 B9 H10 ](-) (Fc(+) FcC2 B9 (-) ) demonstrates the successful incorporation of a carborane cage as an internal counteranion bridging between ferrocene and ferrocenium units. This neutral mixed-valence Fe(II) /Fe(III) complex overcomes the proximal electronic bias imposed by external counterions, a practical limitation in the use of molecular switches. A combination of UV/Vis-NIR spectroscopic and TD-DFT computational studies indicate that electron transfer within Fc(+) FcC2 B9 (-) is achieved through a bridge-mediated mechanism. This electronic framework therefore provides the possibility of an all-neutral null state, a key requirement for the implementation of quantum-dot cellular automata (QCA) molecular computing. The adhesion, ordering, and characterization of Fc(+) FcC2 B9 (-) on Au(111) has been observed by scanning tunneling microscopy. PMID:26516063
Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein
2016-06-01
This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy. PMID:27154739
NASA Astrophysics Data System (ADS)
Bengtsson, L.
2014-12-01
A common way of addressing forecast uncertainty in Numerical Weather Prediction (NWP) models is to use ensemble prediction. The idea behind ensemble predictionis to simulate the sensitivity of the forecast to the initial and boundary conditions, as well as model construction error, such as sub-grid physical parameterizations. Existing methods used in order to account for such model consturction uncertainty include; multi-model ensembles, adding random perturbations to the tendencies produced by the parameterizations, or perturbing parameters within the parameterizations. Although such methods are successful in a probabilistic sense, individual ensemble members can be degraded in a deterministic sense by adding random non-physical perturbations. Furthermore, different ensemble members can have different bias (and skill) since they are based on separate models and/or parameters. Another way of accounting for model uncertainty (due to sub-grid variability) is to introduce random variability in the convection parameterization itself. Here we will present the impact of the stochastic deep convection parameterization using cellular automata described in Bengtsson et. al. 2013, as implemented in the high resolution meso-scale ensemble prediction system HarmonEPS. The questions we would like to answer are; can we improve the forecast skill both in a deterministic and probabilistic sense using the stochastic convection scheme? Can the stochastic parameterization in terms of the spread/skill relationship compete with the multi-model approach? Furthermore, the stochastic parameterization proposed in Bengtsson et. al. 2013 addresses lateral communication between model grid-boxes by using a cellular automaton. It was demonstrated that the scheme in a deterministic model is capable of contributing to the organization of convective squall-lines and meso-scale convective systems. We study if and how uncertainties with origin on the sub-grid scale transfer to the larger atmospheric
NASA Astrophysics Data System (ADS)
Ramírez-López, A.; Romero-Romo, M. A.; Muñoz-Negron, D.; López-Ramírez, S.; Escarela-Pérez, R.; Duran-Valencia, C.
2012-10-01
Computational models are developed to create grain structures using mathematical algorithms based on the chaos theory such as cellular automaton, geometrical models, fractals, and stochastic methods. Because of the chaotic nature of grain structures, some of the most popular routines are based on the Monte Carlo method, statistical distributions, and random walk methods, which can be easily programmed and included in nested loops. Nevertheless, grain structures are not well defined as the results of computational errors and numerical inconsistencies on mathematical methods. Due to the finite definition of numbers or the numerical restrictions during the simulation of solidification, damaged images appear on the screen. These images must be repaired to obtain a good measurement of grain geometrical properties. Some mathematical algorithms were developed to repair, measure, and characterize grain structures obtained from cellular automata in the present work. An appropriate measurement of grain size and the corrected identification of interfaces and length are very important topics in materials science because they are the representation and validation of mathematical models with real samples. As a result, the developed algorithms are tested and proved to be appropriate and efficient to eliminate the errors and characterize the grain structures.
Conway's game of life is a near-critical metastable state in the multiverse of cellular automata
NASA Astrophysics Data System (ADS)
Reia, Sandro M.; Kinouchi, Osame
2014-05-01
Conway's cellular automaton Game of Life has been conjectured to be a critical (or quasicritical) dynamical system. This criticality is generally seen as a continuous order-disorder transition in cellular automata (CA) rule space. Life's mean-field return map predicts an absorbing vacuum phase (ρ =0) and an active phase density, with ρ =0.37, which contrasts with Life's absorbing states in a square lattice, which have a stationary density of ρ2D≈0.03. Here, we study and classify mean-field maps for 6144 outer-totalistic CA and compare them with the corresponding behavior found in the square lattice. We show that the single-site mean-field approach gives qualitative (and even quantitative) predictions for most of them. The transition region in rule space seems to correspond to a nonequilibrium discontinuous absorbing phase transition instead of a continuous order-disorder one. We claim that Life is a quasicritical nucleation process where vacuum phase domains invade the alive phase. Therefore, Life is not at the "border of chaos," but thrives on the "border of extinction."
Conway's Game of Life is a near-critical metastable state in the multiverse of cellular automata.
Reia, Sandro M; Kinouchi, Osame
2014-05-01
Conway's cellular automaton Game of Life has been conjectured to be a critical (or quasicritical) dynamical system. This criticality is generally seen as a continuous order-disorder transition in cellular automata (CA) rule space. Life's mean-field return map predicts an absorbing vacuum phase (ρ = 0) and an active phase density, with ρ = 0.37, which contrasts with Life's absorbing states in a square lattice, which have a stationary density of ρ(2D) ≈ 0.03. Here, we study and classify mean-field maps for 6144 outer-totalistic CA and compare them with the corresponding behavior found in the square lattice. We show that the single-site mean-field approach gives qualitative (and even quantitative) predictions for most of them. The transition region in rule space seems to correspond to a nonequilibrium discontinuous absorbing phase transition instead of a continuous order-disorder one. We claim that Life is a quasicritical nucleation process where vacuum phase domains invade the alive phase. Therefore, Life is not at the "border of chaos," but thrives on the "border of extinction." PMID:25353755
NASA Astrophysics Data System (ADS)
Tiihonen, Juha; Schramm, Andreas; Kylänpää, Ilkka; Rantala, Tapio T.
2016-02-01
A thorough simulation study is carried out on thermal and quantum delocalization effects on the feasibility of a quantum-dot cellular automata (QCA) cell. The occupation correlation of two electrons is modeled with a simple four-site array of harmonic quantum dots (QD). QD sizes range from 20 nm to 40 nm with site separations from 20 nm to 100 nm, relevant for state-of-the-art GaAs/InAs semiconductor technology. The choice of parameters introduces QD overlap, which is only simulated properly with exact treatment of strong Coulombic correlation and thermal equilibrium quantum statistics. These are taken into account with path integral Monte Carlo approach. Thus, we demonstrate novel joint effects of quantum delocalization and decoherence in QCA, but also highly sophisticated quantitative evidence supporting the traditional relations in pragmatic QCA design. Moreover, we show the effects of dimensionality and spin state, and point out the parameter space conditions, where the ‘classical’ treatment becomes invalid.
NASA Astrophysics Data System (ADS)
Feliciani, Claudio; Nishinari, Katsuhiro
2016-06-01
In this article we present an improved version of the Cellular Automata floor field model making use of a sub-mesh system to increase the maximum density allowed during simulation and reproduce phenomena observed in dense crowds. In order to calibrate the model's parameters and to validate it we used data obtained from an empirical observation of bidirectional pedestrian flow. A good agreement was found between numerical simulation and experimental data and, in particular, the double outflow peak observed during the formation of deadlocks could be reproduced in numerical simulations, thus allowing the analysis of deadlock formation and dissolution. Finally, we used the developed high density model to compute the flow-ratio dependent fundamental diagram of bidirectional flow, demonstrating the instability of balanced flow and predicting the bidirectional flow behavior at very high densities. The model we presented here can be used to prevent dense crowd accidents in the future and to investigate the dynamics of the accidents which already occurred in the past. Additionally, fields such as granular and active matter physics may benefit from the developed framework to study different collective phenomena.
NASA Astrophysics Data System (ADS)
Chen, Qun; Wang, Yan
2015-08-01
This paper discusses the interaction of vehicle flows and pedestrian crossings on uncontrolled low-grade roads or branch roads without separating barriers in cities where pedestrians may cross randomly from any location on both sides of the road. The rules governing pedestrian street crossings are analyzed, and a cellular automata (CA) model to simulate the interaction of vehicle flows and pedestrian crossings is proposed. The influence of the interaction of vehicle flows and pedestrian crossings on the volume and travel time of the vehicle flow and the average wait time for pedestrians to cross is investigated through simulations. The main results of the simulation are as follows: (1) The vehicle flow volume decreases because of interruption from pedestrian crossings, but a small number of pedestrian crossings do not cause a significant delay to vehicles. (2) If there are many pedestrian crossings, slow vehicles will have little chance to accelerate, causing travel time to increase and the vehicle flow volume to decrease. (3) The average wait time for pedestrians to cross generally decreases with a decrease in vehicle flow volume and also decreases with an increase in the number of pedestrian crossings. (4) Temporal and spatial characteristics of vehicle flows and pedestrian flows and some interesting phenomena such as "crossing belt" and "vehicle belt" are found through the simulations.
Chai, C; Wong, Y D
2014-02-01
At intersection, vehicles coming from different directions conflict with each other. Improper geometric design and signal settings at signalized intersection will increase occurrence of conflicts between road users and results in a reduction of the safety level. This study established a cellular automata (CA) model to simulate vehicular interactions involving right-turn vehicles (as similar to left-turn vehicles in US). Through various simulation scenarios for four case cross-intersections, the relationships between conflict occurrences involving right-turn vehicles with traffic volume and right-turn movement control strategies are analyzed. Impacts of traffic volume, permissive right-turn compared to red-amber-green (RAG) arrow, shared straight-through and right-turn lane as well as signal setting are estimated from simulation results. The simulation model is found to be able to provide reasonable assessment of conflicts through comparison of existed simulation approach and observed accidents. Through the proposed approach, prediction models for occurrences and severity of vehicle conflicts can be developed for various geometric layouts and traffic control strategies. PMID:24275720
NASA Astrophysics Data System (ADS)
Gong, Wenfeng; Yuan, Li; Fan, Wenyi; Stott, Philip
2015-02-01
There have been rapid population and accelerating urban growth with associated changes in land use and soil degradation in northeast China, an important grain-producing region. The development of integrated use of remote sensing, geographic information systems, and combined cellular automata- Markov models has provided new means of assessing changes in land use and land cover, and has enabled projection of trajectories into the future. We applied such techniques to the prefecture-level city of Harbin, the tenth largest city in China. We found that there had been significant losses of the land uses termed "cropland", "grassland", "wetland", and "floodplain" in favour of "built-up land" and lesser transformations from "floodplain" to "forestland" and "water body" over the 18-year period. However, the transition was not a simple process but a complex network of changes, interchanges, and multiple transitions. In the absence of effective land use policies, projection of past trajectories into a balance state in the future would result in the decline of cropland from 65.6% to 46.9% and the increase of built-up area from 7.7% to 23.0% relative to the total area of the prefecture in 1989. It also led to the virtual elimination of land use types such as unused wetland and floodplain.
NASA Astrophysics Data System (ADS)
He, Yingqing; Ai, Bin; Yao, Yao; Zhong, Fajun
2015-06-01
Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model's parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China's Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model's parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.
Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun
2013-01-01
Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans. PMID:24244472
Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun
2013-01-01
Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans. PMID:24244472
Pokkuluri, Kiran Sree; Inampudi, Ramesh Babu; Nedunuri, S S S N Usha Devi
2014-01-01
Protein coding and promoter region predictions are very important challenges of bioinformatics (Attwood and Teresa, 2000). The identification of these regions plays a crucial role in understanding the genes. Many novel computational and mathematical methods are introduced as well as existing methods that are getting refined for predicting both of the regions separately; still there is a scope for improvement. We propose a classifier that is built with MACA (multiple attractor cellular automata) and MCC (modified clonal classifier) to predict both regions with a single classifier. The proposed classifier is trained and tested with Fickett and Tung (1992) datasets for protein coding region prediction for DNA sequences of lengths 54, 108, and 162. This classifier is trained and tested with MMCRI datasets for protein coding region prediction for DNA sequences of lengths 252 and 354. The proposed classifier is trained and tested with promoter sequences from DBTSS (Yamashita et al., 2006) dataset and nonpromoters from EID (Saxonov et al., 2000) and UTRdb (Pesole et al., 2002) datasets. The proposed model can predict both regions with an average accuracy of 90.5% for promoter and 89.6% for protein coding region predictions. The specificity and sensitivity values of promoter and protein coding region predictions are 0.89 and 0.92, respectively. PMID:25132849
Robust tracking by cellular automata and neural networks with nonlocal weights
NASA Astrophysics Data System (ADS)
Ososkov, Gennadii A.
1995-04-01
A modified rotor model of the Hopfield neural networks (HNN) is proposed for finding tracks in multiwire proportional chambers. That requires us to apply both raw data prefiltering by cellular automaton and HNN weights furnishing by a special robust multiplier. Then this model is developed to be applicable for a more general type of data and detectors. As an example, data processing of ionospheric measurements are considered. For handling tracks detected by high pressure drift chambers with their up-down ambiguity a modification of deformable templates method is proposed. A new concept of controlled HNN is proposed for solving the so-called track-match problem.
Mukhopadhyay, Anirban; Mondal, Parimal; Barik, Jyotiskona; Chowdhury, S M; Ghosh, Tuhin; Hazra, Sugata
2015-06-01
The composition and assemblage of mangroves in the Bangladesh Sundarbans are changing systematically in response to several environmental factors. In order to understand the impact of the changing environmental conditions on the mangrove forest, species composition maps for the years 1985, 1995 and 2005 were studied. In the present study, 1985 and 1995 species zonation maps were considered as base data and the cellular automata-Markov chain model was run to predict the species zonation for the year 2005. The model output was validated against the actual dataset for 2005 and calibrated. Finally, using the model, mangrove species zonation maps for the years 2025, 2055 and 2105 have been prepared. The model was run with the assumption that the continuation of the current tempo and mode of drivers of environmental factors (temperature, rainfall, salinity change) of the last two decades will remain the same in the next few decades. Present findings show that the area distribution of the following species assemblages like Goran (Ceriops), Sundari (Heritiera), Passur (Xylocarpus), and Baen (Avicennia) would decrease in the descending order, whereas the area distribution of Gewa (Excoecaria), Keora (Sonneratia) and Kankra (Bruguiera) dominated assemblages would increase. The spatial distribution of projected mangrove species assemblages shows that more salt tolerant species will dominate in the future; which may be used as a proxy to predict the increase of salinity and its spatial variation in Sundarbans. Considering the present rate of loss of forest land, 17% of the total mangrove cover is predicted to be lost by the year 2105 with a significant loss of fresh water loving mangroves and related ecosystem services. This paper describes a unique approach to assess future changes in species composition and future forest zonation in mangroves under the 'business as usual' scenario of climate change. PMID:25719448
NASA Astrophysics Data System (ADS)
Wang, Li; Liu, Mao; Meng, Bo
2013-02-01
In China, both the mountainous areas and the number of people who live in mountain areas occupy a significant proportion. When production accidents or natural disasters happen, the residents in mountain areas should be evacuated and the evacuation is of obvious importance to public safety. But it is a pity that there are few studies on safety evacuation in rough terrain. The particularity of the complex terrain in mountain areas, however, makes it difficult to study pedestrian evacuation. In this paper, a three-dimensional surface cellular automata model is proposed to numerically simulate the real time dynamic evacuation of residents. The model takes into account topographic characteristics (the slope gradient) of the environment and the biomechanics characteristics (weight and leg extensor power) of the residents to calculate the walking speed. This paper only focuses on the influence of topography and the physiological parameters are defined as constants according to a statistical report. Velocity varies with the topography. In order to simulate the behavior of a crowd with varying movement velocities, and a numerical algorithm is used to determine the time step of iteration. By doing so, a numerical simulation can be conducted in a 3D surface CA model. Moreover, considering residents evacuation around a gas well in a mountain area as a case, a visualization system for a three-dimensional simulation of pedestrian evacuation is developed. In the simulation process, population behaviors of congestion, queuing and collision avoidance can be observed. The simulation results are explained reasonably. Therefore, the model presented in this paper can realize a 3D dynamic simulation of pedestrian evacuation vividly in complex terrain and predict the evacuation procedure and evacuation time required, which can supply some valuable information for emergency management.
NASA Astrophysics Data System (ADS)
Sirakoulis, G. Ch.
2009-04-01
Greece is referred as the most active seismically region of Europe and one of the top active lands in the world. However, the complexity of the available seismicity information calls for the development of ever more powerful and more reliable computational tools to tackle complex problems associated with proper interpretation of the obtained geophysical information. Cellular Automata (CAs) were showed to be a promising model for earthquake modelling, because certain aspects of the earthquake dynamics, function and evolution can be simulated using several mathematical tools introduced through the use of CAs. In this study, a three-dimensional (3-d) CA dynamic system constituted of cell-charges and taking into account the recorded focal depth, able to simulate real earthquake activity is presented. The whole simulation process of the earthquake activity is evolved with an LC analogue CA model in correspondence to well known earthquake models. The parameterisation of the CA model in terms of potential threshold and geophysical area characteristics is succeeded by applying a standard genetic algorithm (GA) which would extend the model ability to study various hypotheses concerning the seismicity of the region under consideration. As a result, the proposed model optimizes the simulation results, which are compared with the Gutenberg - Richter (GR) scaling relations derived by the use of real data, as well as it expands its validity in broader and different regions of increased hazard. Finally, the hardware implementation of the proposed model is also examined. The FPGA realisation of the proposed 3-d CA based earthquake simulation model will exhibit distinct features that facilitate its utilisation, meaning low-cost, high-speed, compactness and portability. The development and manufacture of the dedicated processor aims at its effective incorporation into an efficient seismographic system. As a result, the dedicated processor could realize the first stage of a
Relating the sequential dynamics of excitatory neural networks to synaptic cellular automata.
Nekorkin, V I; Dmitrichev, A S; Kasatkin, D V; Afraimovich, V S
2011-12-01
We have developed a new approach for the description of sequential dynamics of excitatory neural networks. Our approach is based on the dynamics of synapses possessing the short-term plasticity property. We suggest a model of such synapses in the form of a second-order system of nonlinear ODEs. In the framework of the model two types of responses are realized-the fast and the slow ones. Under some relations between their timescales a cellular automaton (CA) on the graph of connections is constructed. Such a CA has only a finite number of attractors and all of them are periodic orbits. The attractors of the CA determine the regimes of sequential dynamics of the original neural network, i.e., itineraries along the network and the times of successive firing of neurons in the form of bunches of spikes. We illustrate our approach on the example of a Morris-Lecar neural network. PMID:22225361
A New Binning Method for Metagenomics by One-Dimensional Cellular Automata
Lin, Ying-Chih
2015-01-01
More and more developed and inexpensive next-generation sequencing (NGS) technologies allow us to extract vast sequence data from a sample containing multiple species. Characterizing the taxonomic diversity for the planet-size data plays an important role in the metagenomic studies, while a crucial step for doing the study is the binning process to group sequence reads from similar species or taxonomic classes. The metagenomic binning remains a challenge work because of not only the various read noises but also the tremendous data volume. In this work, we propose an unsupervised binning method for NGS reads based on the one-dimensional cellular automaton (1D-CA). Our binning method facilities to reduce the memory usage because 1D-CA costs only linear space. Experiments on synthetic dataset exhibit that our method is helpful to identify species of lower abundance compared to the proposed tool. PMID:26557648
Two-lane traffic rules for cellular automata: A systematic approach
Nagel, K. |; Wolf, D.E. |; Wagner, P. |; Simon, P.
1997-11-05
Microscopic modeling of multi-lane traffic is usually done by applying heuristic lane changing rules, and often with unsatisfying results. Recently, a cellular automation model for two-lane traffic was able to overcome some of these problems and to produce a correct density inversion at densities somewhat below the maximum flow density. In this paper, the authors summarize different approaches to lane changing and their results, and propose a general scheme, according to which realistic lane changing rules can be developed. They test this scheme by applying it to several different lane changing rules, which, in spite of their differences, generate similar and realistic results. The authors thus conclude that, for producing realistic results, the logical structure of the lane changing rules, as proposed here, is at least as important as the microscopic details of the rules.
McCoy, Sophie J; Allesina, Stefano; Pfister, Catherine A
2016-03-16
Historical ecological datasets from a coastal marine community of crustose coralline algae (CCA) enabled the documentation of ecological changes in this community over 30 years in the Northeast Pacific. Data on competitive interactions obtained from field surveys showed concordance between the 1980s and 2013, yet also revealed a reduction in how strongly species interact. Here, we extend these empirical findings with a cellular automaton model to forecast ecological dynamics. Our model suggests the emergence of a new dominant competitor in a global change scenario, with a reduced role of herbivory pressure, or trophic control, in regulating competition among CCA. Ocean acidification, due to its energetic demands, may now instead play this role in mediating competitive interactions and thereby promote species diversity within this guild. PMID:26936244
NASA Astrophysics Data System (ADS)
Seybold, P. G.; Kier, L. B.; Cheng, C.-K.
1999-12-01
Emissions from the 1S and 1D excited states of atomic oxygen play a prominent role in creating the dramatic light displays (aurora borealis) seen in the skies over polar regions of the Northern Hemisphere. A probabilistic asynchronous cellular automaton model described previously has been applied to the excited-state dynamics of atomic oxygen. The model simulates the time-dependent variations in ground (3P) and excited-state populations that occur under user-defined probabilistic transition rules for both pulse and steady-state conditions. Although each trial simulation is itself an independent "experiment", deterministic values for the excited-state emission lifetimes and quantum yields emerge as limiting cases for large numbers of cells or large numbers of trials. Stochastic variations in the lifetimes and emission yields can be estimated from repeated trials.
Two-material optimization of plate armour for blast mitigation using hybrid cellular automata
NASA Astrophysics Data System (ADS)
Goetz, J.; Tan, H.; Renaud, J.; Tovar, A.
2012-08-01
With the increased use of improvised explosive devices in regions at war, the threat to military and civilian life has risen. Cabin penetration and gross acceleration are the primary threats in an explosive event. Cabin penetration crushes occupants, damaging the lower body. Acceleration causes death at high magnitudes. This investigation develops a process of designing armour that simultaneously mitigates cabin penetration and acceleration. The hybrid cellular automaton (HCA) method of topology optimization has proven efficient and robust in problems involving large, plastic deformations such as crash impact. Here HCA is extended to the design of armour under blast loading. The ability to distribute two metallic phases, as opposed to one material and void, is also added. The blast wave energy transforms on impact into internal energy (IE) inside the solid medium. Maximum attenuation occurs with maximized IE. The resulting structures show HCA's potential for designing blast mitigating armour structures.
Visualization of Patterns and Self-organization of Cellular Automata in Urban Traffic Situations
NASA Astrophysics Data System (ADS)
Zhou, Lei; Brian, Schwartz
2001-06-01
The use of cellular automaton (CA) techniques is very good at modeling complex or nonlinear systems. In dynamic system within the context of discrete mathematical steps for CA simulations, simple local rules produce complex global rules. The simplicity of CA rules enables us to model and investigate more realistic models for the behavior traffic in two-dimensional flow systems. Our numerical solution presents self-organization behavior, which is called grid-lock for urban city street traffic and a phase transitions in the fundamental flow rate vs. density diagrams. We present calculations, which demonstrate the effects of micro CA rules and traffic parameters on the macro properties of traffic flow and behavior. We modified the stochastic parameter p, which is constant in the original CA rules, to a variable depending on the state of the vehicles. This structure of path dependence on history for traffic properties is in many cases analogous to solutions obtained for interactive magnetic systems. Using 3D ray tracer software, we are able to render the visualization of patterns of grid-lock into a 3D virtual urban environment.
Traffic dynamics around weaving section influenced by accident: Cellular automata approach
NASA Astrophysics Data System (ADS)
Kong, Lin-Peng; Li, Xin-Gang; Lam, William H. K.
2015-07-01
The weaving section, as a typical bottleneck, is one source of vehicle conflicts and an accident-prone area. Traffic accident will block lanes and the road capacity will be reduced. Several models have been established to study the dynamics around traffic bottlenecks. However, little attention has been paid to study the complex traffic dynamics influenced by the combined effects of bottleneck and accident. This paper presents a cellular automaton model to characterize accident-induced traffic behavior around the weaving section. Some effective control measures are proposed and verified for traffic management under accident condition. The total flux as a function of inflow rates, the phase diagrams, the spatial-temporal diagrams, and the density and velocity profiles are presented to analyze the impact of accident. It was shown that the proposed control measures for weaving traffic can improve the capacity of weaving section under both normal and accident conditions; the accidents occurring on median lane in the weaving section are more inclined to cause traffic jam and reduce road capacity; the capacity of weaving section will be greatly reduced when the accident happens downstream the weaving section.
NASA Astrophysics Data System (ADS)
Wu, J. J.; Sun, H. J.; Gao, Z. Y.
2008-09-01
Detrended fluctuation analysis (DFA) is a useful tool to measure the long-range power-law correlations in 1/f noise. In this paper, we investigate the power-law dynamics behavior of the density fluctuation time series generated by the famous Kerner-Klenov-Wolf cellular automata model in road traffic. Then the complexities of spatiotemporal, average speed, and the average density have been analyzed in detail. By introducing the DFA method, our main observation is that the free flow and wide moving jam phases correspond to the long-range anticorrelations. On the contrary, at the synchronized flow phase, the long-range correlated property is observed.
NASA Astrophysics Data System (ADS)
Bartoletti, Massimo
Usage automata are an extension of finite stata automata, with some additional features (e.g. parameters and guards) that improve their expressivity. Usage automata are expressive enough to model security requirements of real-world applications; at the same time, they are simple enough to be statically amenable, e.g. they can be model-checked against abstractions of program usages. We study here some foundational aspects of usage automata. In particular, we discuss about their expressive power, and about their effective use in run-time mechanisms for enforcing usage policies.
Evolving Transport Networks With Cellular Automata Models Inspired by Slime Mould.
