Shim, Jae Wan; Gatignol, Renée
2010-04-01
We show that the heat exchange between fluid particles and boundary walls can be achieved by controlling the velocity change rate following the particles' collision with a wall in discrete kinetic theory, such as the lattice-gas cellular automata and the lattice Boltzmann method. We derive a relation between the velocity change rate and temperature so that we can control the velocity change rate according to a given temperature boundary condition. This relation enables us to deal with the thermal boundary whose temperature varies along a wall in contrast to the previous works of the lattice-gas cellular automata. In addition, we present simulation results to compare our method to the existing and give an example in a microchannel with a high temperature gradient boundary condition by the lattice-gas cellular automata.
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.
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.
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.
1992-05-01
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.
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.
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.
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
Plasmonic Nanostructured Cellular Automata
NASA Astrophysics Data System (ADS)
Alkhazraji, Emad; Ghalib, A.; Manzoor, K.; Alsunaidi, M. A.
2017-03-01
In this work, we have investigated the scattering plasmonic resonance characteristics of silver nanospheres with a geometrical distribution that is modelled by Cellular Automata using time-domain numerical analysis. Cellular Automata are discrete mathematical structures that model different natural phenomena. Two binary one-dimensional Cellular Automata rules are considered to model the nanostructure, namely rule 30 and rule 33. The analysis produces three-dimensional scattering profiles of the entire plasmonic nanostructure. For the Cellular Automaton rule 33, the introduction of more Cellular Automata generations resulted only in slight red and blue shifts in the plasmonic modes with respect to the first generation. On the other hand, while rule 30 introduced significant red shifts in the resonance peaks at early generations, at later generations however, a peculiar effect is witnessed in the scattering profile as new peaks emerge as a feature of the overall Cellular Automata structure rather than the sum of the smaller parts that compose it. We strongly believe that these features that emerge as a result adopting the different 256 Cellular Automata rules as configuration models of nanostructures in different applications and systems might possess a great potential in enhancing their capability, sensitivity, efficiency, and power utilization.
A lattice gas cellular automaton approach to model volcanic eruptions
NASA Astrophysics Data System (ADS)
Sanchez, L.; Shcherbakov, R.
2011-12-01
Volcanic eruptions are the result of complex mechanisms that operate in a magma chamber within the crust. In a previous study, we showed that the dynamics of eruptions on Earth are the same and are quite independent of the location and type of volcanism. The goal of this study is to test the universality of volcanism by designing a simple, general model to simulate processes occurring within a magma chamber. We aim at reproducing the threshold behavior that operates in the magma chamber when pressure increase leads to an eruption. To simulate volcanic eruptions, we propose to use a lattice gas cellular automata (LGCA), which have been proven efficient to simulate fluid flow behavior. This type cellular automaton is a discrete dynamical model in space and time, where the fluid is represented at the microscopic level by discrete particles. We start with the simplest LGCA: the 2-dimensional HPP model (proposed in 1973 by Hardy, de Pazzis and Pomeau), which consists of a square lattice where particles interact with one another mimicking the fluid flow and conserving mass and momentum. We also consider the model on a hexagonal lattice to take anisotropy into account. In this model, magma propagates through a heterogeneous medium, and deformation and fracturing occurs on the walls of the chamber up until a pressure threshold is reached and an eruption or a cascade of eruptions occur. We record the size of each event and the number of time steps between consecutive events (or interevent time). The model simulation results for a large number of realizations