Tsompanas, Michail-Antisthenis I; Sirakoulis, Georgios Ch; Adamatzky, Andrew I
2015-09-01
Man-made transport networks and their design are closely related to the shortest path problem and considered amongst the most debated problems of computational intelligence. Apart from using conventional or bio-inspired computer algorithms, many researchers tried to solve this kind of problem using biological computing substrates, gas-discharge solvers, prototypes of a mobile droplet, and hot ice computers. In this aspect, another example of biological computer is the plasmodium of acellular slime mould Physarum polycephalum (P. polycephalum), which is a large single cell visible by an unaided eye and has been proven as a reliable living substrate for implementing biological computing devices for computational geometry, graph-theoretical problems, and optimization and imitation of transport networks. Although P. polycephalum is easy to experiment with, computing devices built with the living slime mould are extremely slow; it takes slime mould days to execute a computation. Consequently, mapping key computing mechanisms of the slime mould onto silicon would allow us to produce efficient bio-inspired computing devices to tackle with hard to solve computational intelligence problems like the aforementioned. Toward this direction, a cellular automaton (CA)-based, Physarum-inspired, network designing model is proposed. This novel CA-based model is inspired by the propagating strategy, the formation of tubular networks, and the computing abilities of the plasmodium of P. polycephalum. The results delivered by the CA model demonstrate a good match with several previously published results of experimental laboratory studies on imitation of man-made transport networks with P. polycephalum. Consequently, the proposed CA model can be used as a virtual, easy-to-access, and biomimicking laboratory emulator that will economize large time periods needed for biological experiments while producing networks almost identical to the tubular networks of the real-slime mould. PMID
A lattice gas model for thermohydrodynamics
Chen, Shiyi; Chen, Hudong; Doolen, G.D.; Gutman, S.; Lee, M.
1990-05-03
The FHP lattice gas model is extended to include a temperature variable in order to study thermohydrodynamics. The compressible Navier-Stokes equations are derived using a Chapman-Enskog expansion. Heat conduction and convention problems are investigated, including Benard convention. It is shown that the usual FHP rescaling procedure can be avoided by controlling the temperature. 20 refs., 12 figs.
NASA Technical Reports Server (NTRS)
Fijany, Amir; Toomarian, Benny N.
2000-01-01
There has been significant improvement in the performance of VLSI devices, in terms of size, power consumption, and speed, in recent years and this trend may also continue for some near future. However, it is a well known fact that there are major obstacles, i.e., physical limitation of feature size reduction and ever increasing cost of foundry, that would prevent the long term continuation of this trend. This has motivated the exploration of some fundamentally new technologies that are not dependent on the conventional feature size approach. Such technologies are expected to enable scaling to continue to the ultimate level, i.e., molecular and atomistic size. Quantum computing, quantum dot-based computing, DNA based computing, biologically inspired computing, etc., are examples of such new technologies. In particular, quantum-dots based computing by using Quantum-dot Cellular Automata (QCA) has recently been intensely investigated as a promising new technology capable of offering significant improvement over conventional VLSI in terms of reduction of feature size (and hence increase in integration level), reduction of power consumption, and increase of switching speed. Quantum dot-based computing and memory in general and QCA specifically, are intriguing to NASA due to their high packing density (10(exp 11) - 10(exp 12) per square cm ) and low power consumption (no transfer of current) and potentially higher radiation tolerant. Under Revolutionary Computing Technology (RTC) Program at the NASA/JPL Center for Integrated Space Microelectronics (CISM), we have been investigating the potential applications of QCA for the space program. To this end, exploiting the intrinsic features of QCA, we have designed novel QCA-based circuits for co-planner (i.e., single layer) and compact implementation of a class of data permutation matrices, a class of interconnection networks, and a bit-serial processor. Building upon these circuits, we have developed novel algorithms and QCA
NASA Astrophysics Data System (ADS)
Caracciolo, Domenico; Istanbulluoglu, Erkan; Noto, Leonardo Valerio; Collins, Scott L.
2016-05-01
Arid and semiarid grasslands of southwestern North America have changed dramatically over the last 150 years as a result of woody plant encroachment. Overgrazing, reduced fire frequency, and climate change are known drivers of woody plant encroachment into grasslands. In this study, relatively simple algorithms for encroachment factors (i.e., grazing, grassland fires, and seed dispersal by grazers) are proposed and implemented in the ecohydrological Cellular-Automata Tree Grass Shrub Simulator (CATGraSS). CATGraSS is used in a 7.3 km2 rectangular domain located in central New Mexico along a zone of grassland to shrubland transition, where shrub encroachment is currently active. CATGraSS is calibrated and used to investigate the relative contributions of grazing, fire frequency, seed dispersal by herbivores and climate change on shrub abundance over a 150-year period of historical shrub encroachment. The impact of future climate change is examined using a model output that realistically represents current vegetation cover as initial condition, in a series of stochastic CATGraSS future climate simulations. Model simulations are found to be highly sensitive to the initial distribution of shrub cover. Encroachment factors more actively lead to shrub propagation within the domain when the model starts with randomly distributed individual shrubs. However, when shrubs are naturally evolved into clusters, the model response to encroachment factors is muted unless the effect of seed dispersal by herbivores is amplified. The relative contribution of different drivers on modeled shrub encroachment varied based on the initial shrub cover condition used in the model. When historical weather data is used, CATGraSS predicted loss of shrub and grass cover during the 1950 s drought. While future climate change is found to amplify shrub encroachment (∼13% more shrub cover by 2100), grazing remains the dominant factor promoting shrub encroachment. When we modeled future climate
Riccioli, Francesco; El Asmar, Toufic; El Asmar, Jean-Pierre; Fratini, Roberto
2013-07-01
The study of changes in land use has been included lately in territorial processes in order to optimize future management decisions. The different functions that the territory plays (production, aesthetic, and natural functions, etc.) make planning choices more difficult. This work focuses on the selection and combination of a set of indicators to analyze the variables through which the changes occur in the land used in viticulture for wine production. The proposed approach makes use of the Geographic Information System (GIS) in the development of a map of land use scenario. It is applied to a case study through a model involving cellular automata (CA) implemented with maps of suitability for viticulture and Markov chains. The use in this case of the CA is aimed at validating the scenario map in order to deduce the variables and the orientations of the farmers in the field of wine production. PMID:23076871
NASA Astrophysics Data System (ADS)
Zhang, Shuichao; Ren, Gang; Yang, Renfa
2013-10-01
The mixed bicycle flow refers to the bicycle flow containing electric bicycles. The traffic characteristics data of the mixed bicycle flow was collected by the virtual coil method in Nanjing and Ningbo, China. And the speed-density characteristics of the mixed bicycle flow with different proportions of electric bicycles were obtained. The results show that the overall speed of the mixed bicycle flow containing electric bicycles is higher than that of pure bicycle flow when the density is relatively low. The speed decreases when the density is higher than 0.08 bic/m2; the speed-density characteristics of the bicycles and the electric bicycles tend to be the same when the density is higher than 0.25 bic/m2. And when the density reaches 0.58 bic/m2, the mixed bicycle flow becomes blocked and the speed is zero. The cellular automata model and gas dynamics model were also adopted to simulate the speed-density characteristics of the mixed bicycle flow. The simulation results of the cellular automata model are effectively consistent with the actual survey data when the density is lower than 0.225 bic/m2; the simulation results of the gas dynamics model are effectively consistent with the actual survey data when the density is higher than 0.300 bic/m2; but both of the two types of simulation models are inapplicable when the density is between 0.225 and 0.300 bic/m2. These results will be used in the management of mixed bicycles and the research of vehicle-bicycle conflict and so on.
NASA Astrophysics Data System (ADS)
Mendicino, Giuseppe; Pedace, Jessica; Senatore, Alfonso
2015-04-01
Cellular Automata are often used for modeling the evolution in time of environmental systems mainly because they are directly compatible with parallel programming. Nevertheless, defining the optimal time step criterion for integrating forward in time numerical processes can further enhance model computational efficiency. To this aim, a numerical stability analysis of an original overland flow model, within the framework of a fully coupled eco-hydrological system based on the Macroscopic Cellular Automata paradigm, is performed. According to the other modules of the system describing soil water flow, soil-surface-atmosphere fluxes and vegetation dynamics, overland flow model equations were derived through a direct discrete formulation (i.e. no differential equations were discretized), adopting the diffusion wave model as an approximation of the full De Saint Venant equations and including the capability of accounting for specific processes, such as the increasing roughness effects due to vegetation growth or surface-soil water exchanges. Suitable formulations of robust tools usually applied in the stability analyses, such as Courant-Friedrichs-Lewy and von Neumann conditions, were initially derived for the CA-based overland flow model. Afterwards, the theoretical stability conditions were compared to experimental time step constraints through several numerical simulations of a 5-h rain event. Specifically, adopting a constant (i.e. not adaptive) time step for simulations, and discretizing head losses in a way that increases model stability, experimental upper limits preventing numerical instability were found for 13 test cases with different slopes, precipitation intensities, vegetation densities and depths of surface depressions. Even though von Neumann condition and experimental values were well positively correlated, the latter were almost always sensibly lower, excluding cases when free surface gradients tended to zero. Therefore, based on the original method
Nondestructive imaging of an ultracold lattice gas
NASA Astrophysics Data System (ADS)
Patil, Y. S.; Chakram, S.; Aycock, L. M.; Vengalattore, M.
2014-09-01
We demonstrate the nondestructive imaging of a lattice gas of ultracold bosons. Atomic fluorescence is induced in the simultaneous presence of degenerate Raman sideband cooling. The combined influence of these processes controllably cycles an atom between a dark state and a fluorescing state while eliminating heating and loss. Through spatially resolved sideband spectroscopy following the imaging sequence, we demonstrate the efficacy of this imaging technique in various regimes of lattice depth and fluorescence acquisition rate. Our work provides an important extension of quantum gas imaging to the nondestructive detection, control, and manipulation of atoms in optical lattices. In addition, our technique can also be extended to atomic species that are less amenable to molasses-based lattice imaging.
NASA Astrophysics Data System (ADS)
Tsukerblat, Boris; Palii, Andrew; Clemente-Juan, Juan Modesto; Coronado, Eugenio
2015-10-01
Our interest in this article is prompted by the vibronic problem of charge polarized states in the four-dot molecular quantum cellular automata (mQCA), a paradigm for nanoelectronics, in which binary information is encoded in charge configuration of the mQCA cell. Here, we report the evaluation of the electronic levels and adiabatic potentials of mixed-valence (MV) tetra-ruthenium (2Ru(ii) + 2Ru(iii)) derivatives (assembled as two coupled Creutz-Taube complexes) for which molecular implementations of quantum cellular automata (QCA) was proposed. The cell based on this molecule includes two holes shared among four spinless sites and correspondingly we employ the model which takes into account the two relevant electron transfer processes (through the side and through the diagonal of the square) as well as the difference in Coulomb energies for different instant positions of localization of the hole pair. The combined Jahn-Teller (JT) and pseudo JT vibronic coupling is treated within the conventional Piepho-Krauzs-Schatz model adapted to a bi-electronic MV species with the square-planar topology. The adiabatic potentials are evaluated for the low lying Coulomb levels in which the antipodal sites are occupied, the case just actual for utilization in mQCA. The conditions for the vibronic self-trapping in spin-singlet and spin-triplet states are revealed in terms of the two actual transfer pathways parameters and the strength of the vibronic coupling. Spin related effects in degrees of the localization which are found for spin-singlet and spin-triplet states are discussed. The polarization of the cell is evaluated and we demonstrate how the partial delocalization caused by the joint action of the vibronic coupling and electron transfer processes influences polarization of a four-dot cell. The results obtained within the adiabatic approach are compared with those based on the numerical solution of the dynamic vibronic problem. Finally, the Coulomb interaction between the
Tsukerblat, Boris E-mail: andrew.palii@uv.es; Palii, Andrew E-mail: andrew.palii@uv.es; Clemente-Juan, Juan Modesto; Coronado, Eugenio
2015-10-07
Our interest in this article is prompted by the vibronic problem of charge polarized states in the four-dot molecular quantum cellular automata (mQCA), a paradigm for nanoelectronics, in which binary information is encoded in charge configuration of the mQCA cell. Here, we report the evaluation of the electronic levels and adiabatic potentials of mixed-valence (MV) tetra-ruthenium (2Ru(II) + 2Ru(III)) derivatives (assembled as two coupled Creutz-Taube complexes) for which molecular implementations of quantum cellular automata (QCA) was proposed. The cell based on this molecule includes two holes shared among four spinless sites and correspondingly we employ the model which takes into account the two relevant electron transfer processes (through the side and through the diagonal of the square) as well as the difference in Coulomb energies for different instant positions of localization of the hole pair. The combined Jahn-Teller (JT) and pseudo JT vibronic coupling is treated within the conventional Piepho-Krauzs-Schatz model adapted to a bi-electronic MV species with the square-planar topology. The adiabatic potentials are evaluated for the low lying Coulomb levels in which the antipodal sites are occupied, the case just actual for utilization in mQCA. The conditions for the vibronic self-trapping in spin-singlet and spin-triplet states are revealed in terms of the two actual transfer pathways parameters and the strength of the vibronic coupling. Spin related effects in degrees of the localization which are found for spin-singlet and spin-triplet states are discussed. The polarization of the cell is evaluated and we demonstrate how the partial delocalization caused by the joint action of the vibronic coupling and electron transfer processes influences polarization of a four-dot cell. The results obtained within the adiabatic approach are compared with those based on the numerical solution of the dynamic vibronic problem. Finally, the Coulomb interaction between
NASA Astrophysics Data System (ADS)
Odagiri, Kenta; Takatsuka, Kazuo
2009-02-01
We report a comparative study on pattern formation between the methods of cellular automata (CA) and reaction-diffusion equations (RD) applying to a morphology of bacterial colony formation. To do so, we began the study with setting an extremely simple model, which was designed to realize autocatalytic proliferation of bacteria (denoted as X ) fed with nutrition (N) and their inactive state (prespore state) P1 due to starvation: X+N→2X and X→P1 , respectively. It was found numerically that while the CA could successfully generate rich patterns ranging from the circular fat structure to the viscous-finger-like complicated one, the naive RD reproduced only the circular pattern but failed to give a finger structure. Augmenting the RD equations by adding two physical factors, (i) a threshold effect in the dynamics of X+N→2X (breaking the continuity limit of RD) and (ii) internal noise with onset threshold (breaking the inherent symmetry of RD), we have found that the viscous-finger-like realistic patterns are indeed recovered by thus modified RD. This highlights the important difference between CA and RD, and at the same time, clarifies the necessary factors for the complicated patterns to emerge in such a surprisingly simple model system.
NASA Astrophysics Data System (ADS)
Bacani, Vitor Matheus; Sakamoto, Arnaldo Yoso; Quénol, Hervé; Vannier, Clémence; Corgne, Samuel
2016-01-01
The dynamics of land use/land cover change in the Lower Nhecolândia wetland are marked by deforestation for pasture expansion, resulting in a real threat to the ecological stability. The aim of our work was to analyze the spatial distribution of land cover changes in the Lower Nhecolândia from 1985 to 2013 and to predict changes in trends for 2040. The mapping of land cover changes was developed using Landsat satellite images of 1985, 1999, 2007, and 2013, based on geographic object-based image analysis approach. This study uses integrated Markov chains and cellular automata modeling and multicriteria evaluation techniques to produce transition probability maps and describe the trajectory analysis methodology to construct a continuity of spatial and temporal changes for the wetland. The results of the multitemporal change detection classification show that, from 1985 to 2013, the forest woodland decreased by 6.89% and the grassland class increased by 18.29%. On the other hand, all water bodies showed a reducing trend, while the bare soil class increased compared to 1985, but did not present a regular trend of increase or decrease. From the present day, the trend for the future is a reduction of almost 6.4% by 2040. We found that deforestation actions will be concentrated in the areas with the highest concentration of saline lakes, constituting a serious threat to the natural functioning of this environmental system.
Dakua, Sarada Prasad; Abinahed, Julien; Al-Ansari, Abdulla
2015-01-01
Abstract. Liver segmentation continues to remain a major challenge, largely due to its intense complexity with surrounding anatomical structures (stomach, kidney, and heart), high noise level and lack of contrast in pathological computed tomography (CT) data. We present an approach to reconstructing the liver surface in low contrast CT. The main contributions are: (1) a stochastic resonance-based methodology in discrete cosine transform domain is developed to enhance the contrast of pathological liver images, (2) a new formulation is proposed to prevent the object boundary, resulting from the cellular automata method, from leaking into the surrounding areas of similar intensity, and (3) a level-set method is suggested to generate intermediate segmentation contours from two segmented slices distantly located in a subject sequence. We have tested the algorithm on real datasets obtained from two sources, Hamad General Hospital and medical image computing and computer-assisted interventions grand challenge workshop. Various parameters in the algorithm, such as w, Δt, z, α, μ, α1, and α2, play imperative roles, thus their values are precisely selected. Both qualitative and quantitative evaluation performed on liver data show promising segmentation accuracy when compared with ground truth data reflecting the potential of the proposed method. PMID:26158101
Qiu, Menglong; Wang, Qi; Li, Fangbai; Chen, Junjian; Yang, Guoyi; Liu, Liming
2016-01-01
A customized logistic-based cellular automata (CA) model was developed to simulate changes in heavy metal contamination (HMC) in farmland soils of Dongguan, a manufacturing center in Southern China, and to discover the relationship between HMC and related explanatory variables (continuous and categorical). The model was calibrated through the simulation and validation of HMC in 2012. Thereafter, the model was implemented for the scenario simulation of development alternatives for HMC in 2022. The HMC in 2002 and 2012 was determined through soil tests and cokriging. Continuous variables were divided into two groups by odds ratios. Positive variables (odds ratios >1) included the Nemerow synthetic pollution index in 2002, linear drainage density, distance from the city center, distance from the railway, slope, and secondary industrial output per unit of land. Negative variables (odds ratios <1) included elevation, distance from the road, distance from the key polluting enterprises, distance from the town center, soil pH, and distance from bodies of water. Categorical variables, including soil type, parent material type, organic content grade, and land use type, also significantly influenced HMC according to Wald statistics. The relative operating characteristic and kappa coefficients were 0.91 and 0.64, respectively, which proved the validity and accuracy of the model. The scenario simulation shows that the government should not only implement stricter environmental regulation but also strengthen the remediation of the current polluted area to effectively mitigate HMC. PMID:26341341
NASA Astrophysics Data System (ADS)
Bello, S.; de Rienzo, F.; Nardi, G.
2003-04-01
The Turin (Italy) subsoil is mainly made up by alluvial gravels and sands (Pleistocene), characterised by high cementation degree variability, covered by a thin thickness of loess. These alluvial sediments, of about 40 m deep, overlay lacustrine clays (Villafranchiano), locally heteropic with marine sandstones (Pliocene). The reconstruction of the areal distribution of cementation phenomena of the Turin urban subsoil is of fundamental importance within the context of planning and carrying out works in the city subsoil, as well as for preliminary evaluating the stability of such underground works. Moreover, analyses of spatial distribution of soil cementation could be usefully applied for estimating the propagation of waste-polluted fluids, and for reducing either the natural or human-induced risk, related to the overworking of urban area subsoils. The development of mathematical models commonly needs to deal with several interacting physical and chemical phenomena. A deterministic Cellular Automata (CA) model for the evaluation of cementation processes in the conglomerates of the Turin urban subsoil has recently been developed, by using a three-dimensional geological model of the city subsoil based on boreholes data. The model is able to simulate the spatial distribution of the cementation process in the studied area: it has been derived from two pre-existing CA models, i.e. SCAVATU and CABOTO. Geological, mineralogical-petrographic and sedimentological studies of the soil cementation, and a chemical-physical study of the carbonatic equilibria, have first been carried out. These studies pointed out the presence of meniscus cements (which suggest a meteoric diagenesis) and gave fundamental cues for the development of base hypothesis on the genesis of cementation in the considered area. A macroscopic Cellular Automata model has accordingly been developed, in order to simulate the principal phenomena which take place during the cementation process. The model has a
NASA Astrophysics Data System (ADS)
Oku, Makito; Aihara, Kazuyuki
2010-11-01
A modularly-structured neural network model is considered. Each module, which we call a ‘cell’, consists of two parts: a Hopfield neural network model and a multilayered perceptron. An array of such cells is used to simulate the Rule 110 cellular automaton with high accuracy even when all the units of neural networks are replaced by stochastic binary ones. We also find that noise not only degrades but also facilitates computation if the outputs of multilayered perceptrons are below the threshold required to update the states of the cells, which is a stochastic resonance in computation.
NASA Astrophysics Data System (ADS)
Caracciolo, Domenico; Noto, Leonardo Valerio; Istanbulluoglu, Erkan; Fatichi, Simone; Zhou, Xiaochi
2014-11-01
Regions of vegetation transitions (ecotones) are known to be highly sensitive to climate fluctuations. In this study, the Cellular-Automata Tree Grass Shrub Simulator (CATGraSS) has been modified, calibrated and used with downscaled future climate scenarios to examine the role of climate change on vegetation patterns in a steep mountainous catchment (1.3 km2) located in Sicily, Italy. In the catchment, north-facing slopes are mostly covered by trees and grass, and south-facing slopes by Indian Fig opuntia and grass, with grasses dominating as elevation grows. CATGraSS simulates solar radiation, evapotranspiration, and soil moisture in space and time. Each model cell can hold a single plant type or can be bare soil. Plant competition is modeled explicitly through mortality and the establishment of individual plants in open spaces. In this study, CATGraSS is modified to account for heterogeneity in soil thickness and tested in the study catchment using the historical climate of the region. Predicted vegetation patterns are compared with those obtained from satellite images. Results of model under current climate underscore the importance of solar irradiance and soil thickness, especially in the uplands where soil is shallow, in determining vegetation composition over complex terrain. A stochastic weather generator is used to generate future climate change scenarios for the catchment by downscaling GCM realizations in space and time. Future increase in atmospheric CO2 concentration was considered through modifying the vegetation water use efficiency and stomatal resistance for our study site. Model results suggest that vegetation pattern is highly sensitive to temperature and rainfall variations provided by climate scenarios (30% reduction of the annual precipitation and a 2.8 °C increase of the mean annual temperature). Future climate change is predicted to bring a considerable reorganization of the plant composition following topographic patterns, leading to a
NASA Astrophysics Data System (ADS)
Ciampini, D.; Papini, M.
2011-08-01
A cellular automaton simulation which is able to predict the geometry of micro-features etched into ductile erosive targets, as a result of abrasive jet micromachining (AJM), is presented. Similar to a previous simulation for the AJM of brittle erosive targets, the movement of individual erodent particles is tracked in a simulated environment, including their collisions with, and ricochet from, the mask and target substrate modeled as cellular-automatons. A new cell erosion algorithm is presented in order to allow the previous simulation to be applied to the AJM of ductile materials. A previously published empirical erosion rule, which related the erosion rate of ductile substrates caused by a jet, was also proven to be applicable, to a good approximation, to single particle impacts. With this new cell erosion algorithm, the predictions of the model compared well with measurements of the surface evolution of unmasked channels, masked micro-holes and micro-channels machined in polymethyl-methacrylate. The results also highlight the importance of modeling the effect of particle size on the prediction of the size and shape of features fabricated in ductile erosive materials using AJM.
NASA Astrophysics Data System (ADS)
Pazzona, Federico G.; Demontis, Pierfranco; Suffritti, Giuseppe B.
2009-12-01
In the study of adsorption of simple adsorbates in microporous materials like zeolites, thermodynamic models of small grand-canonical cells with very local interactions [e.g., see K. G. Ayappa, J. Chem. Phys. 111, 4736 (1999)] have been proven to be able to produce thermodynamic properties in very good agreement with the results of experiments and atomistic simulations. In this paper we present in details the structure and implementation of a thermodynamic partitioning cellular automaton (PCA) devised as a dynamical version of thermodynamic cell models and proposed as an easy environment to perform coarse-grained simulations of adsorption/diffusion of simple interacting molecules in microporous materials. Local evolution rules and memory effects are introduced to make our PCA able to complete the static picture provided by thermodynamic cell models with the simulation of transport properties.
NASA Astrophysics Data System (ADS)
Liu, L.; Liu, Y.; Wang, X.; Yu, D.; Liu, K.; Huang, H.; Hu, G.
2014-09-01
Flash floods have occurred frequently and severely in the urban areas of South China. An effective process-oriented urban flood inundation model becomes an urgent demand for urban storm water and emergency management. This study develops an effective and flexible cellular automaton (CA) model to simulate storm water runoff and the flood inundation process during extreme storm events. The process of infiltration, inlets discharge and flow dynamic can be simulated only with little pre-processing on commonly available basic urban geographic data. In this model, a set of gravitational diverging rules are implemented in a cellular automation (CA) model to govern the water flow in a 3 x 3 cell template of a raster layer. The model is calibrated by one storm event and validated by another in a small urban catchment in Guangzhou of Southern China. The depth of accumulated water at the catchment outlet is interpreted from street monitoring sensors and verified by on-site survey. A good level of agreement between the simulated process and the reality is reached for both storm events. The model reproduces the changing extent and depth of flooded areas at the catchment outlet with an accuracy of 4 cm in water depth. Comparisons with a physically-based 2-D model (FloodMap) results show that the model have the capability of simulating flow dynamics. The high computational efficiency of CA model can satisfy the demand of city emergency management. The encouraging results of the simulations demonstrate that the CA-based approach is capable of effectively representing the key processes associated with a storm event and reproducing the process of water accumulation at the catchment outlet for making process-considered city emergency management decisions.
NASA Astrophysics Data System (ADS)
Liu, L.; Liu, Y.; Wang, X.; Yu, D.; Liu, K.; Huang, H.; Hu, G.
2015-03-01
Flash floods have occurred frequently in the urban areas of southern China. An effective process-oriented urban flood inundation model is urgently needed for urban storm-water and emergency management. This study develops an efficient and flexible cellular automaton (CA) model to simulate storm-water runoff and the flood inundation process during extreme storm events. The process of infiltration, inlets discharge and flow dynamics can be simulated with little preprocessing on commonly available basic urban geographic data. In this model, a set of gravitational diverging rules are implemented to govern the water flow in a rectangular template of three cells by three cells of a raster layer. The model is calibrated by one storm event and validated by another in a small urban catchment in Guangzhou of southern China. The depth of accumulated water at the catchment outlet is interpreted from street-monitoring closed-circuit television (CCTV) videos and verified by on-site survey. A good level of agreement between the simulated process and the reality is reached for both storm events. The model reproduces the changing extent and depth of flooded areas at the catchment outlet with an accuracy of 4 cm in water depth. Comparisons with a physically based 2-D model (FloodMap) show that the model is capable of effectively simulating flow dynamics. The high computational efficiency of the CA model can meet the needs of city emergency management.
Qiang, Yi; Lam, Nina S N
2015-03-01
As one of the most vulnerable coasts in the continental USA, the Lower Mississippi River Basin (LMRB) region has endured numerous hazards over the past decades. The sustainability of this region has drawn great attention from the international, national, and local communities, wanting to understand how the region as a system develops under intense interplay between the natural and human factors. A major problem in this deltaic region is significant land loss over the years due to a combination of natural and human factors. The main scientific and management questions are what factors contribute to the land use land cover (LULC) changes in this region, can we model the changes, and how would the LULC look like in the future given the current factors? This study analyzed the LULC changes of the region between 1996 and 2006 by utilizing an artificial neural network (ANN) to derive the LULC change rules from 15 human and natural variables. The rules were then used to simulate future scenarios in a cellular automation model. A stochastic element was added in the model to represent factors that were not included in the current model. The analysis was conducted for two sub-regions in the study area for comparison. The results show that the derived ANN models could simulate the LULC changes with a high degree of accuracy (above 92 % on average). A total loss of 263 km(2) in wetlands from 2006 to 2016 was projected, whereas the trend of forest loss will cease. These scenarios provide useful information to decision makers for better planning and management of the region. PMID:25647797
Transport of a lattice gas under continuous measurement
NASA Astrophysics Data System (ADS)
Cheung, Hil F. H.; Patil, Yogesh Sharad; Madjarov, Ivaylo S.; Chen, Huiyao Y.; Vengalattore, Mukund
2016-05-01
The act of measurement has a profound consequence on a quantum system. While this backaction has hitherto been discussed as a limitation to the precision of measurements, it is increasingly being appreciated that measurement backaction is a powerful means of quantum control. We have previously demonstrated that backaction from position measurement can modify the coherent tunneling rate of a lattice gas through the Quantum Zeno effect. By suitably designing measurement landscapes we can control the transport properties of the lattice gas. We describe a quantitative study of lattice gas dynamics under continuous quantum measurement in the context of a quantum to classical transition where the atom dynamics goes from a quantum walk at low measurement strengths to classical diffusion at high measurement strengths. We further discuss the prospect of using disorder measurement landscapes to realize a new form of Anderson localization. This work is supported by the ARO MURI on non-equilibrium dynamics.
Clemente-Juan, Juan Modesto; Palii, Andrew; Coronado, Eugenio; Tsukerblat, Boris
2016-08-01
In this article, we focus on the electron-vibrational problem of the tetrameric mixed-valence (MV) complexes proposed for implementation as four-dot molecular quantum cellular automata (mQCA).1 Although the adiabatic approximation explored in ref 2 is an appropriate tool for the qualitative analysis of the basic characteristics of mQCA, like vibronic trapping of the electrons encoding binary information and cell-cell response, it loses its accuracy providing moderate vibronic coupling and fails in the description of the discrete pattern of the vibronic levels. Therefore, a precise solution of the quantum-mechanical vibronic problem is of primary importance for the evaluation of the shapes of the electron transfer optical absorption bands and quantitative analysis of the main parameters of tetrameric quantum cells. Here, we go beyond the Born-Oppenheimer paradigm and present a solution of the quantum-mechanical pseudo Jahn-Teller (JT) vibronic problem in bielectronic MV species (exemplified by the tetra-ruthenium complexes) based on the recently developed symmetry-assisted approach.3,4 The mathematical approach to the vibronic eigenproblem takes into consideration the point symmetry basis, and therefore, the total matrix of the JT Hamiltonian is blocked to the maximum extent. The submatrices correspond to the irreducible representations (irreps) of the point group. With this tool, we also extend the theory of the mQCA cell beyond the limit of prevailing Coulomb repulsion in the electronic pair (adopted in ref 2), and therefore, the general pseudo-JT problems for spin-singlet ((1)B1g, 2(1)A1g, (1)B2g, (1)Eu) ⊗ (b1g + eu) and spin-triplet states ((3)A2g, (3)B1g, 2(3)Eu) ⊗ (b1g + eu) in a square-planar bielectronic system are solved. The obtained symmetry-adapted electron-vibrational functions are employed for the calculation of the profiles (shape functions) of the charge transfer absorption bands in the tetrameric MV complexes and for the discussion of the
Invariance principle for the stochastic Lorentz lattice gas
Hollander, F. den ); Naudts, J.; Redig, F. )
1992-03-01
The authors prove scaling to nondegenerate Brownian motion for the path of a test particle in the stochastic Lorentz lattice gas on Z[sup d] under a weak ergodicity assumption on the scatterer distribution. They prove that recurrence holds almost surely in d [le] 2. Transience in d [ge] 3 remains open.
Simulation of Wave Motion Using a Lattice Gas Model
NASA Astrophysics Data System (ADS)
Buick, J.; Easson, W.; Greated, C.
1996-02-01
The lattice gas model for simulating two-phase flow, proposed by Appert and Zaleski, has been modified by the introduction of gravitational interactions and the new model has been used to simulate standing wave patterns on the free surface of a fluid. The results compare well with linear theory.
Quantum lattice gas algorithm for the telegraph equation
NASA Astrophysics Data System (ADS)
Coffey, Mark W.; Colburn, Gabriel G.
2009-06-01
The telegraph equation combines features of both the diffusion and wave equations and has many applications to heat propagation, transport in disordered media, and elsewhere. We describe a quantum lattice gas algorithm (QLGA) for this partial differential equation with one spatial dimension. This algorithm generalizes one previously known for the diffusion equation. We present an analysis of the algorithm and accompanying simulation results. The QLGA is suitable for simulation on combined classical-quantum computers.
Lattice gas simulations of dynamical geometry in two dimensions
NASA Astrophysics Data System (ADS)
Klales, Anna; Cianci, Donato; Needell, Zachary; Meyer, David A.; Love, Peter J.
2010-10-01
We present a hydrodynamic lattice gas model for two-dimensional flows on curved surfaces with dynamical geometry. This model is an extension to two dimensions of the dynamical geometry lattice gas model previously studied in one dimension. We expand upon a variation of the two-dimensional flat space Frisch-Hasslacher-Pomeau (FHP) model created by Frisch [Phys. Rev. Lett.PRLTAO0031-9007 56, 1505 (1986)]10.1103/PhysRevLett.56.1505 and independently by Wolfram, and modified by Boghosian [Philos. Trans. R. Soc. London, Ser. A 360, 333 (2002)]10.1098/rsta.2001.0933. We define a hydrodynamic lattice gas model on an arbitrary triangulation whose flat space limit is the FHP model. Rules that change the geometry are constructed using the Pachner moves, which alter the triangulation but not the topology. We present results on the growth of the number of triangles as a function of time. Simulations show that the number of triangles grows with time as t1/3 , in agreement with a mean-field prediction. We also present preliminary results on the distribution of curvature for a typical triangulation in these simulations.
Lattice gas simulations of dynamical geometry in two dimensions.
Klales, Anna; Cianci, Donato; Needell, Zachary; Meyer, David A; Love, Peter J
2010-10-01
We present a hydrodynamic lattice gas model for two-dimensional flows on curved surfaces with dynamical geometry. This model is an extension to two dimensions of the dynamical geometry lattice gas model previously studied in one dimension. We expand upon a variation of the two-dimensional flat space Frisch-Hasslacher-Pomeau (FHP) model created by Frisch [Phys. Rev. Lett. 56, 1505 (1986)] and independently by Wolfram, and modified by Boghosian [Philos. Trans. R. Soc. London, Ser. A 360, 333 (2002)]. We define a hydrodynamic lattice gas model on an arbitrary triangulation whose flat space limit is the FHP model. Rules that change the geometry are constructed using the Pachner moves, which alter the triangulation but not the topology. We present results on the growth of the number of triangles as a function of time. Simulations show that the number of triangles grows with time as t(1/3), in agreement with a mean-field prediction. We also present preliminary results on the distribution of curvature for a typical triangulation in these simulations. PMID:21230410
Towards modeling DNA sequences as automata
NASA Astrophysics Data System (ADS)
Burks, Christian; Farmer, Doyne
1984-01-01
We seek to describe a starting point for modeling the evolution and role of DNA sequences within the framework of cellular automata by discussing the current understanding of genetic information storage in DNA sequences. This includes alternately viewing the role of DNA in living organisms as a simple scheme and as a complex scheme; a brief review of strategies for identifying and classifying patterns in DNA sequences; and finally, notes towards establishing DNA-like automata models, including a discussion of the extent of experimentally determined DNA sequence data present in the database at Los Alamos.
An extinction-survival-type phase transition in the probabilistic cellular automaton p182-q200
NASA Astrophysics Data System (ADS)
Mendonça, J. R. G.; de Oliveira, M. J.
2011-04-01
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.
A lattice gas of prime numbers and the Riemann Hypothesis
NASA Astrophysics Data System (ADS)
Vericat, Fernando
2013-10-01
In recent years, there has been some interest in applying ideas and methods taken from Physics in order to approach several challenging mathematical problems, particularly the Riemann Hypothesis. Most of these kinds of contributions are suggested by some quantum statistical physics problems or by questions originated in chaos theory. In this article, we show that the real part of the non-trivial zeros of the Riemann zeta function extremizes the grand potential corresponding to a simple model of one-dimensional classical lattice gas, the critical point being located at 1/2 as the Riemann Hypothesis claims.
A cellular automaton simulation of contaminant transport in porous media
Freed, D.M.; Simonson, S.A.
1995-12-01
A simulation tool to investigate radionuclide transport in porous groundwater flow is described. The flow systems of interest are those important in determining the fate of radionuclides emplaced in an underground repository, such as saturated matrix flow, matrix and fracture flow in the unsaturated zone, and viscous fingering in porous fractures. The work discussed here is confined to consideration of saturated flow in porous media carrying a dilute, sorptive species. The simulation technique is based on a special class of cellular automata known as lattice gas automata (LGA) which are capable of predicting hydrodynamic behavior. The original two-dimensional scheme (that of Frisch et. al. known as the FHP model) used particles of unit mass traveling on a triangular lattice with unit velocity and undergoing simple collisions which conserve mass and momentum at each node. These microscopic rules go over to the incompressible Navier-Stokes equations in the macroscopic limit. One of the strengths of this technique is the natural way that heterogeneities, such as boundaries, are accommodated. Complex geometries such as those associated with porous microstructures can be modeled effectively. Several constructions based on the FHP model have been devised, including techniques to eliminate statistical noise, extension to three dimensions, and the addition of surface tension which leads to multiphase flow.
Thermodynamics of a lattice gas with linear attractive potential
Pirjol, Dan; Schat, Carlos
2015-01-15
We study the equilibrium thermodynamics of a one-dimensional lattice gas with interaction V(|i−j|)=−1/(μn) (ξ−1/n |i−j|) given by the superposition of a universal attractive interaction with strength −1/(μn) ξ<0, and a linear attractive potential 1/(μn{sup 2}) |i−j|. The interaction is rescaled with the lattice size n, such that the thermodynamical limit n → ∞ is well-behaved. The thermodynamical properties of the system can be found exactly, both for a finite size lattice and in the thermodynamical limit n → ∞. The lattice gas can be mapped to a system of non-interacting bosons which are placed on known energy levels. The exact solution shows that the system has a liquid-gas phase transition for ξ > 0. In the large temperature limit T ≫ T{sub 0}(ρ) = ρ{sup 2}/(4μ) with ρ the density, the system becomes spatially homogeneous, and the equation of state is given to a good approximation by a lattice version of the van der Waals equation, with critical temperature T{sub c}{sup (vdW)}=1/(12μ) (3ξ−1)
NASA Technical Reports Server (NTRS)
Havelund, Klaus
2014-01-01
We present a form of automaton, referred to as data automata, suited for monitoring sequences of data-carrying events, for example emitted by an executing software system. This form of automata allows states to be parameterized with data, forming named records, which are stored in an efficiently indexed data structure, a form of database. This very explicit approach differs from other automaton-based monitoring approaches. Data automata are also characterized by allowing transition conditions to refer to other parameterized states, and by allowing transitions sequences. The presented automaton concept is inspired by rule-based systems, especially the Rete algorithm, which is one of the well-established algorithms for executing rule-based systems. We present an optimized external DSL for data automata, as well as a comparable unoptimized internal DSL (API) in the Scala programming language, in order to compare the two solutions. An evaluation compares these two solutions to several other monitoring systems.
Microscopic reversibility and macroscopic irreversibility: A lattice gas model
NASA Astrophysics Data System (ADS)
Pérez-Cárdenas, Fernando C.; Resca, Lorenzo; Pegg, Ian L.
2016-09-01
We present coarse-grained descriptions and computations of the time evolution of a lattice gas system of indistinguishable particles, whose microscopic laws of motion are exactly reversible, in order to investigate how or what kind of macroscopically irreversible behavior may eventually arise. With increasing coarse-graining and number of particles, relative fluctuations of entropy rapidly decrease and apparently irreversible behavior unfolds. Although that behavior becomes typical in those limits and within a certain range, it is never absolutely irreversible for any individual system with specific initial conditions. Irreversible behavior may arise in various ways. We illustrate one possibility by replacing detailed integer occupation numbers at lattice sites with particle probability densities that evolve diffusively.
Measurement-Induced Localization of an Ultracold Lattice Gas.
Patil, Y S; Chakram, S; Vengalattore, M
2015-10-01
The process of measurement can modify the state of a quantum system and its subsequent evolution. Here, we demonstrate the control of quantum tunneling in an ultracold lattice gas by the measurement backaction imposed by the act of imaging the atoms, i.e., light scattering. By varying the rate of light scattering from the atomic ensemble, we show the crossover from the weak measurement regime, where position measurements have little influence on tunneling dynamics, to the strong measurement regime, where measurement-induced localization causes a large suppression of tunneling--a manifestation of the quantum Zeno effect. Our study realizes an experimental demonstration of the paradigmatic Heisenberg microscope and sheds light on the implications of measurement on the coherent evolution of a quantum system. PMID:26551797
Unitary quantum lattice gas representation of 2D quantum turbulence
NASA Astrophysics Data System (ADS)
Zhang, Bo; Vahala, George; Vahala, Linda; Soe, Min
2011-05-01
Quantum vortex structures and energy cascades are examined for two dimensional quantum turbulence (2D QT) using a special unitary evolution algorithm. The qubit lattice gas (QLG) algorithm, is employed to simulate the weakly-coupled Bose-Einstein condensate (BEC) governed by the Gross-Pitaevskii (GP) equation. A parameter regime is uncovered in which, as in 3D QT, there is a very short Poincare recurrence time. This short recurrence time is destroyed as the nonlinear interaction energy is increased. Energy cascades for 2D QT are considered to examine whether 2D QT exhibits the inverse cascades of 2D classical turbulence. In the parameter regime considered, the spectra analysis reveals no such dual cascades---dual cascades being a hallmark of 2D classical turbulence.
Imaginary time integration method using a quantum lattice gas approach
NASA Astrophysics Data System (ADS)
Oganesov, Armen; Flint, Christopher; Vahala, George; Vahala, Linda; Yepez, Jeffrey; Soe, Min
2016-02-01
By modifying the collision operator in the quantum lattice gas (QLG) algorithm one can develop an imaginary time (IT) integration to determine the ground state solutions of the Schrödinger equation and its variants. These solutions are compared to those found by other methods (in particular the backward-Euler finite-difference scheme and the quantum lattice Boltzmann). In particular, the ground state of the quantum harmonic oscillator is considered as well as bright solitons in the one-dimensional (1D) non-linear Schrödinger equation. The dark solitons in an external potential are then determined. An advantage of the QLG IT algorithm is the avoidance of any real/complex matrix inversion and that its extension to arbitrary dimensions is straightforward.
Quantum lattice-gas model for the many-particle Schr{umlt o}dinger equation in d dimensions
Boghosian, B.M.; Taylor, W. IV
1998-01-01
We consider a general class of discrete unitary dynamical models on the lattice. We show that generically such models give rise to a wave function satisfying a Schr{umlt o}dinger equation in the continuum limit, in any number of dimensions. There is a simple mathematical relationship between the mass of the Schr{umlt o}dinger particle and the eigenvalues of a unitary matrix describing the local evolution of the model. Second quantized versions of these unitary models can be defined, describing in the continuum limit the evolution of a nonrelativistic quantum many-body theory. An arbitrary potential is easily incorporated into these systems. The models we describe fall in the class of quantum lattice-gas automata and can be implemented on a quantum computer with a speedup exponential in the number of particles in the system. This gives an efficient algorithm for simulating general nonrelativistic interacting quantum many-body systems on a quantum computer. {copyright} {ital 1998} {ital The American Physical Society}
NASA Technical Reports Server (NTRS)
Havelund, Klaus
2014-01-01
The field of runtime verification has during the last decade seen a multitude of systems for monitoring event sequences (traces) emitted by a running system. The objective is to ensure correctness of a system by checking its execution traces against formal specifications representing requirements. A special challenge is data parameterized events, where monitors have to keep track of the combination of control states as well as data constraints, relating events and the data they carry across time points. This poses a challenge wrt. efficiency of monitors, as well as expressiveness of logics. Data automata is a form of automata where states are parameterized with data, supporting monitoring of data parameterized events. We describe the full details of a very simple API in the Scala programming language, an internal DSL (Domain-Specific Language), implementing data automata. The small implementation suggests a design pattern. Data automata allow transition conditions to refer to other states than the source state, and allow target states of transitions to be inlined, offering a temporal logic flavored notation. An embedding of a logic in a high-level language like Scala in addition allows monitors to be programmed using all of Scala's language constructs, offering the full flexibility of a programming language. The framework is demonstrated on an XML processing scenario previously addressed in related work.
NASA Astrophysics Data System (ADS)
Ciampini, D.; Papini, M.
2010-04-01
A cellular automaton simulation for the prediction of the size and shape of masked features resulting from the abrasive jet micro-machining (AJM) of brittle targets was presented. The trajectories of individual erosive particles were tracked in the simulation, allowing for multiple particle to surface and particle to mask collisions. The target substrate and mask were both modelled as cellular automatons, and the substrate eroded due to individual particle impacts. The simulation allowed the prediction of complex phenomena such as mask under-etch, mask ricochet, spatial hindering and second-strike effects, which cannot be readily modelled using analytical techniques. The predictions of the simulation were compared with measurements of unmasked micro-holes and micro-channels in borosilicate glass, with the abrasive nozzle both perpendicular and oblique to the target surface, with very good agreement. The simulation was able to predict the surface evolution, including its curvature, more accurately than previous models. The results highlight the importance of modelling the effect of particle size distribution and second strikes in the prediction of the size and shape of features fabricated using AJM.
NASA Astrophysics Data System (ADS)
Barrio-Parra, Fernando; Rodríguez-Santalla, Inmaculada
2016-08-01
Coastal dunes are sedimentary environments characterized by their high dynamism. Their evolution is determined by sedimentary exchanges between the beach-dune subsystems and the dune dynamics itself. Knowledge about these exchanges is important to prioritize management and conservation strategies of these environments. The aim of this work is the inclusion of the aeolian transport rates obtained using a calibrated cellular automaton to estimate the beach-dune sediment exchange rates in a real active dune field at El Fangar Spit (Ebro Delta, Spain). The dune dynamics model is able to estimate average aeolian sediment fluxes. These are used in combination with the observed net sediment budget to obtain a quantitative characterization of the sediment exchange interactions. The methods produce a substantial improvement in the understanding of coastal sedimentary systems that could have major implications in areas where the management and conservation of dune fields are of concern.
Measurement-based quantum lattice gas model of fluid dynamics in 2+1 dimensions.
Micci, Michael M; Yepez, Jeffrey
2015-09-01
Presented are quantum simulation results using a measurement-based quantum lattice gas algorithm for Navier-Stokes fluid dynamics in 2+1 dimensions. Numerical prediction of the kinematic viscosity was measured by the decay rate of an initial sinusoidal flow profile. Due to local quantum entanglement in the quantum lattice gas, the minimum kinematic viscosity in the measurement-based quantum lattice gas is lower than achievable in a classical lattice gas. The numerically predicted viscosities precisely match the theoretical predictions obtained with a mean field approximation. Uniform flow profile with double shear layers, on a 16K×8K lattice, leads to the Kelvin-Helmholtz instability, breaking up the shear layer into pairs of counter-rotating vortices that eventually merge via vortex fusion and dissipate because of the nonzero shear viscosity. PMID:26465581
Measurement-based quantum lattice gas model of fluid dynamics in 2+1 dimensions
NASA Astrophysics Data System (ADS)
Micci, Michael M.; Yepez, Jeffrey
2015-09-01
Presented are quantum simulation results using a measurement-based quantum lattice gas algorithm for Navier-Stokes fluid dynamics in 2+1 dimensions. Numerical prediction of the kinematic viscosity was measured by the decay rate of an initial sinusoidal flow profile. Due to local quantum entanglement in the quantum lattice gas, the minimum kinematic viscosity in the measurement-based quantum lattice gas is lower than achievable in a classical lattice gas. The numerically predicted viscosities precisely match the theoretical predictions obtained with a mean field approximation. Uniform flow profile with double shear layers, on a 16 K ×8 K lattice, leads to the Kelvin-Helmholtz instability, breaking up the shear layer into pairs of counter-rotating vortices that eventually merge via vortex fusion and dissipate because of the nonzero shear viscosity.
NASA Astrophysics Data System (ADS)
Alonso-Sanz, Ramón; Adamatzky, Andy
Actin is a globular protein which forms long polar filaments in eukaryotic. The actin filaments play the roles of cytoskeleton, motility units, information processing and learning. We model actin filament as a double chain of finite state machines, nodes, which take states “0” and “1”. The states are abstractions of absence and presence of a subthreshold charge on actin units corresponding to the nodes. All nodes update their state in parallel to discrete time. A node updates its current state depending on states of two closest neighbors in the node chain and two closest neighbors in the complementary chain. Previous models of actin automata consider momentary state transitions of nodes. We enrich the actin automata model by assuming that states of nodes depend not only on the current states of neighboring node but also on their past states. Thus, we assess the effect of memory of past states on the dynamics of acting automata. We demonstrate in computational experiments that memory slows down propagation of perturbations, decrease entropy of space-time patterns generated, transforms traveling localizations to stationary oscillators, and stationary oscillations to still patterns.
Modeling biological pathway dynamics with timed automata.
Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N
2014-05-01
Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience. PMID:24808226
NASA Astrophysics Data System (ADS)
Caracciolo, Domenico; Fatichi, Simone; Istanbulluoglu, Erkan; Valerio Noto, Leonardo
2013-04-01
Predicting vegetation response in regions of ecotone transition under a changing climate is a among grand challenges in ecohydrology. In a small basin (1.3 sq km) in Sicily, Italy, where north-facing slopes are characterized by Quercus (tree), and south-facing slopes by Opuntia ficus-indaca (evergreen perennial species drought tolerant) and grasses we use an ecohydrological Cellular-Automaton model (CATGraSS) of vegetation coexistence driven by rainfall and solar radiation with downscaled future climate to examine the role of climate change on vegetation patterns. In the model, each cell can hold a single plant type or can be bare soil. Plant competition is modeled explicitly by keeping track of mortality and establishment of plants, both calculated probabilistically based on soil moisture stress. Topographic influence on incoming shortwave radiation is treated explicitly, which leads to spatial variations in potential evapotranspiration and resulting soil moisture and plant distribution. The influence of the soil thickness on the vegetation distribution is also introduced. The model is calibrated first using a representation of the current climate as a forcing and comparing the vegetation obtained from the model with the actual vegetation through statistical techniques.. The calibrated model is then forced with future climate scenarios generated using a stochastic downscaling technique based on the weather generator, AWE-GEN. This methodology allows for the downscaling of an ensemble of climate model outputs deriving the frequency distribution functions of factors of change for several statistics of temperature and precipitation from outputs of General Circulation Models. The stochastic downscaling is carried out using simulations of twelve General Circulation Models adopted in the IPCC 4AR, A1B emission scenario, for the future periods of 2046-2065 and 2081-2100. A high sensitivity of the vegetation distribution to variation of rainfall and temperature has been
NASA Astrophysics Data System (ADS)
Noto, L. V.; Caracciolo, D.; Fatichi, S.; Istanbulluoglu, E.
2013-12-01
Understanding and predicting vegetation change along ecosystem boundaries is among paramount challenges in ecohydrology. In this study, Cellular-Automaton Tree Grass Shrub Simulator (CATGraSS) is implemented in a small upland catchment in Sicily, IT, where north-facing slopes are characterized by quercus (trees), and south-facing slopes exhibit plant coexistence, composed of Opuntia ficus-indaca (shrub) and grasses, to examine the control of solar radiation on plant development and predict potential trajectories of vegetation change under the stress of global warming. CATGraSS is driven by stochastic rainfall and variable solar radiation on topography, represented by a fine-scale gridded domain where vegetation type at each cell is represented individually. In the model, each cell can hold a single plant type or remain empty. Plant competition is modeled explicitly by keeping track of mortality and establishment of plants, both calculated probabilistically based on soil moisture stress. Spatially explicit treatment of solar radiation, and a lower limit to soil moisture storage imposed by bedrock depth lead to spatial organization in evapotranspiration, soil moisture, runoff, and plant type. CATGraSS is first calibrated at the field site driven by stochastic climate that represent the current climate at the study site. Calibrated model results are examined against Google-Earth images. Implications of future climate change are examined using the advanced weather generator (AWE-GEN). AWE-GEN characterizes the statistical characteristics of selected climate variables and their change over time based on a multi-model ensemble of outputs from General Circulation Models (GCMs). Stochastic downscaling is carried out using simulations of twelve GCMs adopted in the IPCC 4AR, A1B emission scenario for the future scenarios 2046-2065 and 2081-2100. Future vegetation changed is predicted to bring a dramatic reorganization of the plant composition based mainly on the topography
Weighted Watson-Crick automata
NASA Astrophysics Data System (ADS)
Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku
2014-07-01
There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.
Weighted Watson-Crick automata
Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku
2014-07-10
There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.
Stochastic cellular automata model of neural networks.
Goltsev, A V; de Abreu, F V; Dorogovtsev, S N; Mendes, J F F
2010-06-01
We propose a stochastic dynamical model of noisy neural networks with complex architectures and discuss activation of neural networks by a stimulus, pacemakers, and spontaneous activity. This model has a complex phase diagram with self-organized active neural states, hybrid phase transitions, and a rich array of behaviors. We show that if spontaneous activity (noise) reaches a threshold level then global neural oscillations emerge. Stochastic resonance is a precursor of this dynamical phase transition. These oscillations are an intrinsic property of even small groups of 50 neurons. PMID:20866454
Self-similarity of phase-space networks of frustrated spin models and lattice gas models
NASA Astrophysics Data System (ADS)
Peng, Yi; Wang, Feng; Han, Yilong
2013-03-01
We studied the self-similar properties of the phase-spaces of two frustrated spin models and two lattice gas models. The frustrated spin models included (1) the anti-ferromagnetic Ising model on a two-dimensional triangular lattice (1a) at the ground states and (1b) above the ground states and (2) the six-vertex model. The two lattice gas models were (3) the one-dimensional lattice gas model and (4) the two-dimensional lattice gas model. The phase spaces were mapped to networks so that the fractal analysis of complex networks could be applied, i.e. the box-covering method and the cluster-growth method. These phase spaces, in turn, establish new classes of networks with unique self-similar properties. Models 1a, 2, and 3 with long-range power-law correlations in real space exhibit fractal phase spaces, while models 1b and 4 with short-range exponential correlations in real space exhibit nonfractal phase spaces. This behavior agrees with one of untested assumptions in Tsallis nonextensive statistics. Hong Kong GRC grants 601208 and 601911
The Hidden Symmetries of Spin-1 Ising Lattice Gas for Usual Quantum Hamiltonians
NASA Astrophysics Data System (ADS)
Payandeh, Farrin
2016-02-01
In this letter, the most common quantum Hamiltonian is exploited in order to compare the definite equivalences, corresponding to possible spin values in a lattice gas model, to those in a spin-1 Ising model. Our approach also requires interpolating both results in a p-state clock model, in order to find the hidden symmetries of both under consideration models.
Mitochondrial fusion through membrane automata.
Giannakis, Konstantinos; Andronikos, Theodore
2015-01-01
Studies have shown that malfunctions in mitochondrial processes can be blamed for diseases. However, the mechanism behind these operations is yet not sufficiently clear. In this work we present a novel approach to describe a biomolecular model for mitochondrial fusion using notions from the membrane computing. We use a case study defined in BioAmbient calculus and we show how to translate it in terms of a P automata variant. We combine brane calculi with (mem)brane automata to produce a new scheme capable of describing simple, realistic models. We propose the further use of similar methods and the test of other biomolecular models with the same behaviour. PMID:25417022
Common features in phase-space networks of frustrated spin models and lattice-gas models
NASA Astrophysics Data System (ADS)
Wang, Feng; Peng, Yi; Han, Yilong
2012-02-01
We mapped the phase spaces of the following four models into networks: (1a) the Ising antiferromagnet on triangular lattice at the ground state and (1b) above the ground state, (2) the six-vertex model (i.e. square ice or spin ice), (3) 1D lattice gas and (4) 2D lattice gas. Their phase-space networks share some common features including the Gaussian degree distribution, the Gaussian spectral density, and the small-world properties. Models 1a, 2 and 3 with long-range correlations in real space exhibit fractal phase spaces, while models 1b and 4 with short-range correlations in real space exhibit non-fractal phase spaces. This result supports one of the untested assumptions in Tsallis's non-extensive statistics.
Residual entropy and waterlike anomalies in the repulsive one dimensional lattice gas
Silva, Fernando Barbosa V. da; Oliveira, Fernando Albuquerque; Barbosa, Marco Aurélio A.
2015-04-14
The thermodynamics and kinetics of the one dimensional lattice gas with repulsive interaction are investigated using transfer matrix technique and Monte Carlo simulations. This simple model is shown to exhibit waterlike anomalies in density, thermal expansion coefficient, and self-diffusion. An unified description for the thermodynamic anomalies in this model is achieved based on the ground state residual entropy which appears in the model due to mixing entropy in a ground state phase transition.
Liquid polymorphism and density anomaly in a three-dimensional associating lattice gas.
Girardi, Mauricio; Balladares, Aline L; Henriques, Vera B; Barbosa, Marcia C
2007-02-14
The authors investigate the phase diagram of a three-dimensional associating lattice gas (ALG) model. This model combines orientational icelike interactions and "van der Waals" that might be repulsive, representing, in this case, a penalty for distortion of hydrogen bonds. These interactions can be interpreted as two competing distances, making the connection between this model and continuous isotropic soft-core potentials. The authors present Monte Carlo studies of the ALG model showing the presence of two liquid phases, two critical points, and density anomaly. PMID:17313225
Lattice-gas models of phase separation: interfaces, phase transitions, and multiphase flow
Rothman, D.H. ); Zaleski, S. )
1994-10-01
Momentum-conserving lattice gases are simple, discrete, microscopic models of fluids. This review describes their hydrodynamics, with particular attention given to the derivation of macroscopic constitutive equations from microscopic dynamics. Lattice-gas models of phase separation receive special emphasis. The current understanding of phase transitions in these momentum-conserving models is reviewed; included in this discussion is a summary of the dynamical properties of interfaces. Because the phase-separation models are microscopically time irreversible, interesting questions are raised about their relationship to real fluid mixtures. Simulation of certain complex-fluid problems, such as multiphase flow through porous media and the interaction of phase transitions with hydrodynamics, is illustrated.
Anticipating the Filtrons of Automata by Complex Discrete Systems Analysis
NASA Astrophysics Data System (ADS)
Siwak, Pawel
2002-09-01
Filtrons of automata are coherent structures (discrete solitons) supported by iterated automata maps (IAMs). They differ from signals of cellular automata. The signals emerge during parallel processing of strings, while IAMs transform strings in serial. We relate the filtron and its supporting automaton with a particular complex discrete system (CDS). This CDS has the form of a processing ring net. Its computation is characterized by four components: instructions of processing nodes (I), inter-processor communication constraints (C), initial data (D), and synchronization (S). We present an analysis of a computation performed within this CDS. It is useful in the problems of searching for any of the mentioned four components assuming that remaining three are known. We give a technique of anticipating the filtrons with a desired parameter C when I, S and D are given. We show how to decide the synchronization S when I, C and D are assumed, and how to determine instructions I when the desired filtron is described by known C, D and S.
Stochastic lattice gas model describing the dynamics of the SIRS epidemic process
NASA Astrophysics Data System (ADS)
de Souza, David R.; Tomé, Tânia
2010-03-01
We study a stochastic process describing the onset of spreading dynamics of an epidemic in a population composed of individuals of three classes: susceptible (S), infected (I), and recovered (R). The stochastic process is defined by local rules and involves the following cyclic process: S → I → R → S (SIRS). The open process S → I → R (SIR) is studied as a particular case of the SIRS process. The epidemic process is analyzed at different levels of description: by a stochastic lattice gas model and by a birth and death process. By means of Monte Carlo simulations and dynamical mean-field approximations we show that the SIRS stochastic lattice gas model exhibit a line of critical points separating the two phases: an absorbing phase where the lattice is completely full of S individuals and an active phase where S, I and R individuals coexist, which may or may not present population cycles. The critical line, that corresponds to the onset of epidemic spreading, is shown to belong in the directed percolation universality class. By considering the birth and death process we analyze the role of noise in stabilizing the oscillations.
Critical dynamics of the jamming transition in one-dimensional nonequilibrium lattice-gas models
NASA Astrophysics Data System (ADS)
Priyanka; Jain, Kavita
2016-04-01
We consider several one-dimensional driven lattice-gas models that show a phase transition in the stationary state between a high-density fluid phase in which the typical length of a hole cluster is of order unity and a low-density jammed phase where a hole cluster of macroscopic length forms in front of a particle. Using a hydrodynamic equation for an interface growth model obtained from the driven lattice-gas models of interest here, we find that in the fluid phase, the roughness exponent and the dynamic exponent that, respectively, characterize the scaling of the saturation width and the relaxation time of the interface with the system size are given by the Kardar-Parisi-Zhang exponents. However, at the critical point, we show analytically that when the equal-time density-density correlation function decays slower than inverse distance, the roughness exponent varies continuously with a parameter in the hop rates, but it is one-half otherwise. Using these results and numerical simulations for the density-density autocorrelation function, we further find that the dynamic exponent z =3 /2 in all cases.
Pair interaction lattice gas simulations: Flow past obstacles in two and three dimensions
Vogeler, A.; Wolf-Gladrow, D.A. )
1993-04-01
Apart from the FCHC (face-centered hypercube), Nasilowski's pair interaction lattice gas (PI) is the only known lattice gas automaton for three-dimensional hydrodynamic simulations. Unfortunately, the viscosity of PI is not isotropic. In order to determine the degree anisotropy, the authors derive fluid dynamic equations for the regime of compressible viscid flow. From relaxation measurements of waves propagating in various directions they compute the physically relevant dissipation coefficients and compare their results with theoretical predictions. Although PI shows a high degree of anisotropy, they define the mean value of the dissipation tensor as effective shear viscosity. Using this value of v[sub eff][sup 2D] = 0.35, two-dimensional simulations of flow past a cylinder yield drag coefficients in quantitative agreement with wind tunnel measurements over a range of Reynolds numbers of 5-50. Three-dimensional simulations of flow past a sphere yield qualitative agreement with various references. A fit of the results to a semi-empirical curve provides an effective value of v[sub eff][sup 2D] = 0.21 for a range of Reynolds numbers from 0.19 to 40. In order to check for finite-size effects, the authors measured the mean free path [lambda] and computed the Knudsen numbers. They obtained [lambda] [approx]1 lattice unit, corresponding to Kn = 0.01 (2D) and Kn = 0.1 (3D). They found no significant finite-size effects. 44 refs., 10 figs.
Quantum Control by Imaging: The Zeno Effect in an Ultracold Lattice Gas
NASA Astrophysics Data System (ADS)
Patil, Yogesh Sharad; Chakram, Srivatsan; Vengalattore, Mukund
2015-05-01
We demonstrate the control of quantum tunneling in an ultracold lattice gas by the measurement backaction imposed by an imaging process. A in situ imaging technique is used to acquire repeated images of an ultracold gas confined in a shallow optical lattice. The backaction induced by these position measurements modifies the coherent quantum tunneling of atoms within the lattice. By varying the rate at which atoms are imaged, we observe the crossover from the weak measurement regime, where the measurement has a negligible effect on coherent dynamics, to the strong measurement regime, where measurement-induced localization leads to a dramatic suppression of tunneling. The latter effect is a manifestation of the Quantum Zeno effect. We thereby demonstrate the paradigmatic Heisenberg microscope in a lattice gas, and shed light on the implications of quantum measurement on the coherent evolution of a mesoscopic quantum system. Our technique demonstrates a powerful tool for the control of an interacting many-body quantum system via spatially resolved measurement backaction. This work is supported by the ARO MURI on non-equilibrium dynamics.
Generalized information-lossless automata. I
Speranskii, D.V.
1995-01-01
Huffman and Even introduced classes of abstract automata, which they called respectively information-lossless automata (ILL) and information-lossless automata of finite order (ILLFO). The underlying property of these automata is the ability to reconstruct unknown input sequences from observations of the output response, assuming that the true initial state of the automaton is known. Similar classes of automata introduced in are called essentially information-lossless automata, and they are capable of reconstructing the unknown input word without knowledge of the initial state of the automaton. It is only assumed that the set of possible initial states of the automaton is the set of all automaton states. In this paper we analyze a structural analog of an abstract ILL-automaton whose set of initial states may be of arbitrary cardinality. This class of automata is thus a generalization of the classical ILL-automata, which allows not only for the structure of the input and output alphabets, but also for the configuration of the set of possible initial states.
Hunt, H. B.; Rosenkrantz, D. J.; Barrett, C. L.; Marathe, M. V.; Ravi, S. S.
2001-01-01
We identify several simple but powerful concepts, techniques, and results; and we use them to characterize the complexities of a number of basic problems II, that arise in the analysis and verification of the following models M of communicating automata and discrete dynamical systems: systems of communicating automata including both finite and infinite cellular automata, transition systems, discrete dynamical systems, and succinctly-specified finite automata. These concepts, techniques, and results are centered on the following: (1) reductions Of STATE-REACHABILITY problems, especially for very simple systems of communicating copies of a single simple finite automaton, (2) reductions of generalized CNF satisfiability problems [Sc78], especially to very simple communicating systems of copies of a few basic acyclic finite sequential machines, and (3) reductions of the EMPTINESS and EMPTINESS-OF-INTERSECTION problems, for several kinds of regular set descriptors. For systems of communicating automata and transition systems, the problems studied include: all equivalence relations and simulation preorders in the Linear-time/Branching-time hierarchies of equivalence relations and simulation preorders of [vG90, vG93], both without and with the hiding abstraction. For discrete dynamical systems, the problems studied include the INITIAL and BOUNDARY VALUE PROBLEMS (denoted IVPs and BVPs, respectively), for nonlinear difference equations over many different algebraic structures, e.g. all unitary rings, all finite unitary semirings, and all lattices. For succinctly specified finite automata, the problems studied also include the several problems studied in [AY98], e.g. the EMPTINESS, EMPTINESS-OF-INTERSECTION, EQUIVALENCE and CONTAINMENT problems. The concepts, techniques, and results presented unify and significantly extend many of the known results in the literature, e.g. [Wo86, Gu89, BPT91, GM92, Ra92, HT94, SH+96, AY98, AKY99, RH93, SM73, Hu73, HRS76, HR78], for
H. B. HUNT; D. J. ROSENKRANTS; ET AL
2001-03-01
We identify several simple but powerful concepts, techniques, and results; and we use them to characterize the complexities of a number of basic problems II, that arise in the analysis and verification of the following models M of communicating automata and discrete dynamical systems: systems of communicating automata including both finite and infinite cellular automata, transition systems, discrete dynamical systems, and succinctly-specified finite automata. These concepts, techniques, and results are centered on the following: (i) reductions Of STATE-REACHABILITY problems, especially for very simple systems of communicating copies of a single simple finite automaton, (ii) reductions of generalized CNF satisfiability problems [Sc78], especially to very simple communicating systems of copies of a few basic acyclic finite sequential machines, and (iii) reductions of the EMPTINESS and EMPTINESS-OF-INTERSECTION problems, for several kinds of regular set descriptors. For systems of communicating automata and transition systems, the problems studied include: all equivalence relations and simulation preorders in the Linear-time/Branching-time hierarchies of equivalence relations and simulation preorders of [vG90, vG93], both without and with the hiding abstraction. For discrete dynamical systems, the problems studied include the INITIAL and BOUNDARY VALUE PROBLEMS (denoted IVPs and BVPS, respectively), for nonlinear difference equations over many different algebraic structures, e.g. all unitary rings, all finite unitary semirings, and all lattices. For succinctly-specified finite automata, the problems studied also include the several problems studied in [AY98], e.g. the EMPTINESS, EMPTINESS-OF-INTERSECTION, EQUIVALENCE and CONTAINMENT problems. The concepts, techniques, and results presented unify and significantly extend many of the known results in the literature, e.g. [Wo86, Gu89, BPT91, GM92, Ra92, HT94, SH+96, AY98, AKY99, RH93, SM73, Hu73, HRS76, HR78], for
NASA Astrophysics Data System (ADS)
Medved', I.; Trník, A.; Černý, Robert
2014-12-01
We investigate which isotherm equation arises when a lattice gas with rather general lateral interactions is used to model an adsorption of particles on a solid surface at subcritical temperatures. For simplicity, an energetically homogeneous surface is considered, and only a single phase is assumed to be stable in the system. We show that, up to a constant, the result is a sum of terms that have the same form as the Hill isotherm or, less accurately, as the Freundlich isotherm. Each of these terms contains three types of microscopic parameters whose relation to the details of the considered lattice gas, such as its lateral interactions, is provided. We also provide a formula for the heat of adsorption and discuss the phenomenon of adsorption compression. We illustrate the results for a simple lattice gas on a triangular lattice with pair and triple interactions. Possible extensions to inhomogeneous surfaces, multi-component adsorption, and phase coexistence regions are pointed out.
Stochastic computing with biomolecular automata
NASA Astrophysics Data System (ADS)
Adar, Rivka; Benenson, Yaakov; Linshiz, Gregory; Rosner, Amit; Tishby, Naftali; Shapiro, Ehud
2004-07-01
Stochastic computing has a broad range of applications, yet electronic computers realize its basic step, stochastic choice between alternative computation paths, in a cumbersome way. Biomolecular computers use a different computational paradigm and hence afford novel designs. We constructed a stochastic molecular automaton in which stochastic choice is realized by means of competition between alternative biochemical pathways, and choice probabilities are programmed by the relative molar concentrations of the software molecules coding for the alternatives. Programmable and autonomous stochastic molecular automata have been shown to perform direct analysis of disease-related molecular indicators in vitro and may have the potential to provide in situ medical diagnosis and cure.
Competition of coarsening and shredding of clusters in a driven diffusive lattice gas
NASA Astrophysics Data System (ADS)
Kunwar, Ambarish; Chowdhury, Debashish; Schadschneider, Andreas; Nishinari, Katsuhiro
2006-06-01
We investigate a driven diffusive lattice gas model with two oppositely moving species of particle. The model is motivated by bidirectional traffic of ants on a pre-existing trail. A third species, corresponding to pheromones used by the ants for communication, is not conserved and mediates interactions between the particles. Here we study the spatio-temporal organization of the particles. In the unidirectional variant of this model it is known to be determined by the formation and coarsening of 'loose clusters'. For our bidirectional model, we show that the interaction of oppositely moving clusters is essential. In the late stages of evolution the cluster size oscillates because of a competition between their 'shredding' during encounters with oppositely moving counterparts and subsequent 'coarsening' during collision-free evolution. We also establish a nontrivial dependence of the spatio-temporal organization on the system size.
Glass transition in the quenched and annealed version of the frustrated lattice gas model
NASA Astrophysics Data System (ADS)
Fierro, Annalisa; de Candia, Antonio; Coniglio, Antonio
2000-12-01
In this paper we study the three-dimensional frustrated lattice gas model in the annealed version, where the disorder is allowed to evolve in time with a suitable kinetic constraint. Although the model does not exhibit any thermodynamic transition it shows a diverging peak at some characteristic time in the dynamical nonlinear susceptibility, similar to the results on the p-spin model in mean field and the Lennard-Jones mixture recently found by Donati et al. (e-print cond-mat/9905433). Comparing these results to those obtained in the model with quenched interactions, we conclude that the critical behavior of the dynamical susceptibility is reminiscent of the thermodynamic transition present in the quenched model, and signaled by the divergence of the static nonlinear susceptibility, suggesting therefore a similar mechanism also in supercooled glass-forming liquids.
The high density phase of the k-NN hard core lattice gas model
NASA Astrophysics Data System (ADS)
Nath, Trisha; Rajesh, R.
2016-07-01
The k-NN hard core lattice gas model on a square lattice, in which the first k next nearest neighbor sites of a particle are excluded from being occupied by another particle, is the lattice version of the hard disc model in two dimensional continuum. It has been conjectured that the lattice model, like its continuum counterpart, will show multiple entropy-driven transitions with increasing density if the high density phase has columnar or striped order. Here, we determine the nature of the phase at full packing for k up to 820 302 . We show that there are only eighteen values of k, all less than k = 4134, that show columnar order, while the others show solid-like sublattice order.
Simulating the time-dependent Schr"odinger equation with a quantum lattice-gas algorithm
NASA Astrophysics Data System (ADS)
Prezkuta, Zachary; Coffey, Mark
2007-03-01
Quantum computing algorithms promise remarkable improvements in speed or memory for certain applications. Currently, the Type II (or hybrid) quantum computer is the most feasible to build. This consists of a large number of small Type I (pure) quantum computers that compute with quantum logic, but communicate with nearest neighbors in a classical way. The arrangement thus formed is suitable for computations that execute a quantum lattice gas algorithm (QLGA). We report QLGA simulations for both the linear and nonlinear time-dependent Schr"odinger equation. These evidence the stable, efficient, and at least second order convergent properties of the algorithm. The simulation capability provides a computational tool for applications in nonlinear optics, superconducting and superfluid materials, Bose-Einstein condensates, and elsewhere.
Self-avoiding modes of motion in a deterministic Lorentz lattice gas
NASA Astrophysics Data System (ADS)
Webb, B. Z.; Cohen, E. G. D.
2014-08-01
We study the motion of a particle on the two-dimensional honeycomb lattice, whose sites are occupied by either flipping rotators or flipping mirrors, which scatter the particle according to a deterministic rule. For both types of scatterers we find a new type of motion that has not been observed in a Lorentz Lattice gas, where the particle's trajectory is a self-avoiding walk between returns to its initial position. We show that this behavior is a consequence of the deterministic scattering rule and the particular class of initial scatterer configurations we consider. Since self-avoiding walks are one of the main tools used to model the growth of crystals and polymers, the particle's motion in this class of systems is potentially important for the study of these processes.
NASA Astrophysics Data System (ADS)
Rubio Puzzo, M. Leticia; Saracco, Gustavo P.; Bab, Marisa A.
2016-02-01
Phase transitions and damage spreading for a lattice gas model with mixed driven lattice gas (DLG)-Glauber dynamics are studied by means of Monte Carlo simulations. In order to control the number of sites updated according to the nonconservative Glauber dynamics, a parameter pɛ [ 0 , 1 ] is defined. In this way, for p = 0 the system corresponds to the DLG model with biased Kawasaki conservative dynamics, while for p = 1 it corresponds to the Ising model with Glauber dynamics. The results obtained show that the introduction of nonconservative dynamics dramatically affects the behavior of the DLG model, leading to the existence of Ising-like phase transitions from fully occupied to disordered states. The short-time dynamics results suggest that this transition is second order for values of p = 0.1 and p > 0.6 and first order for 0.1 < p ≤ 0.6. On the other hand, damage always spreads within the investigated temperature range and reaches a saturation value Dsat that depends on the system size, the temperature, and p. The value of Dsat in the thermodynamic limit is estimated by performing a finite-size analysis. For p < 0.6 the results show a change in the behavior of Dsat with temperature, similar to those reported for the pure (p = 0) DLG model. However, for p ≥ 0.6 the data remind us of the Ising (p = 1) curves. In each case, a damage temperature TD(p) can be defined as the value where either Dsat reaches a maximum or it becomes nonzero. This temperature is, within error bars, similar to the reported values of the temperatures that characterize the mentioned phase transitions.
Crackling sound generation during the formation of liquid bridges: A lattice gas model
NASA Astrophysics Data System (ADS)
Almeida, Alexandre B.; Buldyrev, Sergey V.; Alencar, Adriano M.
2013-08-01
Due to abnormal mechanical instabilities, liquid bridges may form in the small airways blocking airflow. Liquid bridge ruptures during inhalation are the major cause of the crackling adventitious lung sound, which can be heard using a simple stethoscope. Recently, Vyshedskiy and colleagues (2009) [1] described and characterized a crackle sound originated during expiration. However, the mechanism and origin of the expiratory crackle are still controversial. Thus, in this paper, we propose a mechanism for expiratory crackles. We hypothesize that the expiratory crackle sound is a result of the energy released in the form of acoustic waves during the formation of the liquid bridge. The magnitude of the energy released is proportional to the difference in free energy prior and after the bridge formation. We use a lattice gas model to describe the liquid bridge formation between two parallel planes. Specifically, we determine the surface free energy and the conditions of the liquid bridge formation between two parallel planes separated by a distance 2h by a liquid droplet of volume Ω and contact angle Θ, using both Monte Carlo simulation of a lattice gas model and variational calculus based on minimization of the surface area with the volume and the contact angle constrained. We numerically and analytically determine the phase diagram of the system as a function of the dimensionless parameter hΩ and Θ. We can distinguish two different phases: one droplet and one liquid bridge. We observe a hysteresis curve for the energy changes between these two states, and a finite size effect in the bridge formation. We compute the release of free energy during the formation of the liquid bridge and discuss the results in terms of system size. We also calculate the force exerted from liquid bridge on the planes by studying the dependence of the free energy on the separation between the planes 2h. The simulation results are in agreement with the analytical solution.
Distribution functions of probabilistic automata
NASA Technical Reports Server (NTRS)
Vatan, F.
2001-01-01
Each probabilistic automaton M over an alphabet A defines a probability measure Prob sub(M) on the set of all finite and infinite words over A. We can identify a k letter alphabet A with the set {0, 1,..., k-1}, and, hence, we can consider every finite or infinite word w over A as a radix k expansion of a real number X(w) in the interval [0, 1]. This makes X(w) a random variable and the distribution function of M is defined as usual: F(x) := Prob sub(M) { w: X(w) < x }. Utilizing the fixed-point semantics (denotational semantics), extended to probabilistic computations, we investigate the distribution functions of probabilistic automata in detail. Automata with continuous distribution functions are characterized. By a new, and much more easier method, it is shown that the distribution function F(x) is an analytic function if it is a polynomial. Finally, answering a question posed by D. Knuth and A. Yao, we show that a polynomial distribution function F(x) on [0, 1] can be generated by a prob abilistic automaton iff all the roots of F'(x) = 0 in this interval, if any, are rational numbers. For this, we define two dynamical systems on the set of polynomial distributions and study attracting fixed points of random composition of these two systems.
A Decomposition Theorem for Finite Automata.
ERIC Educational Resources Information Center
Santa Coloma, Teresa L.; Tucci, Ralph P.
1990-01-01
Described is automata theory which is a branch of theoretical computer science. A decomposition theorem is presented that is easier than the Krohn-Rhodes theorem. Included are the definitions, the theorem, and a proof. (KR)
Linear System Control Using Stochastic Learning Automata
NASA Technical Reports Server (NTRS)
Ziyad, Nigel; Cox, E. Lucien; Chouikha, Mohamed F.
1998-01-01
This paper explains the use of a Stochastic Learning Automata (SLA) to control switching between three systems to produce the desired output response. The SLA learns the optimal choice of the damping ratio for each system to achieve a desired result. We show that the SLA can learn these states for the control of an unknown system with the proper choice of the error criteria. The results of using a single automaton are compared to using multiple automata.
Fuzzy automata and pattern matching
NASA Technical Reports Server (NTRS)
Setzer, C. B.; Warsi, N. A.
1986-01-01
A wide-ranging search for articles and books concerned with fuzzy automata and syntactic pattern recognition is presented. A number of survey articles on image processing and feature detection were included. Hough's algorithm is presented to illustrate the way in which knowledge about an image can be used to interpret the details of the image. It was found that in hand generated pictures, the algorithm worked well on following the straight lines, but had great difficulty turning corners. An algorithm was developed which produces a minimal finite automaton recognizing a given finite set of strings. One difficulty of the construction is that, in some cases, this minimal automaton is not unique for a given set of strings and a given maximum length. This algorithm compares favorably with other inference algorithms. More importantly, the algorithm produces an automaton with a rigorously described relationship to the original set of strings that does not depend on the algorithm itself.
NASA Astrophysics Data System (ADS)
Huang, He
In this thesis, I present the results of studies of the structural properties and phase transition of a charge neutral FCC Lattice Gas with Yukawa Interaction and discuss a novel fast calculation algorithm---Accelerated Cartesian Expansion (ACE) method. In the first part of my thesis, I discuss the results of Monte Carlo simulations carried out to understand the finite temperature (phase transition) properties and the ground state structure of a Yukawa Lattice Gas (YLG) model. In this model the ions interact via the potential q iqjexp(-kappar> ij)/rij where qi,j are the charges of the ions located at the lattice sites i and j with position vectors R i and Rj; rij = Ri-Rj, kappa is a measure of the range of the interaction and is called the screening parameter. This model approximates an interesting quaternary system of great current thermoelectric interest called LAST-m, AgSbPbmTem+2. I have also developed rapid calculation methods for the potential energy calculation in a lattice gas system with periodic boundary condition bases on the Ewald summation method and coded the algorithm to compute the energies in MC simulation. Some of the interesting results of the MC simulations are: (i) how the nature and strength of the phase transition depend on the range of interaction (Yukawa screening parameter kappa) (ii) what is the degeneracy of the ground state for different values of the concentration of charges, and (iii) what is the nature of two-stage disordering transition seen for certain values of x. In addition, based on the analysis of the surface energy of different nano-clusters formed near the transition temperature, the solidification process and the rate of production of these nano-clusters have been studied. In the second part of my thesis, we have developed two methods for rapidly computing potentials of the form R-nu. Both these methods are founded on addition theorems based on Taylor expansions. Taylor's series has a couple of inherent advantages: (i) it
Bus Automata For Intelligent Robots And Computer Vision
NASA Astrophysics Data System (ADS)
Rothstein, Jerome
1988-02-01
Bus automata (BA's) are arrays of automata, each controlling a module of a global interconnection network, an automaton and its module constituting a cell. Connecting modules permits cells to become effectively nearest neighbors even when widely separated. This facilitates parallelism in computation far in excess of that allowed by the "bucket-brigade" communication bottleneck of traditional cellular automata (CA's). Distributed information storage via local automaton states permits complex parallel data processing for rapid pattern recognition, language parsing and other distributed computation at systolic array rates. Global BA architecture can be entirely changed in the time to make one cell state transition. The BA is thus a neural model (cells correspond to neurons) with network plasticity attractive for brain models. Planar (chip) BA's admitting optical input (phototransistors) become powerful retinal models. The distributed input pattern is optically fed directly to distributed local memory, ready for distributed processing, both "retinally" and cooperatively with other BA chips ("brain"). This composite BA can compute control signals for output organs, and sensory inputs other than visual can be utilized similarly. In the BA retina is essentially brain, as in mammals (retina and brain are embryologically the same). The BA can also model opto-motor response (frogs, insects) or sonar response (dolphins, bats), and is proposed as the model of choice for the brains of future intelligent robots and for computer eyes with local parallel image processing capability. Multidimensional formal languages are introduced, corresponding to BA's and patterns the way generative grammars correspond to sequential machines, and applied to fractals and their recognition by BA's.
Solution of an associating lattice-gas model with density anomaly on a Husimi lattice
NASA Astrophysics Data System (ADS)
Oliveira, Tiago J.; Stilck, Jürgen F.; Barbosa, Marco Aurélio A.
2010-11-01
We study a model of a lattice gas with orientational degrees of freedom which resemble the formation of hydrogen bonds between the molecules. In this model, which is the simplified version of the Henriques-Barbosa model, no distinction is made between donors and acceptors in the bonding arms. We solve the model in the grand-canonical ensemble on a Husimi lattice built with hexagonal plaquettes with a central site. The ground state of the model, which was originally defined on the triangular lattice, is exactly reproduced by the solution on this Husimi lattice. In the phase diagram, one gas and two liquid [high density liquid (HDL) and low density liquid (LDL)] phases are present. All phase transitions (GAS-LDL, GAS-HDL, and LDL-HDL) are discontinuous, and the three phases coexist at a triple point. A line of temperatures of maximum density in the isobars is found in the metastable GAS phase, as well as another line of temperatures of minimum density appears in the LDL phase, part of it in the stable region and another in the metastable region of this phase. These findings are at variance with simulational results for the same model on the triangular lattice, which suggested a phase diagram with two critical points. However, our results show very good quantitative agreement with the simulations, both for the coexistence loci and the densities of particles and of hydrogen bonds. We discuss the comparison of the simulations with our results.
Thermal phase transitions in a honeycomb lattice gas with three-body interactions.
Lohöfer, Maximilian; Bonnes, Lars; Wessel, Stefan
2013-11-01
We study the thermal phase transitions in a classical (hard-core) lattice gas model with nearest-neighbor three-body interactions on the honeycomb lattice, based on parallel tempering Monte Carlo simulations. This system realizes incompressible low-temperature phases at fractional fillings of 9/16, 5/8, and 3/4 that were identified in a previous study of a related quantum model. In particular, both the 9/16 and the 5/8 phase exhibit an extensive ground-state degeneracy reflecting the frustrated nature of the three-body interactions on the honeycomb lattice. The thermal melting of the 9/16 phase is found to be a first-order, discontinuous phase transition. On the other hand, from the thermodynamic behavior we obtain indications for a four-states Potts-model thermal transition out of the 5/8 phase. We find that this thermal Potts-model transition relates to the selection of one out of four extensive sectors within the low-energy manifold of the 5/8 phase, which we obtain via an exact mapping of the ground-state manifold to a hard-core dimer model on an embedded honeycomb superlattice. PMID:24329242
Effect of porosity on flow of miscible fluid mixture by a lattice gas Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Cueva, Luis; Pandey, Ras; Stauffer, Dietrich; Seyfarth, Ray; Gettrust, Joe; Wood, Warren
2002-03-01
Using an interacting lattice gas model, flow of a fluid mixture through porous media is studied in three dimensions. The porous medium is generated by a random distribution of barriers (sediments) on a discrete lattice with porosity p above the percolation threshold p_c. The fluid mixture consists of constituents A and B with their mass ratios, 1, 1/2, 1/3, etc. We consider a set of interactions: AB attractive, AA and BB repulsive, A and B with pore attractive, and a hard-core interaction with the sediment barrier. A source of fluid mixture is connected to the bottom where the fluid constituents may enter the porous matrix but they can escape the system from bottom or top. The Metropolis algorithm is used to move fluid particles. While the sedimentation is caused by the gravity, the concentration gradient drives the fluid from bottom to top. The flow rate density is examined as a function of porosity and is found to scale with p-pc with a power-law exponent close to 2.
Pedestrian flow dynamics in a lattice gas model coupled with an evolutionary game.
Hao, Qing-Yi; Jiang, Rui; Hu, Mao-Bin; Jia, Bin; Wu, Qing-Song
2011-09-01
This paper studies unidirectional pedestrian flow by using a lattice gas model with parallel update rules. Game theory is introduced to deal with conflicts that two or three pedestrians want to move into the same site. Pedestrians are either cooperators or defectors. The cooperators are gentle and the defectors are aggressive. Moreover, pedestrians could change their strategy. The fundamental diagram and the cooperator fraction at different system width W have been investigated in detail. It is found that a two-lane system exhibits a first-order phase transition while a multilane system does not. A microscopic mechanism behind the transition has been provided. Mean-field analysis is carried out to calculate the critical density of the transition as well as the probability of games at large value of W. The spatial distribution of pedestrians is investigated, which is found to be dependent (independent) on the initial cooperator fraction when W is small (large). Finally, the influence of the evolutionary game rule has been discussed. PMID:22060456
Multiple phase transitions in extended hard-core lattice gas models in two dimensions.
Nath, Trisha; Rajesh, R
2014-07-01
We study the k-NN hard-core lattice gas model in which the first k next-nearest-neighbor sites of a particle are excluded from occupation by other particles on a two-dimensional square lattice. This model is the lattice version of the hard-disk system with increasing k corresponding to decreasing lattice spacing. While the hard-disk system is known to undergo a two-step freezing process with increasing density, the lattice model has been known to show only one transition. Here, based on Monte Carlo simulations and high-density expansions of the free energy and density, we argue that for k = 4,10,11,14,⋯, the lattice model undergoes multiple transitions with increasing density. Using Monte Carlo simulations, we confirm the same for k = 4,...,11. This, in turn, resolves an existing puzzle as to why the 4-NN model has a continuous transition against the expectation of a first-order transition. PMID:25122264
Entanglement Properties of a Quantum Lattice-Gas Model on Square and Triangular Ladders
NASA Astrophysics Data System (ADS)
Tanaka, Shu; Tamura, Ryo; Katsura, Hosho
2014-03-01
In this paper, we review the entanglement properties of a quantum lattice-gas model according to our previous paper [S. Tanaka, R. Tamura, and H. Katsura, Phys. Rev. A 86, 032326 (2012)]. The ground state of the model under consideration can be exactly obtained and expressed by the Rokhsar-Kivelson type quantum superposition. The reduced density matrices of the model on square and triangular ladders are related to the transfer matrices of the classical hard-square and hard-hexagon models, respectively. In our previous paper, we investigated the entanglement properties including the entanglement entropy, the entanglement spectrum, and the nested entanglement entropy. We found that the entanglement spectra are critical when parameters are chosen so that the corresponding classical model is critical. In order to further investigate the entanglement properties, we also considered the nested entanglement entropy. As a result, the entanglement properties of the model on square and triangular ladders are described by the critical phenomena of the Ising model and the three-state ferromagnetic Potts model in two dimension, respectively.
Velocity and density profiles of granular flow in channels using a lattice gas automaton
Peng, G.; Ohta, T.
1997-06-01
We have performed two-dimensional lattice-gas-automaton simulations of granular flow between two parallel planes. We find that the velocity profiles have nonparabolic distributions, while simultaneously the density profiles are nonuniform. Under nonslip boundary conditions, deviation of velocity profiles from the parabolic form of Newtonian fluids is found to be characterized solely by ratio of maximal velocity at the center to the average velocity, though the ratio depends on the model parameters in a complex manner. We also find that the maximal velocity (u{sub max}) at the center is a linear function of the driving force (g) as u{sub max}={alpha}g{minus}{delta} with nonzero {delta} in contrast with Newtonian fluids. Regarding density profiles, we observe that densities near the boundaries are higher than those in the center. The width of higher densities (above the average density) relative to the channel width is a decreasing function of a variable which scales with the driving force (g), energy dissipation parameter ({epsilon}), and the width of the system (L) as g{sup {mu}}L{sup {nu}}/{epsilon} with exponents {mu}=1.4{plus_minus}0.1 and {nu}=0.5{plus_minus}0.1. A phenomenological theory based on a scaling argument is presented to interpret these findings. {copyright} {ital 1997} {ital The American Physical Society}
NASA Astrophysics Data System (ADS)
Martín Del Rey, A.; Rodríguez Sánchez, G.
2015-03-01
The study of the reversibility of elementary cellular automata with rule number 150 over the finite state set 𝔽p and endowed with periodic boundary conditions is done. The dynamic of such discrete dynamical systems is characterized by means of characteristic circulant matrices, and their analysis allows us to state that the reversibility depends on the number of cells of the cellular space and to explicitly compute the corresponding inverse cellular automata.
Lee, Sang Bub
2015-12-01
The absorbing phase transition of the modified conserved lattice gas (m-CLG) model was investigated in one dimension. The m-CLG model was modified from the conserved lattice gas (CLG) model in such a way that each active particle hops to one of the nearest-neighbor and next-nearest-neighbor empty sites. The order parameter exponent, the dynamic exponent, and the correlation length exponent were estimated from the power-law behavior and finite-size scaling of the active particle densities. The exponents were found to differ considerably from those of the ordinary CLG model and were also distinct from those of the Manna model, suggesting that next-nearest-neighbor hopping is a relevant factor that alters the critical behavior in the one-dimensional CLG model. PMID:26764627
Exploiting the features of the finite state automata for biomolecular computing.
Martínez-Pérez, Israel Marck; Ignatova, Zoya; Zimmermann, Karl-Heinz
2009-01-01
Here, we review patents that have emerged in the field of DNA-based computing focusing thereby on the discoveries using the concept of molecular finite state automata. A finite state automaton, operating on a finite sequence of symbols and converting information from one to another, provides a basis for developing molecular-scale autonomous programmable models of biomolecular computation at cellular level. We also provide a brief overview on inventions which methodologically support the DNA-based computational approach. PMID:19519583
Varieties of learning automata: an overview.
Thathachar, M L; Sastry, P S
2002-01-01
Automata models of learning systems introduced in the 1960s were popularized as learning automata (LA) in a survey paper by Narendra and Thathachar (1974). Since then, there have been many fundamental advances in the theory as well as applications of these learning models. In the past few years, the structure of LA, has been modified in several directions to suit different applications. Concepts such as parameterized learning automata (PLA), generalized learning,automata (GLA), and continuous action-set learning automata (CALA) have been proposed, analyzed, and applied to solve many significant learning problems. Furthermore, groups of LA forming teams and feedforward networks have been shown to converge to desired solutions under appropriate learning algorithms. Modules of LA have been used for parallel operation with consequent increase in speed of convergence. All of these concepts and results are relatively new and are scattered in technical literature. An attempt has been made in this paper to bring together the main ideas involved in a unified framework and provide pointers to relevant references. PMID:18244878
Automata in random environments with application to machine intelligence
Wegman, E.J.; Gould, J.
1982-09-01
Computers and brains are modeled by finite and probabilistic automata, respectively. Probabilistic automata are known to be strictly more powerful than finite automata. The observation that the environment affects behavior of both computer and brain is made. Automata are then modeled in an environment. Theorem 1 shows that useful environmental models are those which are infinite sets. A probabilistic structure is placed on the environment set. Theorem 2 compares the behavior of finite (deterministic) and probabilistic automata in random environments. Several interpretations of theorem 2 are discussed which offer some insight into some mathematical limits of machine intelligence. 15 references.
Monte Carlo tests of nucleation concepts in the lattice gas model
NASA Astrophysics Data System (ADS)
Schmitz, Fabian; Virnau, Peter; Binder, Kurt
2013-05-01
The conventional theory of homogeneous and heterogeneous nucleation in a supersaturated vapor is tested by Monte Carlo simulations of the lattice gas (Ising) model with nearest-neighbor attractive interactions on the simple cubic lattice. The theory considers the nucleation process as a slow (quasistatic) cluster (droplet) growth over a free energy barrier ΔF*, constructed in terms of a balance of surface and bulk term of a critical droplet of radius R*, implying that the rates of droplet growth and shrinking essentially balance each other for droplet radius R=R*. For heterogeneous nucleation at surfaces, the barrier is reduced by a factor depending on the contact angle. Using the definition of physical clusters based on the Fortuin-Kasteleyn mapping, the time dependence of the cluster size distribution is studied for quenching experiments in the kinetic Ising model and the cluster size ℓ* where the cluster growth rate changes sign is estimated. These studies of nucleation kinetics are compared to studies where the relation between cluster size and supersaturation is estimated from equilibrium simulations of phase coexistence between droplet and vapor in the canonical ensemble. The chemical potential is estimated from a lattice version of the Widom particle insertion method. For large droplets it is shown that the physical clusters have a volume consistent with the estimates from the lever rule. Geometrical clusters (defined such that each site belonging to the cluster is occupied and has at least one occupied neighbor site) yield valid results only for temperatures less than 60% of the critical temperature, where the cluster shape is nonspherical. We show how the chemical potential can be used to numerically estimate ΔF* also for nonspherical cluster shapes.
Modelling and synthesis of automata in HDLs
NASA Astrophysics Data System (ADS)
Chmielewski, Sławomir; Węgrzyn, Marek
2006-10-01
In the paper digital modelling and synthesis of automata in Hardware Description Languages is described. There is presented different kinds of automata and methods of realization using languages like VHDL and Verilog. Basic models for control units are: Finite State Machine (FSM), Algorithmic State Machine (ASM) and Linked State Machine (LSM). FSM, ASM and LSM can be represented graphically, which would help a designer to visualize and design in a more efficient way. On the other hand, a designer needs a fast and direct way to convert the considered designs into Hardware Description Language (HDL) codes for simulation and analysis it for synthesis and implementation.
Automata theory. 1964-May 1983 (Citations from the NTIS Data Base)
Not Available
1983-06-01
Research reports are cited on pushdown automata, tessellation automata, web automata, and finite state automata. Studies on finite state machines, turing machines, and sequential machines are included. Research on Boolean functions, recursive functions, the Moore model, and the Mealey model, as applied to automata theory, are also covered. (This updated bibliography contains 298 citations, 41 of which are new entries to the previous edition.)
Partial Derivative Automata Formalized in Coq
NASA Astrophysics Data System (ADS)
Almeida, José Bacelar; Moreira, Nelma; Pereira, David; de Sousa, Simão Melo
In this paper we present a computer assisted proof of the correctness of a partial derivative automata construction from a regular expression within the Coq proof assistant. This proof is part of a formalization of Kleene algebra and regular languages in Coq towards their usage in program certification.
Fuzzy tree automata and syntactic pattern recognition.
Lee, E T
1982-04-01
An approach of representing patterns by trees and processing these trees by fuzzy tree automata is described. Fuzzy tree automata are defined and investigated. The results include that the class of fuzzy root-to-frontier recognizable ¿-trees is closed under intersection, union, and complementation. Thus, the class of fuzzy root-to-frontier recognizable ¿-trees forms a Boolean algebra. Fuzzy tree automata are applied to processing fuzzy tree representation of patterns based on syntactic pattern recognition. The grade of acceptance is defined and investigated. Quantitative measures of ``approximate isosceles triangle,'' ``approximate elongated isosceles triangle,'' ``approximate rectangle,'' and ``approximate cross'' are defined and used in the illustrative examples of this approach. By using these quantitative measures, a house, a house with high roof, and a church are also presented as illustrative examples. In addition, three fuzzy tree automata are constructed which have the capability of processing the fuzzy tree representations of ``fuzzy houses,'' ``houses with high roofs,'' and ``fuzzy churches,'' respectively. The results may have useful applications in pattern recognition, image processing, artificial intelligence, pattern database design and processing, image science, and pictorial information systems. PMID:21869062
Evolution of cooperation in Axelrod tournament using cellular automata
NASA Astrophysics Data System (ADS)
Schimit, P. H. T.; Santos, B. O.; Soares, C. A.
2015-11-01
Results of the Axelrod Tournament were published in 1981, and since then, evolutionary game theory emerged as an idea for understanding relations, like conflict and cooperation, between rational decision-makers. Robert Axelrod organized it as a round-robin tournament where strategies for iterated Prisoner's Dilemma were faced in a sequence of two players game. Here, we attempt to simulate the strategies submitted to the tournament in a multi-agent context, where individuals play a two-player game with their neighbors. Each individual has one of the strategies, and it plays the Prisoner's Dilemma with its neighbors. According to actions chosen (cooperate or defect), points of life are subtracted from their profiles. When an individual dies, some fitness functions are defined to choose the most successful strategy which the new individual will copy. Although tit-for-tat was the best strategy, on average, in the tournament, in our evolutionary multi-agent context, it has not been successful.
Application of cellular automata approach for cloud simulation and rendering
Christopher Immanuel, W.; Paul Mary Deborrah, S.; Samuel Selvaraj, R.
2014-03-15
Current techniques for creating clouds in games and other real time applications produce static, homogenous clouds. These clouds, while viable for real time applications, do not exhibit an organic feel that clouds in nature exhibit. These clouds, when viewed over a time period, were able to deform their initial shape and move in a more organic and dynamic way. With cloud shape technology we should be able in the future to extend to create even more cloud shapes in real time with more forces. Clouds are an essential part of any computer model of a landscape or an animation of an outdoor scene. A realistic animation of clouds is also important for creating scenes for flight simulators, movies, games, and other. Our goal was to create a realistic animation of clouds.
Multifractal analyses of row sum signals of elementary cellular automata
NASA Astrophysics Data System (ADS)
Murguía, J. S.; Rosu, H. C.
2012-07-01
We first apply the WT-MFDFA, MFDFA, and WTMM multifractal methods to binomial multifractal time series of three different binomial parameters and find that the WTMM method indicates an enhanced difference between the fractal components than the known theoretical result. Next, we make use of the same methods for the time series of the row sum signals of the two complementary ECA pairs of rules (90,165) and (150,105) for ten initial conditions going from a single 1 in the central position up to a set of ten 1's covering the ten central positions in the first row. Since the members of the pairs are actually similar from the statistical point of view, we can check which method is the most stable numerically by recording the differences provided by the methods between the two members of the pairs for various important quantities of the scaling analyses, such as the multifractal support, the most frequent Hölder exponent, and the Hurst exponent and considering as the better one the method that provides the minimum differences. According to this criterion, our results show that the MFDFA performs better than WT-MFDFA and WTMM in the case of the multifractal support, while for the other two scaling parameters the WT-MFDFA is the best. The employed set of initial conditions does not generate any specific trend in the values of the multifractal parameters.
Application of Cellular Automata to Detection of Malicious Network Packets
ERIC Educational Resources Information Center
Brown, Robert L.
2014-01-01
A problem in computer security is identification of attack signatures in network packets. An attack signature is a pattern of bits that characterizes a particular attack. Because there are many kinds of attacks, there are potentially many attack signatures. Furthermore, attackers may seek to avoid detection by altering the attack mechanism so that…
The Use of Cellular Automata in the Learning of Emergence
ERIC Educational Resources Information Center
Faraco, G.; Pantano, P.; Servidio, R.
2006-01-01
In recent years, research efforts on complex systems have contributed to improve our ability in investigating, at different levels of complexity, the emergent behaviour shown by a system in the course of its evolution. The study of emergence, an intrinsic property of a large number of complex systems, can be tackled by making use of Cellular…
Traffic Behavior around the Weaving Section in Cellular Automata Model
NASA Astrophysics Data System (ADS)
Jia, Bin; Li, Xin-Gang; Jiang, Rui; Gao, Zi-You
In this paper, the traffic behavior around the weaving section, in which an on-ramp and an off-ramp are joined together by an auxiliary lane, is investigated. The drive-in vehicle should merge into the main road while the exit vehicle should diverge from the main road. The influence of those merging and diverging behavior on the dynamics of traffic around the weaving section is studied by analyzing the phase diagram in different spaces and the total flux depending on each parameter. When the number of drive-in vehicle and the number of exit vehicle are close to each other, the total flux is less disturbed. But when they have large difference, the total flux is greatly reduced. We also studied the total flux as a function of the length of the weaving section. It is shown that the weaving section should not be shorter than 150 m.
Solving multiconstraint assignment problems using learning automata.
Horn, Geir; Oommen, B John
2010-02-01
This paper considers the NP-hard problem of object assignment with respect to multiple constraints: assigning a set of elements (or objects) into mutually exclusive classes (or groups), where the elements which are "similar" to each other are hopefully located in the same class. The literature reports solutions in which the similarity constraint consists of a single index that is inappropriate for the type of multiconstraint problems considered here and where the constraints could simultaneously be contradictory. This feature, where we permit possibly contradictory constraints, distinguishes this paper from the state of the art. Indeed, we are aware of no learning automata (or other heuristic) solutions which solve this problem in its most general setting. Such a scenario is illustrated with the static mapping problem, which consists of distributing the processes of a parallel application onto a set of computing nodes. This is a classical and yet very important problem within the areas of parallel computing, grid computing, and cloud computing. We have developed four learning-automata (LA)-based algorithms to solve this problem: First, a fixed-structure stochastic automata algorithm is presented, where the processes try to form pairs to go onto the same node. This algorithm solves the problem, although it requires some centralized coordination. As it is desirable to avoid centralized control, we subsequently present three different variable-structure stochastic automata (VSSA) algorithms, which have superior partitioning properties in certain settings, although they forfeit some of the scalability features of the fixed-structure algorithm. All three VSSA algorithms model the processes as automata having first the hosting nodes as possible actions; second, the processes as possible actions; and, third, attempting to estimate the process communication digraph prior to probabilistically mapping the processes. This paper, which, we believe, comprehensively reports the
A Quantum Relativistic Prisoner's Dilemma Cellular Automaton
NASA Astrophysics Data System (ADS)
Alonso-Sanz, Ramón; Carvalho, Márcio; Situ, Haozhen
2016-06-01
The effect of variable entangling on the dynamics of a spatial quantum relativistic formulation of the iterated prisoner's dilemma game is studied in this work. The game is played in the cellular automata manner, i.e., with local and synchronous interaction. The game is assessed in fair and unfair contests.
Fonk, Y.; Hilhorst, H.J.
1987-12-01
The authors determine the zero-temperature properties of a one-dimensional lattice gas of particles that interact via a nearest neighbor exclusion potential and are subject to a random external field. The model is a special limiting case of the random field Ising chain. We calculate (1) the energy and density of the ground state as well as the local energy-density correlation and (2) the pair correlation function. The latter calculation gives access to all higher order correlations. The structure factor is shown to be a squared Lorentzian. The authors also compare the ground state to the quenched state obtained by sequentially filling the lowest available energy levels.
Cellular automaton for chimera states
NASA Astrophysics Data System (ADS)
García-Morales, Vladimir
2016-04-01
A minimalistic model for chimera states is presented. The model is a cellular automaton (CA) which depends on only one adjustable parameter, the range of the nonlocal coupling, and is built from elementary cellular automata and the majority (voting) rule. This suggests the universality of chimera-like behavior from a new point of view: Already simple CA rules based on the majority rule exhibit this behavior. After a short transient, we find chimera states for arbitrary initial conditions, the system spontaneously splitting into stable domains separated by static boundaries, some synchronously oscillating and the others incoherent. When the coupling range is local, nontrivial coherent structures with different periodicities are formed.
Liu, Da-Jiang; Evans, J W
2006-04-21
We have developed an atomistic lattice-gas model for the catalytic oxidation of CO on single-crystal Pd(100) surfaces under ultrahigh vacuum conditions. This model necessarily incorporates an detailed description of adlayer ordering and adsorption-desorption kinetics both for CO on Pd(100), and for oxygen on Pd(100). Relevant energetic parameters are determined by comparing model predictions with experiment, together with some guidance from density functional theory calculations. The latter also facilitates description of the interaction and reaction of adsorbed CO and oxygen. Kinetic Monte Carlo simulations of this reaction model are performed to predict temperature-programmed reaction spectra, as well as steady-state bifurcation behavior. PMID:16674249
Probabilistic arithmetic automata and their applications.
Marschall, Tobias; Herms, Inke; Kaltenbach, Hans-Michael; Rahmann, Sven
2012-01-01
We present a comprehensive review on probabilistic arithmetic automata (PAAs), a general model to describe chains of operations whose operands depend on chance, along with two algorithms to numerically compute the distribution of the results of such probabilistic calculations. PAAs provide a unifying framework to approach many problems arising in computational biology and elsewhere. We present five different applications, namely 1) pattern matching statistics on random texts, including the computation of the distribution of occurrence counts, waiting times, and clump sizes under hidden Markov background models; 2) exact analysis of window-based pattern matching algorithms; 3) sensitivity of filtration seeds used to detect candidate sequence alignments; 4) length and mass statistics of peptide fragments resulting from enzymatic cleavage reactions; and 5) read length statistics of 454 and IonTorrent sequencing reads. The diversity of these applications indicates the flexibility and unifying character of the presented framework. While the construction of a PAA depends on the particular application, we single out a frequently applicable construction method: We introduce deterministic arithmetic automata (DAAs) to model deterministic calculations on sequences, and demonstrate how to construct a PAA from a given DAA and a finite-memory random text model. This procedure is used for all five discussed applications and greatly simplifies the construction of PAAs. Implementations are available as part of the MoSDi package. Its application programming interface facilitates the rapid development of new applications based on the PAA framework. PMID:22868683
Automata-Based Verification of Temporal Properties on Running Programs
NASA Technical Reports Server (NTRS)
Giannakopoulou, Dimitra; Havelund, Klaus; Lan, Sonie (Technical Monitor)
2001-01-01
This paper presents an approach to checking a running program against its Linear Temporal Logic (LTL) specifications. LTL is a widely used logic for expressing properties of programs viewed as sets of executions. Our approach consists of translating LTL formulae to finite-state automata, which are used as observers of the program behavior. The translation algorithm we propose modifies standard LTL to Buchi automata conversion techniques to generate automata that check finite program traces. The algorithm has been implemented in a tool, which has been integrated with the generic JPaX framework for runtime analysis of Java programs.
A simplified cellular automation model for city traffic
Simon, P.M.; Nagel, K. |
1997-12-31
The authors systematically investigate the effect of blockage sites in a cellular automata model for traffic flow. Different scheduling schemes for the blockage sites are considered. None of them returns a linear relationship between the fraction of green time and the throughput. The authors use this information for a fast implementation of traffic in Dallas.
Viewing hybrid systems as products of control systems and automata
NASA Technical Reports Server (NTRS)
Grossman, R. L.; Larson, R. G.
1992-01-01
The purpose of this note is to show how hybrid systems may be modeled as products of nonlinear control systems and finite state automata. By a hybrid system, we mean a network of consisting of continuous, nonlinear control system connected to discrete, finite state automata. Our point of view is that the automata switches between the control systems, and that this switching is a function of the discrete input symbols or letters that it receives. We show how a nonlinear control system may be viewed as a pair consisting of a bialgebra of operators coding the dynamics, and an algebra of observations coding the state space. We also show that a finite automata has a similar representation. A hybrid system is then modeled by taking suitable products of the bialgebras coding the dynamics and the observation algebras coding the state spaces.
NASA Astrophysics Data System (ADS)
Lee, Sang Bub
2014-06-01
The conserved lattice gas model in one dimension, generated from various initial states, was intensively studied. The dynamic critical exponents α and ν║ associated with the decay of activeparticle densities and the correlation time, respectively, were found to depend drastically on the initial states. The perfectly-ordered initial state prepared by repeatedly placing the block `0011' yielded a standard critical behavior, with the critical exponents satisfying all the scaling relations. On the other hand, the natural initial states and the ordered initial states of blocks of odd numbers of particles yielded an exponent α slightly larger than that of an ordered state of `0011', but the data for active-particle densities did not satisfy scaling function. The exponents α and ν║ were also calculated from, respectively, the autocorrelation function and the persistence distribution of the active-particle densities, both in the steady states. The value of α was found to be close to the value for an ordered state of `0011' whereas the value of ν║ was consistent with that for the random initial states.
NASA Astrophysics Data System (ADS)
Frank, Stefan; Roberts, Daniel E.; Rikvold, Per Arne
2005-02-01
The influence of nearest-neighbor diffusion on the decay of a metastable low-coverage phase (monolayer adsorption) in a square lattice-gas model of electrochemical metal deposition is investigated by kinetic Monte Carlo simulations. The phase-transformation dynamics are compared to the well-established Kolmogorov-Johnson-Mehl-Avrami theory. The phase transformation is accelerated by diffusion, but remains in accord with the theory for continuous nucleation up to moderate diffusion rates. At very high diffusion rates the phase-transformation kinetic shows a crossover to instantaneous nucleation. Then, the probability of medium-sized clusters is reduced in favor of large clusters. Upon reversal of the supersaturation, the adsorbate desorbs, but large clusters still tend to grow during the initial stages of desorption. Calculation of the free energy of subcritical clusters by enumeration of lattice animals yields a quasiequilibrium distribution which is in reasonable agreement with the simulation results. This is an improvement relative to classical droplet theory, which fails to describe the distributions, since the macroscopic surface tension is a bad approximation for small clusters.
On Matrices, Automata, and Double Counting
NASA Astrophysics Data System (ADS)
Beldiceanu, Nicolas; Carlsson, Mats; Flener, Pierre; Pearson, Justin
Matrix models are ubiquitous for constraint problems. Many such problems have a matrix of variables M, with the same constraint defined by a finite-state automaton A on each row of M and a global cardinality constraint gcc on each column of M. We give two methods for deriving, by double counting, necessary conditions on the cardinality variables of the gcc constraints from the automaton A. The first method yields linear necessary conditions and simple arithmetic constraints. The second method introduces the cardinality automaton, which abstracts the overall behaviour of all the row automata and can be encoded by a set of linear constraints. We evaluate the impact of our methods on a large set of nurse rostering problem instances.
Elton, A.B.H.
1990-09-24
A numerical theory for the massively parallel lattice gas and lattice Boltzmann methods for computing solutions to nonlinear advective-diffusive systems is introduced. The convergence theory is based on consistency and stability arguments that are supported by the discrete Chapman-Enskog expansion (for consistency) and conditions of monotonicity (in establishing stability). The theory is applied to four lattice methods: Two of the methods are for some two-dimensional nonlinear diffusion equations. One of the methods is for the one-dimensional lattice method for the one-dimensional viscous Burgers equation. And one of the methods is for a two-dimensional nonlinear advection-diffusion equation. Convergence is formally proven in the L{sub 1}-norm for the first three methods, revealing that they are second-order, conservative, conditionally monotone finite difference methods. Computational results which support the theory for lattice methods are presented. In addition, a domain decomposition strategy using mesh refinement techniques is presented for lattice gas and lattice Boltzmann methods. The strategy allows concentration of computational resources on regions of high activity. Computational evidence is reported for the strategy applied to the lattice gas method for the one-dimensional viscous Burgers equation. 72 refs., 19 figs., 28 tabs.
PAM: Particle automata model in simulation of Fusarium graminearum pathogen expansion.
Wcisło, Rafał; Miller, S Shea; Dzwinel, Witold
2016-01-21
The multi-scale nature and inherent complexity of biological systems are a great challenge for computer modeling and classical modeling paradigms. We present a novel particle automata modeling metaphor in the context of developing a 3D model of Fusarium graminearum infection in wheat. The system consisting of the host plant and Fusarium pathogen cells can be represented by an ensemble of discrete particles defined by a set of attributes. The cells-particles can interact with each other mimicking mechanical resistance of the cell walls and cell coalescence. The particles can move, while some of their attributes can be changed according to prescribed rules. The rules can represent cellular scales of a complex system, while the integrated particle automata model (PAM) simulates its overall multi-scale behavior. We show that due to the ability of mimicking mechanical interactions of Fusarium tip cells with the host tissue, the model is able to simulate realistic penetration properties of the colonization process reproducing both vertical and lateral Fusarium invasion scenarios. The comparison of simulation results with micrographs from laboratory experiments shows encouraging qualitative agreement between the two. PMID:26549468
NASA Astrophysics Data System (ADS)
Cox, Brian N.; Snead, Malcolm L.
2016-02-01
We argue in favor of representing living cells as automata and review demonstrations that autonomous cells can form patterns by responding to local variations in the strain fields that arise from their individual or collective motions. An autonomous cell's response to strain stimuli is assumed to be effected by internally-generated, internally-powered forces, which generally move the cell in directions other than those implied by external energy gradients. Evidence of cells acting as strain-cued automata have been inferred from patterns observed in nature and from experiments conducted in vitro. Simulations that mimic particular cases of pattern forming share the idealization that cells are assumed to pass information among themselves solely via mechanical boundary conditions, i.e., the tractions and displacements present at their membranes. This assumption opens three mechanisms for pattern formation in large cell populations: wavelike behavior, kinematic feedback in cell motility that can lead to sliding and rotational patterns, and directed migration during invasions. Wavelike behavior among ameloblast cells during amelogenesis (the formation of dental enamel) has been inferred from enamel microstructure, while strain waves in populations of epithelial cells have been observed in vitro. One hypothesized kinematic feedback mechanism, "enhanced shear motility", accounts successfully for the spontaneous formation of layered patterns during amelogenesis in the mouse incisor. Directed migration is exemplified by a theory of invader cells that sense and respond to the strains they themselves create in the host population as they invade it: analysis shows that the strain fields contain positional information that could aid the formation of cell network structures, stabilizing the slender geometry of branches and helping govern the frequency of branch bifurcation and branch coalescence (the formation of closed networks). In simulations of pattern formation in
Efficient Translation of LTL Formulae into Buchi Automata
NASA Technical Reports Server (NTRS)
Giannakopoulou, Dimitra; Lerda, Flavio
2001-01-01
Model checking is a fully automated technique for checking that a system satisfies a set of required properties. With explicit-state model checkers, properties are typically defined in linear-time temporal logic (LTL), and are translated into B chi automata in order to be checked. This report presents how we have combined and improved existing techniques to obtain an efficient LTL to B chi automata translator. In particular, we optimize the core of existing tableau-based approaches to generate significantly smaller automata. Our approach has been implemented and is being released as part of the Java PathFinder software (JPF), an explicit state model checker under development at the NASA Ames Research Center.
On the applications of multiplicity automata in learning
Beimel, A.; Bergadano, F.; Bshouty, N.H.
1996-12-31
Recently the learnability of multiplicity automata attracted a lot of attention, mainly because of its implications on the learnability of several classes of DNF formulae. In this paper we further study the learnability of multiplicity automata. Our starting point is a known theorem from automata theory relating the number of states in a minimal multiplicity automaton for a function f to the rank of a certain matrix F. With this theorem in hand we obtain the following results: (1) A new simple algorithm for learning multiplicity automata in the spirit with a better query complexity. As a result, we improve the complexity for all classes that use the algorithms of and also obtain the best query complexity for several classes known to be learnable by other methods such as decision trees and polynomials over GF(2). (2) We prove the learnability of some new classes that were not known to be learnable before. Most notably, the class of polynomials over finite fields, the class of bounded-degree polynomials over infinite fields, the class of XOR of terms, and a certain class of decision-trees. (3) While multiplicity automata were shown to be useful to prove the learnability of some subclasses of DNF formulae and various other classes, we study the limitations of this method. We prove that this method cannot be used to resolve the learnability of some other open problems such as the learnability of general DNF formulae or even k -term DNF for k = {omega}(log n) or satisfy-s DNF formulae for s = {omega}(1). These results are proven by exhibiting functions in the above classes that require multiplicity automata with superpolynomial number of states.
Gunji, Y; Nakamura, T
1991-01-01
In the present paper the self-consistency or operational closure of autopoiesis is described by introducing time explicitly. It is an extension of Spencer-Brown's idea of time, however. The definition of time is segregated into two parts, corresponding to the syntax and semantics of language, respectively. In this context, time reversibility is defined by the formalization of the relationship between time and self-consistency. This idea has also been discussed in the context of designation and/or naming. Here we will discuss it in the context of cellular automata and explain the structure of one-to-many type mappings. Our approach is the first attempt to extend autopoietic systems in terms of dynamics. It illustrates how to introduce an autopoietic time which looks irreversible, but without the concept of entropy. PMID:1912385
Comprehensive bidding strategies with genetic programming/finite state automata
Richter, C.W. Jr.; Sheble, G.B.; Ashlock, D.
1999-11-01
This research is an extension of the authors' previous work in double auctions aimed at developing bidding strategies for electric utilities which trade electricity competitively. The improvements detailed in this paper come from using data structures which combine genetic programming and finite state automata termed GP-Automata. The strategies developed by the method described here are adaptive--reacting to inputs--whereas the previously developed strategies were only suitable in the particular scenario for which they had been designed. The strategies encoded in the GP-Automata are tested in an auction simulator. The simulator pits them against other distribution companies (distcos) and generation companies (gencos), buying and selling power via double auctions implemented in regional commodity exchanges. The GP-Automata are evolved with a genetic algorithm so that they possess certain characteristics. In addition to designing successful bidding strategies (whose usage would result in higher profits) the resulting strategies can also be designed to imitate certain types of trading behaviors. The resulting strategies can be implemented directly in on-line trading, or can be used as realistic competitors in an off-line trading simulator.
On a three-parameter quantum battle of the sexes cellular automaton
NASA Astrophysics Data System (ADS)
Alonso-Sanz, Ramón
2013-05-01
The dynamics of a spatial quantum formulation of the iterated battle of the sexes game is studied in this work. The game is played in the cellular automata manner, i.e., with local and synchronous interaction. The effect of spatial structure is assessed when allowing the players to adopt quantum strategies that are no restricted to any particular subset of the possible strategies.
A cellular automaton implementation of a quantum battle of the sexes game with imperfect information
NASA Astrophysics Data System (ADS)
Alonso-Sanz, Ramón
2015-10-01
The dynamics of a spatial quantum formulation of the iterated battle of the sexes game with imperfect information is studied in this work. The game is played with variable entangling in a cellular automata manner, i.e. with local and synchronous interaction. The effect of spatial structure is assessed in fair and unfair scenarios.
A SIMPLE CELLULAR AUTOMATON MODEL FOR HIGH-LEVEL VEGETATION DYNAMICS
We have produced a simple two-dimensional (ground-plan) cellular automata model of vegetation dynamics specifically to investigate high-level community processes. The model is probabilistic, with individual plant behavior determined by physiologically-based rules derived from a w...
NASA Astrophysics Data System (ADS)
Yepez, J.; Vahala, G.; Vahala, L.
2009-04-01
Presented is a type-II quantum algorithm for superfluid dynamics, used to numerically predict solutions of the GP equation for a complex scalar field (spinless bosons) in φ4 theory. The GP equation is a long wavelength effective field theory of a microscopic quantum lattice gas with nonlinear state reduction. The quantum lattice gas algorithm for modeling the dynamics of the one-body BEC state in 3+1 dimensions is presented. To demonstrate the method's strength as a computational physics tool, a difficult situation of filamentary singularities is simulated, the dynamics of solitary vortex-antivortex pairs, which are a basic building block of morphologies of quantum turbulence.
Abductive learning of quantized stochastic processes with probabilistic finite automata.
Chattopadhyay, Ishanu; Lipson, Hod
2013-02-13
We present an unsupervised learning algorithm (GenESeSS) to infer the causal structure of quantized stochastic processes, defined as stochastic dynamical systems evolving over discrete time, and producing quantized observations. Assuming ergodicity and stationarity, GenESeSS infers probabilistic finite state automata models from a sufficiently long observed trace. Our approach is abductive; attempting to infer a simple hypothesis, consistent with observations and modelling framework that essentially fixes the hypothesis class. The probabilistic automata we infer have no initial and terminal states, have no structural restrictions and are shown to be probably approximately correct-learnable. Additionally, we establish rigorous performance guarantees and data requirements, and show that GenESeSS correctly infers long-range dependencies. Modelling and prediction examples on simulated and real data establish relevance to automated inference of causal stochastic structures underlying complex physical phenomena. PMID:23277601
On the secure obfuscation of deterministic finite automata.
Anderson, William Erik
2008-06-01
In this paper, we show how to construct secure obfuscation for Deterministic Finite Automata, assuming non-uniformly strong one-way functions exist. We revisit the software protection approaches originally proposed by [5, 10, 12, 17] and revise them to the current obfuscation setting of Barak et al. [2]. Under this model, we introduce an efficient oracle that retains some 'small' secret about the original program. Using this secret, we can construct an obfuscator and two-party protocol that securely obfuscates Deterministic Finite Automata against malicious adversaries. The security of this model retains the strong 'virtual black box' property originally proposed in [2] while incorporating the stronger condition of dependent auxiliary inputs in [15]. Additionally, we show that our techniques remain secure under concurrent self-composition with adaptive inputs and that Turing machines are obfuscatable under this model.
Relational String Verification Using Multi-track Automata
NASA Astrophysics Data System (ADS)
Yu, Fang; Bultan, Tevfik; Ibarra, Oscar H.
Verification of string manipulation operations is a crucial problem in computer security. In this paper, we present a new relational string verification technique based on multi-track automata. Our approach is capable of verifying properties that depend on relations among string variables. This enables us to prove that vulnerabilities that result from improper string manipulation do not exist in a given program. Our main contributions in this paper can be summarized as follows: (1) We formally characterize the string verification problem as the reachability analysis of string systems and show decidability/undecidability results for several string analysis problems. (2) We develop a sound symbolic analysis technique for string verification that over-approximates the reachable states of a given string system using multi-track automata and summarization. (3) We evaluate the presented techniques with respect to several string analysis benchmarks extracted from real web applications.
Automata-theoretic models of mutation and alignment
Searls, D.B.; Murphy, K.P.
1995-12-31
Finite-state automata called transducers, which have both input and output, can be used to model simple mechanisms of biological mutation. We present a methodology whereby numerically-weighted versions of such specifications can be mechanically adapted to create string edit machines that are essentially equivalent to recurrence relations of the sort that characterize dynamic programming alignment algorithms. Based on this, we have developed a visual programming system for designing new alignment algorithms in a rapid-prototyping fashion.
An autonomous DNA model for finite state automata.
Martinez-Perez, Israel M; Zimmermann, Karl-Heinz; Ignatova, Zoya
2009-01-01
In this paper we introduce an autonomous DNA model for finite state automata. This model called sticker automaton model is based on the hybridisation of single stranded DNA molecules (stickers) encoding transition rules and input data. The computation is carried out in an autonomous manner by one enzyme which allows us to determine whether a resulting double-stranded DNA molecule belongs to the automaton's language or not. PMID:19136366
Supervisory control of (max,+) automata: extensions towards applications
NASA Astrophysics Data System (ADS)
Lahaye, Sébastien; Komenda, Jan; Boimond, Jean-Louis
2015-12-01
In this paper, supervisory control of (max,+) automata is studied. The synthesis of maximally permissive and just-in-time supervisor, as well as the synthesis of minimally permissive and just-after-time supervisor, are proposed. Results are also specialised to non-decreasing solutions, because only such supervisors can be realised in practice. The inherent issue of rationality raised recently is discussed. An illustration of concepts and results is presented through an example of a flexible manufacturing system.
Discovering Motifs in Biological Sequences Using the Micron Automata Processor.
Roy, Indranil; Aluru, Srinivas
2016-01-01
Finding approximately conserved sequences, called motifs, across multiple DNA or protein sequences is an important problem in computational biology. In this paper, we consider the (l, d) motif search problem of identifying one or more motifs of length l present in at least q of the n given sequences, with each occurrence differing from the motif in at most d substitutions. The problem is known to be NP-complete, and the largest solved instance reported to date is (26,11). We propose a novel algorithm for the (l,d) motif search problem using streaming execution over a large set of non-deterministic finite automata (NFA). This solution is designed to take advantage of the micron automata processor, a new technology close to deployment that can simultaneously execute multiple NFA in parallel. We demonstrate the capability for solving much larger instances of the (l, d) motif search problem using the resources available within a single automata processor board, by estimating run-times for problem instances (39,18) and (40,17). The paper serves as a useful guide to solving problems using this new accelerator technology. PMID:26886735
All-DNA finite-state automata with finite memory.
Wang, Zhen-Gang; Elbaz, Johann; Remacle, F; Levine, R D; Willner, Itamar
2010-12-21
Biomolecular logic devices can be applied for sensing and nano-medicine. We built three DNA tweezers that are activated by the inputs H(+)/OH(-); ; nucleic acid linker/complementary antilinker to yield a 16-states finite-state automaton. The outputs of the automata are the configuration of the respective tweezers (opened or closed) determined by observing fluorescence from a fluorophore/quencher pair at the end of the arms of the tweezers. The system exhibits a memory because each current state and output depend not only on the source configuration but also on past states and inputs. PMID:21135212
A SAND approach based on cellular computation models for analysis and optimization
NASA Astrophysics Data System (ADS)
Canyurt, O. E.; Hajela, P.
2007-06-01
Genetic algorithms (GAs) have received considerable recent attention in problems of design optimization. The mechanics of population-based search in GAs are highly amenable to implementation on parallel computers. The present article describes a fine-grained model of parallel GA implementation that derives from a cellular-automata-like computation. The central idea behind the cellular genetic algorithm (CGA) approach is to treat the GA population as being distributed over a 2-D grid of cells, with each member of the population occupying a particular cell and defining the state of that cell. Evolution of the cell state is tantamount to updating the design information contained in a cell site and, as in cellular automata computations, takes place on the basis of local interaction with neighbouring cells. A special focus of the article is in the use of cellular automata (CA)-based models for structural analysis in conjunction with the CGA approach to optimization. In such an approach, the analysis and optimization are evolved simultaneously in a unified cellular computational framework. The article describes the implementation of this approach and examines its efficiency in the context of representative structural optimization problems.
Development of a Bacteria Computer: From in silico Finite Automata to in vitro and in vivo
NASA Astrophysics Data System (ADS)
Sakakibara, Yasubumi
We overview a series of our research on implementing finite automata in vitro and in vivo in the framework of DNA-based computing [1,2]. First, we employ the length-encoding technique proposed and presented in [3,4] to implement finite automata in test tube. In the length-encoding method, the states and state transition functions of a target finite automaton are effectively encoded into DNA sequences, a computation (accepting) process of finite automata is accomplished by self-assembly of encoded complementary DNA strands, and the acceptance of an input string is determined by the detection of a completely hybridized double-strand DNA. Second, we report our intensive in vitro experiments in which we have implemented and executed several finite-state automata in test tube. We have designed and developed practical laboratory protocols which combine several in vitro operations such as annealing, ligation, PCR, and streptavidin-biotin bonding to execute in vitro finite automata based on the length-encoding technique. We have carried laboratory experiments on various finite automata with 2 up to 6 states for several input strings. Third, we present a novel framework to develop a programmable and autonomous in vivo computer using Escherichia coli (E. coli), and implement in vivo finite-state automata based on the framework by employing the protein-synthesis mechanism of E. coli. We show some successful experiments to run an in vivo finite-state automaton on E. coli.
Edison, John R.; Monson, Peter A.
2014-07-14
Recently we have developed a dynamic mean field theory (DMFT) for lattice gas models of fluids in porous materials [P. A. Monson, J. Chem. Phys. 128(8), 084701 (2008)]. The theory can be used to describe the relaxation processes in the approach to equilibrium or metastable states for fluids in pores and is especially useful for studying system exhibiting adsorption/desorption hysteresis. In this paper we discuss the extension of the theory to higher order by means of the path probability method (PPM) of Kikuchi and co-workers. We show that this leads to a treatment of the dynamics that is consistent with thermodynamics coming from the Bethe-Peierls or Quasi-Chemical approximation for the equilibrium or metastable equilibrium states of the lattice model. We compare the results from the PPM with those from DMFT and from dynamic Monte Carlo simulations. We find that the predictions from PPM are qualitatively similar to those from DMFT but give somewhat improved quantitative accuracy, in part due to the superior treatment of the underlying thermodynamics. This comes at the cost of greater computational expense associated with the larger number of equations that must be solved.
Sampling from complex networks using distributed learning automata
NASA Astrophysics Data System (ADS)
Rezvanian, Alireza; Rahmati, Mohammad; Meybodi, Mohammad Reza
2014-02-01
A complex network provides a framework for modeling many real-world phenomena in the form of a network. In general, a complex network is considered as a graph of real world phenomena such as biological networks, ecological networks, technological networks, information networks and particularly social networks. Recently, major studies are reported for the characterization of social networks due to a growing trend in analysis of online social networks as dynamic complex large-scale graphs. Due to the large scale and limited access of real networks, the network model is characterized using an appropriate part of a network by sampling approaches. In this paper, a new sampling algorithm based on distributed learning automata has been proposed for sampling from complex networks. In the proposed algorithm, a set of distributed learning automata cooperate with each other in order to take appropriate samples from the given network. To investigate the performance of the proposed algorithm, several simulation experiments are conducted on well-known complex networks. Experimental results are compared with several sampling methods in terms of different measures. The experimental results demonstrate the superiority of the proposed algorithm over the others.
Stochastic Games for Verification of Probabilistic Timed Automata
NASA Astrophysics Data System (ADS)
Kwiatkowska, Marta; Norman, Gethin; Parker, David
Probabilistic timed automata (PTAs) are used for formal modelling and verification of systems with probabilistic, nondeterministic and real-time behaviour. For non-probabilistic timed automata, forwards reachability is the analysis method of choice, since it can be implemented extremely efficiently. However, for PTAs, such techniques are only able to compute upper bounds on maximum reachability probabilities. In this paper, we propose a new approach to the analysis of PTAs using abstraction and stochastic games. We show how efficient forwards reachability techniques can be extended to yield both lower and upper bounds on maximum (and minimum) reachability probabilities. We also present abstraction-refinement techniques that are guaranteed to improve the precision of these probability bounds, providing a fully automatic method for computing the exact values. We have implemented these techniques and applied them to a set of large case studies. We show that, in comparison to alternative approaches to verifying PTAs, such as backwards reachability and digital clocks, our techniques exhibit superior performance and scalability.
Cellular automata model simulating traffic car accidents in the on-ramp system
NASA Astrophysics Data System (ADS)
Echab, H.; Lakouari, N.; Ez-Zahraouy, H.; Benyoussef, A.
2015-01-01
In this paper, using Nagel-Schreckenberg model we study the on-ramp system under the expanded open boundary condition. The phase diagram of the two-lane on-ramp system is computed. It is found that the expanded left boundary insertion strategy enhances the flow in the on-ramp lane. Furthermore, we have studied the probability of the occurrence of car accidents. We distinguish two types of car accidents: the accident at the on-ramp site (Prc) and the rear-end accident in the main road (Pac). It is shown that car accidents at the on-ramp site are more likely to occur when traffic is free on road A. However, the rear-end accidents begin to occur above a critical injecting rate αc1. The influence of the on-ramp length (LB) and position (xC0) on the car accidents probabilities is studied. We found that large LB or xC0 causes an important decrease of the probability Prc. However, only large xC0 provokes an increase of the probability Pac. The effect of the stochastic randomization is also computed.
Mathematical Modeling of Pedestrian Flows Using Cellular Automata and Dynamic Stepsizing
NASA Astrophysics Data System (ADS)
Bärwolff, Günter; Chen, Minjie; Schwandt, Hartmut
2007-09-01
We present a two-dimensional automaton model to simulate pedestrian flows. In this model, pedestrians may be allocated have preassigned or randomly chosen starting points and destinations, and they may get influenced by additional repelling or indicating factors. Interior walls and other obstacles can be abstracted as repellors. We apply Bresenham's algorithm [1] of line rastering to calculate the ideal forward step which a single pedestrian may take on a two-dimensional grid. We introduce a flexible choice of step sizes to improve the basic algorithm.
A multi-layer cellular automata approach for algorithmic generation of virtual case studies: VIBe.
Sitzenfrei, R; Fach, S; Kinzel, H; Rauch, W
2010-01-01
Analyses of case studies are used to evaluate new or existing technologies, measures or strategies with regard to their impact on the overall process. However, data availability is limited and hence, new technologies, measures or strategies can only be tested on a limited number of case studies. Owing to the specific boundary conditions and system properties of each single case study, results can hardly be generalized or transferred to other boundary conditions. virtual infrastructure benchmarking (VIBe) is a software tool which algorithmically generates virtual case studies (VCSs) for urban water systems. System descriptions needed for evaluation are extracted from VIBe whose parameters are based on real world case studies and literature. As a result VIBe writes Input files for water simulation software as EPANET and EPA SWMM. With such input files numerous simulations can be performed and the results can be benchmarked and analysed stochastically at a city scale. In this work the approach of VIBe is applied with parameters according to a section of the Inn valley and therewith 1,000 VCSs are generated and evaluated. A comparison of the VCSs with data of real world case studies shows that the real world case studies fit within the parameter ranges of the VCSs. Consequently, VIBe tackles the problem of limited availability of case study data. PMID:20057089
A survey of cellular automata like the “game of life”
NASA Astrophysics Data System (ADS)
de la Torre, A. C.; Mártin, H. O.
1997-02-01
The density and activity (defined as the average between the rate of fertility and the rate of mortality) for all games similar to the “game of life” has been calculated after 1000 time steps in a 100 × 100 lattice. Mean-field arguments that describe some global features are presented. A morphological description for many games resembling shapes found in nature is given.
NASA Astrophysics Data System (ADS)
Liu, Da-Jiang; Evans, James W.
2013-12-01
A realistic molecular-level description of catalytic reactions on single-crystal metal surfaces can be provided by stochastic multisite lattice-gas (msLG) models. This approach has general applicability, although in this report, we will focus on the example of CO-oxidation on the unreconstructed fcc metal (1 0 0) or M(1 0 0) surfaces of common catalyst metals M = Pd, Rh, Pt and Ir (i.e., avoiding regimes where Pt and Ir reconstruct). These models can capture the thermodynamics and kinetics of adsorbed layers for the individual reactants species, such as CO/M(1 0 0) and O/M(1 0 0), as well as the interaction and reaction between different reactant species in mixed adlayers, such as (CO + O)/M(1 0 0). The msLG models allow population of any of hollow, bridge, and top sites. This enables a more flexible and realistic description of adsorption and adlayer ordering, as well as of reaction configurations and configuration-dependent barriers. Adspecies adsorption and interaction energies, as well as barriers for various processes, constitute key model input. The choice of these energies is guided by experimental observations, as well as by extensive Density Functional Theory analysis. Model behavior is assessed via Kinetic Monte Carlo (KMC) simulation. We also address the simulation challenges and theoretical ramifications associated with very rapid diffusion and local equilibration of reactant adspecies such as CO. These msLG models are applied to describe adsorption, ordering, and temperature programmed desorption (TPD) for individual CO/M(1 0 0) and O/M(1 0 0) reactant adlayers. In addition, they are also applied to predict mixed (CO + O)/M(1 0 0) adlayer structure on the nanoscale, the complete bifurcation diagram for reactive steady-states under continuous flow conditions, temperature programmed reaction (TPR) spectra, and titration reactions for the CO-oxidation reaction. Extensive and reasonably successful comparison of model predictions is made with experimental
Liu, Dajiang; Evans, James W.
2013-12-01
A realistic molecular-level description of catalytic reactions on single-crystal metal surfaces can be provided by stochastic multisite lattice-gas (msLG) models. This approach has general applicability, although in this report, we will focus on the example of CO-oxidation on the unreconstructed fcc metal (100) or M(100) surfaces of common catalyst metals M = Pd, Rh, Pt and Ir (i.e., avoiding regimes where Pt and Ir reconstruct). These models can capture the thermodynamics and kinetics of adsorbed layers for the individual reactants species, such as CO/M(100) and O/M(100), as well as the interaction and reaction between different reactant species in mixed adlayers, such as (CO + O)/M(100). The msLG models allow population of any of hollow, bridge, and top sites. This enables a more flexible and realistic description of adsorption and adlayer ordering, as well as of reaction configurations and configuration-dependent barriers. Adspecies adsorption and interaction energies, as well as barriers for various processes, constitute key model input. The choice of these energies is guided by experimental observations, as well as by extensive Density Functional Theory analysis. Model behavior is assessed via Kinetic Monte Carlo (KMC) simulation. We also address the simulation challenges and theoretical ramifications associated with very rapid diffusion and local equilibration of reactant adspecies such as CO. These msLG models are applied to describe adsorption, ordering, and temperature programmed desorption (TPD) for individual CO/M(100) and O/M(100) reactant adlayers. In addition, they are also applied to predict mixed (CO + O)/M(100) adlayer structure on the nanoscale, the complete bifurcation diagram for reactive steady-states under continuous flow conditions, temperature programmed reaction (TPR) spectra, and titration reactions for the CO-oxidation reaction. Extensive and reasonably successful comparison of model predictions is made with experimental data. Furthermore
Spectral Analysis of Transition Operators, Automata Groups and Translation in BBS
NASA Astrophysics Data System (ADS)
Kato, Tsuyoshi; Tsujimoto, Satoshi; Zuk, Andrzej
2016-06-01
We give the automata that describe time evolution rules of the box-ball system with a carrier. It can be shown by use of tropical geometry that such systems are ultradiscrete analogues of KdV equation. We discuss their relation with the lamplighter group generated by an automaton. We present spectral analysis of the stochastic matrices induced by these automata and verify their spectral coincidence.
Automata network theories in immunology: their utility and their underdetermination.
Atlan, H
1989-01-01
Small networks of threshold automata are used to model complex interactions between populations of regulatory cells (helpers and suppressors, antigen specific and anti-idiotypic) which participate in the immune response. The models, being discrete and semiquantitative, are well adapted to the situation of incomplete information often encountered in vivo. However, the dynamics of many different network structures usually end up in the same attractor set. Thus, many different theories are equivalent in their explicative power for the same facts. This property, known as underdetermination of the theories by the facts, is given a quantitative estimate. It appears that such an underdetermination, as a kind of irreducible complexity, can be expected in many in vivo biological processes, even when the number of interacting and functionally coupled elements is relatively small. PMID:2924021
Towards Time Automata and Multi-Agent Systems
NASA Technical Reports Server (NTRS)
Hutzler, G.; Klaudel, H.; Wang, D. Y.
2004-01-01
The design of reactive systems must comply with logical correctness (the system does what it is supposed to do) and timeliness (the system has to satisfy a set of temporal constraints) criteria. In this paper, we propose a global approach for the design of adaptive reactive systems, i.e., systems that dynamically adapt their architecture depending on the context. We use the timed automata formalism for the design of the agents' behavior. This allows evaluating beforehand the properties of the system (regarding logical correctness and timeliness), thanks to model-checking and simulation techniques. This model is enhanced with tools that we developed for the automatic generation of code, allowing to produce very quickly a running multi-agent prototype satisfying the properties of the model.
Encoding nondeterministic fuzzy tree automata into recursive neural networks.
Gori, Marco; Petrosino, Alfredo
2004-11-01
Fuzzy neural systems have been a subject of great interest in the last few years, due to their abilities to facilitate the exchange of information between symbolic and subsymbolic domains. However, the models in the literature are not able to deal with structured organization of information, that is typically required by symbolic processing. In many application domains, the patterns are not only structured, but a fuzziness degree is attached to each subsymbolic pattern primitive. The purpose of this paper is to show how recursive neural networks, properly conceived for dealing with structured information, can represent nondeterministic fuzzy frontier-to-root tree automata. Whereas available prior knowledge expressed in terms of fuzzy state transition rules are injected into a recursive network, unknown rules are supposed to be filled in by data-driven learning. We also prove the stability of the encoding algorithm, extending previous results on the injection of fuzzy finite-state dynamics in high-order recurrent networks. PMID:15565771
Hybrid automata as a unifying framework for modeling excitable cells.
Ye, P; Entcheva, E; Smolka, S A; True, M R; Grosu, R
2006-01-01
We propose hybrid automata (HA) as a unifying framework for computational models of excitable cells. HA, which combine discrete transition graphs with continuous dynamics, can be naturally used to obtain a piecewise, possibly linear, approximation of a nonlinear excitable-cell model. We first show how HA can be used to efficiently capture the action-potential morphology--as well as reproduce typical excitable-cell characteristics such as refractoriness and restitution--of the dynamic Luo-Rudy model of a guinea-pig ventricular myocyte. We then recast two well-known computational models, Biktashev's and Fenton-Karma, as HA without any loss of expressiveness. Given that HA possess an intuitive graphical representation and are supported by a rich mathematical theory and numerous analysis tools, we argue that they are well positioned as a computational model for biological processes. PMID:17947070
Behavioral Modeling Based on Probabilistic Finite Automata: An Empirical Study.
Tîrnăucă, Cristina; Montaña, José L; Ontañón, Santiago; González, Avelino J; Pardo, Luis M
2016-01-01
Imagine an agent that performs tasks according to different strategies. The goal of Behavioral Recognition (BR) is to identify which of the available strategies is the one being used by the agent, by simply observing the agent's actions and the environmental conditions during a certain period of time. The goal of Behavioral Cloning (BC) is more ambitious. In this last case, the learner must be able to build a model of the behavior of the agent. In both settings, the only assumption is that the learner has access to a training set that contains instances of observed behavioral traces for each available strategy. This paper studies a machine learning approach based on Probabilistic Finite Automata (PFAs), capable of achieving both the recognition and cloning tasks. We evaluate the performance of PFAs in the context of a simulated learning environment (in this case, a virtual Roomba vacuum cleaner robot), and compare it with a collection of other machine learning approaches. PMID:27347956
LAHS: A novel harmony search algorithm based on learning automata
NASA Astrophysics Data System (ADS)
Enayatifar, Rasul; Yousefi, Moslem; Abdullah, Abdul Hanan; Darus, Amer Nordin
2013-12-01
This study presents a learning automata-based harmony search (LAHS) for unconstrained optimization of continuous problems. The harmony search (HS) algorithm performance strongly depends on the fine tuning of its parameters, including the harmony consideration rate (HMCR), pitch adjustment rate (PAR) and bandwidth (bw). Inspired by the spur-in-time responses in the musical improvisation process, learning capabilities are employed in the HS to select these parameters based on spontaneous reactions. An extensive numerical investigation is conducted on several well-known test functions, and the results are compared with the HS algorithm and its prominent variants, including the improved harmony search (IHS), global-best harmony search (GHS) and self-adaptive global-best harmony search (SGHS). The numerical results indicate that the LAHS is more efficient in finding optimum solutions and outperforms the existing HS algorithm variants.
Emergence of Power-Law in Spatial Epidemics Using Cellular Automation
NASA Astrophysics Data System (ADS)
Li, Li; Sun, Gui-Quan; Jin, Zhen
We analyze a spatial susceptible-infected epidemic model using cellular automata and investigate the relations between the power-law distribution of patch sizes and the regime of invasion. The obtained results show that, when the invasion is in the form of coexistence of stable target and spiral wave, power-law will emerge, which may provide a new insight into the control of disease.
Towards a voxel-based geographic automata for the simulation of geospatial processes
NASA Astrophysics Data System (ADS)
Jjumba, Anthony; Dragićević, Suzana
2016-07-01
Many geographic processes evolve in a three dimensional space and time continuum. However, when they are represented with the aid of geographic information systems (GIS) or geosimulation models they are modelled in a framework of two-dimensional space with an added temporal component. The objective of this study is to propose the design and implementation of voxel-based automata as a methodological approach for representing spatial processes evolving in the four-dimensional (4D) space-time domain. Similar to geographic automata models which are developed to capture and forecast geospatial processes that change in a two-dimensional spatial framework using cells (raster geospatial data), voxel automata rely on the automata theory and use three-dimensional volumetric units (voxels). Transition rules have been developed to represent various spatial processes which range from the movement of an object in 3D to the diffusion of airborne particles and landslide simulation. In addition, the proposed 4D models demonstrate that complex processes can be readily reproduced from simple transition functions without complex methodological approaches. The voxel-based automata approach provides a unique basis to model geospatial processes in 4D for the purpose of improving representation, analysis and understanding their spatiotemporal dynamics. This study contributes to the advancement of the concepts and framework of 4D GIS.
Devising an unconventional formal logic for bioinspired spacefaring automata
NASA Astrophysics Data System (ADS)
Santoli, Salvatore
2011-03-01
The field of robotics is increasingly moving from robots confined to factory floors and assembly lines and bound to perform the same tasks over and over in an uncertainty-free, well foreseeable environment, to robots designed for operating in highly dynamic and uncertainty domains, like those of interest in space exploration. According to an idea of a "new system of formal logic less rigid than past and present formal logic" advocated by von Neumann for building a powerful theory of automata, such system should be "closer to another discipline which has been little linked in the past with logic, i.e. thermodynamics, primarily in the form it was received by Boltzmann". Following that idea, which is particularly interesting now with the emerging computational nano-sciences, it is stressed here that a full set of isomorphisms can be established between the fundamental logical principles and the information flows, Hamiltonian or dissipative, in phase space. This form of logic, dubbed here kinetic logic, takes standard formal logic out of the field of combinatorics and into the field of the Boltzmannian form of thermodynamics, i.e. kinetics.
Epileptic spike recognition in electroencephalogram using deterministic finite automata.
Keshri, Anup Kumar; Sinha, Rakesh Kumar; Hatwal, Rajesh; Das, Barda Nand
2009-06-01
This Paper presents an automated method of Epileptic Spike detection in Electroencephalogram (EEG) using Deterministic Finite Automata (DFA). It takes prerecorded single channel EEG data file as input and finds the occurrences of Epileptic Spikes data in it. The EEG signal was recorded at 256 Hz in two minutes separate data files using the Visual Lab-M software (ADLink Technology Inc., Taiwan). It was preprocessed for removal of baseline shift and band pass filtered using an infinite impulse response (IIR) Butterworth filter. A system, whose functionality was modeled with DFA, was designed. The system was tested with 10 EEG signal data files. The recognition rate of Epileptic Spike as on average was 95.68%. This system does not require any human intrusion. Also it does not need any short of training. The result shows that the application of DFA can be useful in detection of different characteristics present in EEG signals. This approach could be extended to a continuous data processing system. PMID:19408450
Artificial life simulation of self-assembly in bacteriophage by movable finite automata.
Shirayama, Masatoshi; Koshino, Makoto; Hatakeyama, Toyomasa; Kimura, Haruhiko
2004-11-01
This paper presents a model which is based on biological research using the movable finite automata (MFA) on a self-assembly of T4 phage, and exhibits the results of artificial life simulation. In the previous work, Thompson and Goel [Artificial Life, Addison Weley, 1989, pp. 317-340; Biosystems 18 (1985) 23; J. Theor. Biol. 131 (1988) 351] presented the movable finite automata (MFA) which has a capability of moving on finite automata, and simulated on a computer. They were represented individual rectangular boxes, however, the results of simulation was different from real T4 phage. We propose the sphere model as a protein structure, and simulate the self-assembly of the entire structure of the T4 phage on a computer. PMID:15527954
Dirac Cellular Automaton from Split-step Quantum Walk
NASA Astrophysics Data System (ADS)
Mallick, Arindam; Chandrashekar, C. M.
2016-05-01
Simulations of one quantum system by an other has an implication in realization of quantum machine that can imitate any quantum system and solve problems that are not accessible to classical computers. One of the approach to engineer quantum simulations is to discretize the space-time degree of freedom in quantum dynamics and define the quantum cellular automata (QCA), a local unitary update rule on a lattice. Different models of QCA are constructed using set of conditions which are not unique and are not always in implementable configuration on any other system. Dirac Cellular Automata (DCA) is one such model constructed for Dirac Hamiltonian (DH) in free quantum field theory. Here, starting from a split-step discrete-time quantum walk (QW) which is uniquely defined for experimental implementation, we recover the DCA along with all the fine oscillations in position space and bridge the missing connection between DH-DCA-QW. We will present the contribution of the parameters resulting in the fine oscillations on the Zitterbewegung frequency and entanglement. The tuneability of the evolution parameters demonstrated in experimental implementation of QW will establish it as an efficient tool to design quantum simulator and approach quantum field theory from principles of quantum information theory.
Dirac Cellular Automaton from Split-step Quantum Walk.
Mallick, Arindam; Chandrashekar, C M
2016-01-01
Simulations of one quantum system by an other has an implication in realization of quantum machine that can imitate any quantum system and solve problems that are not accessible to classical computers. One of the approach to engineer quantum simulations is to discretize the space-time degree of freedom in quantum dynamics and define the quantum cellular automata (QCA), a local unitary update rule on a lattice. Different models of QCA are constructed using set of conditions which are not unique and are not always in implementable configuration on any other system. Dirac Cellular Automata (DCA) is one such model constructed for Dirac Hamiltonian (DH) in free quantum field theory. Here, starting from a split-step discrete-time quantum walk (QW) which is uniquely defined for experimental implementation, we recover the DCA along with all the fine oscillations in position space and bridge the missing connection between DH-DCA-QW. We will present the contribution of the parameters resulting in the fine oscillations on the Zitterbewegung frequency and entanglement. The tuneability of the evolution parameters demonstrated in experimental implementation of QW will establish it as an efficient tool to design quantum simulator and approach quantum field theory from principles of quantum information theory. PMID:27184159
Dirac Cellular Automaton from Split-step Quantum Walk
Mallick, Arindam; Chandrashekar, C. M.
2016-01-01
Simulations of one quantum system by an other has an implication in realization of quantum machine that can imitate any quantum system and solve problems that are not accessible to classical computers. One of the approach to engineer quantum simulations is to discretize the space-time degree of freedom in quantum dynamics and define the quantum cellular automata (QCA), a local unitary update rule on a lattice. Different models of QCA are constructed using set of conditions which are not unique and are not always in implementable configuration on any other system. Dirac Cellular Automata (DCA) is one such model constructed for Dirac Hamiltonian (DH) in free quantum field theory. Here, starting from a split-step discrete-time quantum walk (QW) which is uniquely defined for experimental implementation, we recover the DCA along with all the fine oscillations in position space and bridge the missing connection between DH-DCA-QW. We will present the contribution of the parameters resulting in the fine oscillations on the Zitterbewegung frequency and entanglement. The tuneability of the evolution parameters demonstrated in experimental implementation of QW will establish it as an efficient tool to design quantum simulator and approach quantum field theory from principles of quantum information theory. PMID:27184159
The cellular automaton model of investment behavior in the stock market
NASA Astrophysics Data System (ADS)
Wei, Yi-ming; Ying, Shang-jun; Fan, Ying; Wang, Bing-Hong
2003-07-01
The modeling theory and method using cellular automata are applied to the study on the complexity in the stock market. An evolution model based on cellular automaton for the investment behavior in the stock market is formulated. The simulation results and analyses of various states of the stock market show that investors’ imitation degree and the macro factors are the key determinants to the stability of the stock market. We observed that more diversity in the investment views of agents and lower imitation among investors are in favor of the normal development of the stock market.
Smirnova, Lena; Harris, Georgina; Leist, Marcel; Hartung, Thomas
2015-01-01
Cellular resilience describes the ability of a cell to cope with environmental changes such as toxicant exposure. If cellular metabolism does not collapse directly after the hit or end in programmed cell death, the ensuing stress responses promote a new homeostasis under stress. The processes of reverting "back to normal" and reversal of apoptosis ("anastasis") have been studied little at the cellular level. Cell types show astonishingly similar vulnerability to most toxicants, except for those that require a very specific target, metabolism or mechanism present only in specific cell types. The majority of chemicals triggers "general cytotoxicity" in any cell at similar concentrations. We hypothesize that cells differ less in their vulnerability to a given toxicant than in their resilience (coping with the "hit"). In many cases, cells do not return to the naive state after a toxic insult. The phenomena of "pre-conditioning", "tolerance" and "hormesis" describe this for low-dose exposures to toxicants that render the cell more resistant to subsequent hits. The defense and resilience programs include epigenetic changes that leave a "memory/scar" - an alteration as a consequence of the stress the cell has experienced. These memories might have long-term consequences, both positive (resistance) and negative, that contribute to chronic and delayed manifestations of hazard and, ultimately, disease. This article calls for more systematic analyses of how cells cope with toxic perturbations in the long-term after stressor withdrawal. A technical prerequisite for these are stable (organotypic) cultures and a characterization of stress response molecular networks. PMID:26536287
Lower bounds on parallel, distributed, and automata computations
Gereb-Graus, M.
1989-01-01
In this thesis the author presents a collection of lower bound results from several areas of computer science. Conventional wisdom states that lower bounds are much more difficult to prove than upper bounds. To get an upper bound one has to demonstrate just one scheme with the appropriate complexity. On the other hand, to prove lower bounds one has to deal with all possible schemes. The difficulty of lower bounds can be further demonstrated by the fact that wherever for some problem he has a very large gap between the lower and the upper bound, the conjecture for the truth usually is the known upper bound. His first two results are impossibility results for finite state automata. A hierarchy of complexity classes on tree languages (analogous to the polynomial hierarchy) accepted by alternating finite state machines is introduced. It turns out that the alternating class is equal to the well known tree language class accepted by the treeautomata. By separating the deterministic and the nondeterministic classes of his hierarchy he gives a negative answer to the folklore question whether the expressive power of the treeautomata is the same as that of the finite state automaton that can walk on the edges of the tree (bugautomaton). He proves that three-head one-way DFA cannot perform string-matching, that is, no three-head one-way DFA accepts the language L = (x{number sign}y {vert bar} x is a substring of y, where x,y {element of} (0,1){sup *}). He proves that in a one round fair coin flipping (or voting) scheme with n participants, there is at least one participant who has a chance to decide the outcome with probability at least 3/n {minus} o(1/n).
Applications of automata and graphs: Labeling operators in Hilbert space. II
Cho, Ilwoo; Jorgensen, Palle E. T.
2009-06-15
We introduced a family of infinite graphs directly associated with a class of von Neumann automaton model A{sub G}. These are finite state models used in symbolic dynamics: stimuli models and in control theory. In the context of groupoid von Neumann algebras, and an associated fractal group, we prove a classification theorem for representations of automata.
Stimulus-Response Theory of Finite Automata, Technical Report No. 133.
ERIC Educational Resources Information Center
Suppes, Patrick
The central aim of this paper and its projected successors is to prove in detail that stimulus-response theory, or at least a mathematically precise version, can give an account of the learning of many phrase-structure grammars. Section 2 is concerned with standard notions of finite and probabilistic automata. An automaton is defined as a device…
Distributed learning automata-based algorithm for community detection in complex networks
NASA Astrophysics Data System (ADS)
Khomami, Mohammad Mehdi Daliri; Rezvanian, Alireza; Meybodi, Mohammad Reza
2016-03-01
Community structure is an important and universal topological property of many complex networks such as social and information networks. The detection of communities of a network is a significant technique for understanding the structure and function of networks. In this paper, we propose an algorithm based on distributed learning automata for community detection (DLACD) in complex networks. In the proposed algorithm, each vertex of network is equipped with a learning automation. According to the cooperation among network of learning automata and updating action probabilities of each automaton, the algorithm interactively tries to identify high-density local communities. The performance of the proposed algorithm is investigated through a number of simulations on popular synthetic and real networks. Experimental results in comparison with popular community detection algorithms such as walk trap, Danon greedy optimization, Fuzzy community detection, Multi-resolution community detection and label propagation demonstrated the superiority of DLACD in terms of modularity, NMI, performance, min-max-cut and coverage.
An Efficient Translation of Timed-Arc Petri Nets to Networks of Timed Automata
NASA Astrophysics Data System (ADS)
Byg, Joakim; Jørgensen, Kenneth Yrke; Srba, Jiří
Bounded timed-arc Petri nets with read-arcs were recently proven equivalent to networks of timed automata, though the Petri net model cannot express urgent behaviour and the described mutual translations are rather inefficient. We propose an extension of timed-arc Petri nets with invariants to enforce urgency and with transport arcs to generalise the read-arcs. We also describe a novel translation from the extended timed-arc Petri net model to networks of timed automata. The translation is implemented in the tool TAPAAL and it uses UPPAAL as the verification engine. Our experiments confirm the efficiency of the translation and in some cases the translated models verify significantly faster than the native UPPAAL models do.
Identification of finite state automata with a class of recurrent neural networks.
Won, Sung Hwan; Song, Iickho; Lee, Sun Young; Park, Cheol Hoon
2010-09-01
A class of recurrent neural networks is proposed and proven to be capable of identifying any discrete-time dynamical system. The application of the proposed network is addressed in the encoding, identification, and extraction of finite state automata (FSAs). Simulation results show that the identification of FSAs using the proposed network, trained by the hybrid greedy simulated annealing with a modified cost function in the training stage, generally exhibits better performance than the conventional identification procedures. PMID:20709639
NASA Astrophysics Data System (ADS)
Martin, Bruno
One-dimensional cellular automata are known to be able to present complex behaviors. In some cases, their evolution may be understood as movings, collisions, or creations of particles. In the case of the special Wolfram's rule 54, Boccara has previously pointed out basic particles. In this paper, we introduce a group which allows the formal study of interactions between these particles. Coming back to the complexity of rule 54 and using the new algebraic classification of Rapaport, we prove that rule 54 is not simple.
The use of hybrid automata for fault-tolerant vibration control for parametric failures
NASA Astrophysics Data System (ADS)
Byreddy, Chakradhar; Frampton, Kenneth D.; Yongmin, Kim
2006-03-01
The purpose of this work is to make use of hybrid automata for vibration control reconfiguration under system failures. Fault detection and isolation (FDI) filters are used to monitor an active vibration control system. When system failures occur (specifically parametric faults) the FDI filters detect and identify the specific failure. In this work we are specifically interested in parametric faults such as changes in system physical parameters; however this approach works equally well with additive faults such as sensor or actuator failures. The FDI filter output is used to drive a hybrid automaton, which selects the appropriate controller and FDI filter from a library. The hybrid automata also implements switching between controllers and filters in order to maintain optimal performance under faulty operating conditions. The biggest challenge in developing this system is managing the switching and in maintaining stability during the discontinuous switches. Therefore, in addition to vibration control, the stability associated with switching compensators and FDI filters is studied. Furthermore, the performance of two types of FDI filters is compared: filters based on parameter estimation methods and so called "Beard-Jones" filters. Finally, these simulations help in understanding the use of hybrid automata for fault-tolerant control.
NASA Astrophysics Data System (ADS)
Hirabayashi, Miki; Ohashi, Hirotada; Kubo, Tai
We have presented experimental analysis on the controllability of our transcription-based diagnostic biomolecular automata by programmed molecules. Focusing on the noninvasive transcriptome diagnosis by salivary mRNAs, we already proposed the novel concept of diagnostic device using DNA computation. This system consists of the main computational element which has a stem shaped promoter region and a pseudo-loop shaped read-only memory region for transcription regulation through the conformation change caused by the recognition of disease-related biomarkers. We utilize the transcription of malachite green aptamer sequence triggered by the target recognition for observation of detection. This algorithm makes it possible to release RNA-aptamer drugs multiply, different from the digestion-based systems by the restriction enzyme which was proposed previously, for the in-vivo use, however, the controllability of aptamer release is not enough at the previous stage. In this paper, we verified the regulation effect on aptamer transcription by programmed molecules in basic conditions towards the developm! ent of therapeutic automata. These results would bring us one step closer to the realization of new intelligent diagnostic and therapeutic automata based on molecular circuits.
Query Monitoring and Analysis for Database Privacy - A Security Automata Model Approach
Kumar, Anand; Ligatti, Jay; Tu, Yi-Cheng
2015-01-01
Privacy and usage restriction issues are important when valuable data are exchanged or acquired by different organizations. Standard access control mechanisms either restrict or completely grant access to valuable data. On the other hand, data obfuscation limits the overall usability and may result in loss of total value. There are no standard policy enforcement mechanisms for data acquired through mutual and copyright agreements. In practice, many different types of policies can be enforced in protecting data privacy. Hence there is the need for an unified framework that encapsulates multiple suites of policies to protect the data. We present our vision of an architecture named security automata model (SAM) to enforce privacy-preserving policies and usage restrictions. SAM analyzes the input queries and their outputs to enforce various policies, liberating data owners from the burden of monitoring data access. SAM allows administrators to specify various policies and enforces them to monitor queries and control the data access. Our goal is to address the problems of data usage control and protection through privacy policies that can be defined, enforced, and integrated with the existing access control mechanisms using SAM. In this paper, we lay out the theoretical foundation of SAM, which is based on an automata named Mandatory Result Automata. We also discuss the major challenges of implementing SAM in a real-world database environment as well as ideas to meet such challenges. PMID:26997936
Modeling the topological organization of cellular processes.
Giavitto, Jean-Louis; Michel, Olivier
2003-07-01
The cell as a dynamical system presents the characteristics of having a dynamical structure. That is, the exact phase space of the system cannot be fixed before the evolution and integrative cell models must state the evolution of the structure jointly with the evolution of the cell state. This kind of dynamical systems is very challenging to model and simulate. New programming concepts must be developed to ease their modeling and simulation. In this context, the goal of the MGS project is to develop an experimental programming language dedicated to the simulation of this kind of systems. MGS proposes a unified view on several computational mechanisms (CHAM, Lindenmayer systems, Paun systems, cellular automata) enabling the specification of spatially localized computations on heterogeneous entities. The evolution of a dynamical structure is handled through the concept of transformation which relies on the topological organization of the system components. An example based on the modeling of spatially distributed biochemical networks is used to illustrate how these notions can be used to model the spatial and temporal organization of intracellular processes. PMID:12915272
NASA Astrophysics Data System (ADS)
Mendonça, J. Ricardo G.
2016-07-01
We investigate the inactive-active phase transition in an array of additive (exclusive-or) cellular automata (CA) under noise. The model is closely related with the Domany-Kinzel (DK) probabilistic cellular automaton (PCA), for which there are rigorous as well as numerical estimates on the transition probabilities. Here, we characterize the critical behavior of the noisy additive cellular automaton by mean field analysis and finite-size scaling and show that its phase transition belongs to the directed percolation universality class of critical behavior. As a by-product of our analysis, we argue that the critical behavior of the noisy elementary CA 90 and 102 (in Wolfram’s enumeration scheme) must be the same. We also perform an empirical investigation of the mean field equations to assess their quality and find that away from the critical point (but not necessarily very far away) the mean field approximations provide a reasonably good description of the dynamics of the PCA.
NASA Astrophysics Data System (ADS)
Li, Xin; Li, Xingang; Xiao, Yao; Jia, Bin
2016-06-01
Real traffic is heterogeneous with car and truck. Due to mechanical restrictions, the car and the truck have different limited deceleration capabilities, which are important factors in safety driving. This paper extends the single lane safety driving (SD) model with limited deceleration capability to two-lane SD model, in which car-truck heterogeneous traffic is considered. A car has a larger limited deceleration capability while a heavy truck has a smaller limited deceleration capability as a result of loaded goods. Then the safety driving conditions are different as the types of the following and the leading vehicles vary. In order to eliminate the well-known plug in heterogeneous two-lane traffic, it is assumed that heavy truck has active deceleration behavior when the heavy truck perceives the forming plug. The lane-changing decisions are also determined by the safety driving conditions. The fundamental diagram, spatiotemporal diagram, and lane-changing frequency were investigated to show the effect of mechanical restriction on heterogeneous traffic flow. It was shown that there would be still three traffic phases in heterogeneous traffic condition; the active deceleration of the heavy truck could well eliminate the plug; the lane-changing frequency was low in synchronized flow; the flow and velocity would decrease as the proportion of heavy truck grows or the limited deceleration capability of heavy truck drops; and the flow could be improved with lane control measures.
NASA Astrophysics Data System (ADS)
Caracciolo, D.; Istanbulluoglu, E.; Noto, L. V.
2013-12-01
Arid and semiarid grasslands of western North America have experienced dramatic changes over the last 150 years as a result of woody plant encroachment (WPE). WPE is characterized as increase in density, cover and biomass of indigenous tree or shrubby plants in grasslands. In this study we examine the environmental factors that trigger and further the progress of WPE at two semiarid sites using the CATGraSS ecohydrologic plant coexistence model. CATGraSS is a spatially distributed model driven by spatially explicit irradiance and runs on a fine-resolution gridded domain. In CATGraSS each cell can hold a single plant type or can remain empty. Plant competition is modeled by keeping track of mortality and establishment of plants, both calculated probabilistically based on soil moisture stress. For this study CATGraSS is improved with a stochastic fire and a grazing function, and its plant establishment algorithm is modified. Using CATGraSS shrub encroachment is studied in the Sevilleta National Wildlife Refuge (SNWR), New Mexico, located in the northern Chihuahuan desert. The area shows a dramatic encroachment front of Larrea tridentata (shrub) into native desert grassland. The model is implemented in a small area (7.3 km2) in SNWR. The second study site is a small catchment (11.8 km2) located within the Ochoco National Forest, Crook County, OR, where Juniper encroachment has been observed since the mid 1800s. The outcome of the changes in observed climate, fire frequency, and grazing intensity are investigated through numerical modeling scenarios. While in the Ochoco National Forest basin, the Western Juniper encroaches all the study area and the shrub disappears. In the SNWR basin, the model is able to reproduce the encroachment, simulating an increasing of the shrub from 2% in 1860 to 42% in 2010 (actual shrub percentage) highlighting as more influent factors the reduced fire frequency and the increased grazing intensity.
The development of models is of interest to ecologists, regulators and developers, since it may assist theoretical understanding, decision making in experimental design, product development and risk assessment. A successful modeling methodology for investigating such characteris...
NASA Astrophysics Data System (ADS)
Zvejnieks, G.; Merzlyakov, P.; Kuzovkov, V. N.; Kotomin, E. A.
2016-02-01
Calcium fluoride (CaF2) is an important optical material widely used in both microlithography and deep UV windows. It is known that under certain conditions electron beam irradiation can create therein a superlattice consisting of vacancy clusters (called a void lattice). The goal of this paper is twofold. Firstly, to perform a quantitative analysis of experimental TEM images demonstrating void lattice formation, we developed two distinct image filters. As a result, we can easily calculate vacancy concentration, vacancy cluster distribution function as well as average distances between defect clusters. The results for two suggested filters are similar and demonstrate that experimental void cluster growth is accompanied by a slight increase of the void lattice constant. Secondly, we proposed a microscopic model that allows us to reproduce a macroscopic void ordering, in agreement with experimental data, and to resolve existing theoretical and experimental contradictions. Our computer simulations demonstrate that macroscopic void lattice self-organization can occur only in a narrow parameter range. Moreover, we studied the kinetics of a void lattice ordering, starting from an initial disordered stage, in a good agreement with the TEM experimental data.
Kawano, Tomonori; Bouteau, François; Mancuso, Stefano
2012-11-01
The automata theory is the mathematical study of abstract machines commonly studied in the theoretical computer science and highly interdisciplinary fields that combine the natural sciences and the theoretical computer science. In the present review article, as the chemical and biological basis for natural computing or informatics, some plants, plant cells or plant-derived molecules involved in signaling are listed and classified as natural sequential machines (namely, the Mealy machines or Moore machines) or finite state automata. By defining the actions (states and transition functions) of these natural automata, the similarity between the computational data processing and plant decision-making processes became obvious. Finally, their putative roles as the parts for plant-based computing or robotic systems are discussed. PMID:23336016
Kawano, Tomonori; Bouteau, François; Mancuso, Stefano
2012-01-01
The automata theory is the mathematical study of abstract machines commonly studied in the theoretical computer science and highly interdisciplinary fields that combine the natural sciences and the theoretical computer science. In the present review article, as the chemical and biological basis for natural computing or informatics, some plants, plant cells or plant-derived molecules involved in signaling are listed and classified as natural sequential machines (namely, the Mealy machines or Moore machines) or finite state automata. By defining the actions (states and transition functions) of these natural automata, the similarity between the computational data processing and plant decision-making processes became obvious. Finally, their putative roles as the parts for plant-based computing or robotic systems are discussed. PMID:23336016
A verification strategy for web services composition using enhanced stacked automata model.
Nagamouttou, Danapaquiame; Egambaram, Ilavarasan; Krishnan, Muthumanickam; Narasingam, Poonkuzhali
2015-01-01
Currently, Service-Oriented Architecture (SOA) is becoming the most popular software architecture of contemporary enterprise applications, and one crucial technique of its implementation is web services. Individual service offered by some service providers may symbolize limited business functionality; however, by composing individual services from different service providers, a composite service describing the intact business process of an enterprise can be made. Many new standards have been defined to decipher web service composition problem namely Business Process Execution Language (BPEL). BPEL provides an initial work for forming an Extended Markup Language (XML) specification language for defining and implementing business practice workflows for web services. The problems with most realistic approaches to service composition are the verification of composed web services. It has to depend on formal verification method to ensure the correctness of composed services. A few research works has been carried out in the literature survey for verification of web services for deterministic system. Moreover the existing models did not address the verification properties like dead transition, deadlock, reachability and safetyness. In this paper, a new model to verify the composed web services using Enhanced Stacked Automata Model (ESAM) has been proposed. The correctness properties of the non-deterministic system have been evaluated based on the properties like dead transition, deadlock, safetyness, liveness and reachability. Initially web services are composed using Business Process Execution Language for Web Service (BPEL4WS) and it is converted into ESAM (combination of Muller Automata (MA) and Push Down Automata (PDA)) and it is transformed into Promela language, an input language for Simple ProMeLa Interpreter (SPIN) tool. The model is verified using SPIN tool and the results revealed better recital in terms of finding dead transition and deadlock in contrast to the
Cellular Stress Responses and Monitored Cellular Activities.
Sawa, Teiji; Naito, Yoshifumi; Kato, Hideya; Amaya, Fumimasa
2016-08-01
To survive, organisms require mechanisms that enable them to sense changes in the outside environment, introduce necessary responses, and resist unfavorable distortion. Consequently, through evolutionary adaptation, cells have become equipped with the apparatus required to monitor their fundamental intracellular processes and the mechanisms needed to try to offset malfunction without receiving any direct signals from the outside environment. It has been shown recently that eukaryotic cells are equipped with a special mechanism that monitors their fundamental cellular functions and that some pathogenic proteobacteria can override this monitoring mechanism to cause harm. The monitored cellular activities involved in the stressed intracellular response have been researched extensively in Caenorhabditis elegans, where discovery of an association between key mitochondrial activities and innate immune responses was named "cellular associated detoxification and defenses (cSADD)." This cellular surveillance pathway (cSADD) oversees core cellular activities such as mitochondrial respiration and protein transport into mitochondria, detects xenobiotics and invading pathogens, and activates the endocrine pathways controlling behavior, detoxification, and immunity. The cSADD pathway is probably associated with cellular responses to stress in human inflammatory diseases. In the critical care field, the pathogenesis of lethal inflammatory syndromes (e.g., respiratory distress syndromes and sepsis) involves the disturbance of mitochondrial respiration leading to cell death. Up-to-date knowledge about monitored cellular activities and cSADD, especially focusing on mitochondrial involvement, can probably help fill a knowledge gap regarding the pathogenesis of lethal inflammatory syndromes in the critical care field. PMID:26954943
... the call. How are people exposed to the energy from cellular phone towers? As people use cell ... where people can be exposed to them. The energy from a cellular phone tower antenna, like that ...
Hierarchical cellular materials
Gibson, L.J.
1991-01-01
In this paper a method for estimating the contributions of both the composite and the cellular microstructures to the overall material properties and the mechanical efficiency of natural cellular solids will be described. The method will be demonstrated by focusing on the Young's modulus; similar techniques can be used for other material properties. The results suggest efficient microstructures for engineered cellular materials.
Hierarchical cellular materials
Gibson, L.J.
1991-12-31
In this paper a method for estimating the contributions of both the composite and the cellular microstructures to the overall material properties and the mechanical efficiency of natural cellular solids will be described. The method will be demonstrated by focusing on the Young`s modulus; similar techniques can be used for other material properties. The results suggest efficient microstructures for engineered cellular materials.
NASA Astrophysics Data System (ADS)
Zhang, Li-Sheng; Deng, Min-Yi; Kong, Ling-Jiang; Liu, Mu-Ren; Tang, Guo-Ning
2010-01-01
Using the Greenberg-Hasting cellular automata model, we study the properties of target waves in excitable media under the no-flux boundary conditions. For the system has only one excited state, the computer simulation and analysis lead to the conclusions that, the number of refractory states does not influence the wave-front speed; the wave-front speed decreases as the excitation threshold increases and increases as the neighbor radius increases; the period of target waves is equal to the number of cell states; the excitation condition for target waves is that the wave-front speed must be bigger than half of the neighbor radius.
Fan, Linjun; Tang, Jun; Ling, Yunxiang; Li, Benxian
2014-01-01
This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA. PMID:24772033
Revisiting Decidability and Optimum Reachability for Multi-Priced Timed Automata
NASA Astrophysics Data System (ADS)
Fränzle, Martin; Swaminathan, Mani
We investigate the optimum reachability problem for Multi-Priced Timed Automata (MPTA) that admit both positive and negative costs on edges and locations, thus bridging the gap between the results of Bouyer et al. (2007) and of Larsen and Rasmussen (2008). Our contributions are the following: (1) We show that even the location reachability problem is undecidable for MPTA equipped with both positive and negative costs, provided the costs are subject to a bounded budget, in the sense that paths of the underlying Multi-Priced Transition System (MPTS) that operationally exceed the budget are considered as not being viable. This undecidability result follows from an encoding of Stop-Watch Automata using such MPTA, and applies to MPTA with as few as two cost variables, and even when no costs are incurred upon taking edges. (2) We then restrict the MPTA such that each viable quasi-cyclic path of the underlying MPTS incurs a minimum absolute cost. Under such a condition, the location reachability problem is shown to be decidable and the optimum cost is shown to be computable for MPTA with positive and negative costs and a bounded budget. These results follow from a reduction of the optimum reachability problem to the solution of a linear constraint system representing the path conditions over a finite number of viable paths of bounded length.
Simulating tissue mechanics with agent-based models: concepts, perspectives and some novel results
NASA Astrophysics Data System (ADS)
Van Liedekerke, P.; Palm, M. M.; Jagiella, N.; Drasdo, D.
2015-12-01
In this paper we present an overview of agent-based models that are used to simulate mechanical and physiological phenomena in cells and tissues, and we discuss underlying concepts, limitations, and future perspectives of these models. As the interest in cell and tissue mechanics increase, agent-based models are becoming more common the modeling community. We overview the physical aspects, complexity, shortcomings, and capabilities of the major agent-based model categories: lattice-based models (cellular automata, lattice gas cellular automata, cellular Potts models), off-lattice models (center-based models, deformable cell models, vertex models), and hybrid discrete-continuum models. In this way, we hope to assist future researchers in choosing a model for the phenomenon they want to model and understand. The article also contains some novel results.
Rule-based modelling and simulation of biochemical systems with molecular finite automata.
Yang, J; Meng, X; Hlavacek, W S
2010-11-01
The authors propose a theoretical formalism, molecular finite automata (MFA), to describe individual proteins as rule-based computing machines. The MFA formalism provides a framework for modelling individual protein behaviours and systems-level dynamics via construction of programmable and executable machines. Models specified within this formalism explicitly represent the context-sensitive dynamics of individual proteins driven by external inputs and represent protein-protein interactions as synchronised machine reconfigurations. Both deterministic and stochastic simulations can be applied to quantitatively compute the dynamics of MFA models. They apply the MFA formalism to model and simulate a simple example of a signal-transduction system that involves an MAP kinase cascade and a scaffold protein. PMID:21073243
Learning to construct pushdown automata for accepting deterministic context-free languages
NASA Astrophysics Data System (ADS)
Sen, Sandip; Janakiraman, Janani
1992-03-01
Genetic algorithms (GAs) are a class of probabilistic optimization algorithms which utilize ideas from natural genetics. In this paper, we apply the genetic algorithm to a difficult machine learning problem, viz., to learn the description of pushdown automata (PDA) to accept a context-free language (CFL), given legal and illegal sentences of the language. Previous work has involved the use of GAs in learning descriptions for finite state machines for accepting regular languages. CFLs are known to properly include regular languages, and hence, the learning problem addressed here is of a greater complexity. The ability to accept context free languages can be applied to a number of practical problems like text processing, speech recognition, etc.
Behavioral Modeling Based on Probabilistic Finite Automata: An Empirical Study †
Tîrnăucă, Cristina; Montaña, José L.; Ontañón, Santiago; González, Avelino J.; Pardo, Luis M.
2016-01-01
Imagine an agent that performs tasks according to different strategies. The goal of Behavioral Recognition (BR) is to identify which of the available strategies is the one being used by the agent, by simply observing the agent’s actions and the environmental conditions during a certain period of time. The goal of Behavioral Cloning (BC) is more ambitious. In this last case, the learner must be able to build a model of the behavior of the agent. In both settings, the only assumption is that the learner has access to a training set that contains instances of observed behavioral traces for each available strategy. This paper studies a machine learning approach based on Probabilistic Finite Automata (PFAs), capable of achieving both the recognition and cloning tasks. We evaluate the performance of PFAs in the context of a simulated learning environment (in this case, a virtual Roomba vacuum cleaner robot), and compare it with a collection of other machine learning approaches. PMID:27347956
Real-time extended interface automata for software testing cases generation.
Yang, Shunkun; Xu, Jiaqi; Man, Tianlong; Liu, Bin
2014-01-01
Testing and verification of the interface between software components are particularly important due to the large number of complex interactions, which requires the traditional modeling languages to overcome the existing shortcomings in the aspects of temporal information description and software testing input controlling. This paper presents the real-time extended interface automata (RTEIA) which adds clearer and more detailed temporal information description by the application of time words. We also establish the input interface automaton for every input in order to solve the problems of input controlling and interface covering nimbly when applied in the software testing field. Detailed definitions of the RTEIA and the testing cases generation algorithm are provided in this paper. The feasibility and efficiency of this method have been verified in the testing of one real aircraft braking system. PMID:24892080
Real-Time Extended Interface Automata for Software Testing Cases Generation
Yang, Shunkun; Xu, Jiaqi; Man, Tianlong; Liu, Bin
2014-01-01
Testing and verification of the interface between software components are particularly important due to the large number of complex interactions, which requires the traditional modeling languages to overcome the existing shortcomings in the aspects of temporal information description and software testing input controlling. This paper presents the real-time extended interface automata (RTEIA) which adds clearer and more detailed temporal information description by the application of time words. We also establish the input interface automaton for every input in order to solve the problems of input controlling and interface covering nimbly when applied in the software testing field. Detailed definitions of the RTEIA and the testing cases generation algorithm are provided in this paper. The feasibility and efficiency of this method have been verified in the testing of one real aircraft braking system. PMID:24892080
A Multi-Teacher Learning Automata Computing Model for Graph Partitioning Problems
NASA Astrophysics Data System (ADS)
Ikebo, Shigeya; Qian, Fei; Hirata, Hironori
Graph partitioning is an important problem that has extensive applications in many areas, including VLSI design, scientific computing, data mining, geographical information systems and job scheduling. The graph partitioning problem (GPP) is NP-complete. There are several heuristic algorithms developed finding a reasonably good resolution. The most famous partitioning methods are simulated annealing (SA) and mean field algorithm (MFA) known to produce good partition for a wide class of problems, and they are used quite extensively. However these methods are very expensive in time and very sensitive in parameters tuning methods. In this paper, a new parameter-free algorithm for GPP has been proposed. The algorithm has been constructed using the S-model learning automata with multi-teacher random environments. As shown in our experiments, the proposed algorithm has some advantages superior to SA, MFA and ParMeTiS.
Solving initial and boundary value problems using learning automata particle swarm optimization
NASA Astrophysics Data System (ADS)
Nemati, Kourosh; Mariyam Shamsuddin, Siti; Darus, Maslina
2015-05-01
In this article, the particle swarm optimization (PSO) algorithm is modified to use the learning automata (LA) technique for solving initial and boundary value problems. A constrained problem is converted into an unconstrained problem using a penalty method to define an appropriate fitness function, which is optimized using the LA-PSO method. This method analyses a large number of candidate solutions of the unconstrained problem with the LA-PSO algorithm to minimize an error measure, which quantifies how well a candidate solution satisfies the governing ordinary differential equations (ODEs) or partial differential equations (PDEs) and the boundary conditions. This approach is very capable of solving linear and nonlinear ODEs, systems of ordinary differential equations, and linear and nonlinear PDEs. The computational efficiency and accuracy of the PSO algorithm combined with the LA technique for solving initial and boundary value problems were improved. Numerical results demonstrate the high accuracy and efficiency of the proposed method.
Monadic structures over an ordered universal random graph and finite automata
NASA Astrophysics Data System (ADS)
Dudakov, Sergey M.
2011-10-01
We continue the investigation of the expressive power of the language of predicate logic for finite algebraic systems embedded in infinite systems. This investigation stems from papers of M. A. Taitslin, M. Benedikt and L. Libkin, among others. We study the properties of a finite monadic system which can be expressed by formulae if such a system is embedded in a random graph that is totally ordered in an arbitrary way. The Büchi representation is used to connect monadic structures and formal languages. It is shown that, if one restricts attention to formulae that are -invariant in totally ordered random graphs, then these formulae correspond to finite automata. We show that =-invariant formulae expressing the properties of the embedded system itself can express only Boolean combinations of properties of the form `the cardinality of an intersection of one-place predicates belongs to one of finitely many fixed finite or infinite arithmetic progressions'.
NASA Astrophysics Data System (ADS)
Endy, Drew; Brent, Roger
2001-01-01
Representations of cellular processes that can be used to compute their future behaviour would be of general scientific and practical value. But past attempts to construct such representations have been disappointing. This is now changing. Increases in biological understanding combined with advances in computational methods and in computer power make it possible to foresee construction of useful and predictive simulations of cellular processes.
NASA Technical Reports Server (NTRS)
Romanofsky, Robert R.
2010-01-01
The cellular reflectarray antenna is intended to replace conventional parabolic reflectors that must be physically aligned with a particular satellite in geostationary orbit. These arrays are designed for specified geographical locations, defined by latitude and longitude, each called a "cell." A particular cell occupies nominally 1,500 square miles (3,885 sq. km), but this varies according to latitude and longitude. The cellular reflectarray antenna designed for a particular cell is simply positioned to align with magnetic North, and the antenna surface is level (parallel to the ground). A given cellular reflectarray antenna will not operate in any other cell.
Michael H. L. S. Wang; Cancelo, Gustavo; Green, Christopher; Guo, Deyuan; Wang, Ke; Zmuda, Ted
2016-06-25
Here, we explore the Micron Automata Processor (AP) as a suitable commodity technology that can address the growing computational needs of pattern recognition in High Energy Physics (HEP) experiments. A toy detector model is developed for which an electron track confirmation trigger based on the Micron AP serves as a test case. Although primarily meant for high speed text-based searches, we demonstrate a proof of concept for the use of the Micron AP in a HEP trigger application.
Michael H. L. S. Wang; Cancelo, Gustavo; Green, Christopher; Guo, Deyuan; Wang, Ke; Zmuda, Ted
2016-06-25
Here, we explore the Micron Automata Processor (AP) as a suitable commodity technology that can address the growing computational needs of pattern recognition in High Energy Physics (HEP) experiments. A toy detector model is developed for which an electron track confirmation trigger based on the Micron AP serves as a test case. Although primarily meant for high speed text-based searches, we demonstrate a proof of concept for the use of the Micron AP in a HEP trigger application.
CELLULAR MAGNESIUM HOMEOSTASIS
Romani, Andrea M.P.
2011-01-01
Magnesium, the second most abundant cellular cation after potassium, is essential to regulate numerous cellular functions and enzymes, including ion channels, metabolic cycles, and signaling pathways, as attested by more than 1000 entries in the literature. Despite significant recent progress, however, our understanding of how cells regulate Mg2+ homeostasis and transport still remains incomplete. For example, the occurrence of major fluxes of Mg2+ in either direction across the plasma membrane of mammalian cells following metabolic or hormonal stimuli has been extensively documented. Yet, the mechanisms ultimately responsible for magnesium extrusion across the cell membrane have not been cloned. Even less is known about the regulation in cellular organelles. The present review is aimed at providing the reader with a comprehensive and up-to-date understanding of the mechanisms enacted by eukaryotic cells to regulate cellular Mg2+ homeostasis and how these mechanisms are altered under specific pathological conditions. PMID:21640700
Cellular automaton model considering the velocity effect of a car on the successive car.
Li, X; Wu, Q; Jiang, R
2001-12-01
In this paper we present a cellular automata model for one-lane traffic flow. The update rules of velocity of a car depend not only on the positions of this car and the car ahead of it, but also on the velocities of the two cars. Using computer simulations we obtain some basic qualitative results and the fundamental diagram of the proposed model. In comparison with those of the existing models in the literature, we find that the fundamental diagram of the proposed model is more consistent with the results measured in the real traffic, and the model is able to reproduce some relevant macroscopic states that are found in the real traffic flow but cannot be predicted by the existing models. PMID:11736257
Dynamical and critical behavior of a simple discrete model of the cellular immune system
NASA Astrophysics Data System (ADS)
Brass, A.; Bancroft, A. J.; Clamp, M. E.; Grencis, R. K.; Else, K. J.
1994-08-01
A simple cellular automata model has been constructed to investigate the interactions between the two T-helper subset cell types (TH1 and TH2) in a lymph node during chronic parasitic infection. The model exhibits behavior similar to a phase transition as a function of the antigenic burden placed on the host. At low antigen density the behavior of the model resembles that of a ``paramagnetic'' phase in which both T-helper cell subset cells can coexist. Above a threshold antigen density then one or other of the TH subset cells becomes dominant and forms a single, connected, infinite cluster (equivalent to a ``ferromagnetic'' phase). Much of the phenomenological behavior of the model is seen to be in good agreement with that observed in animal models of parasitic infection.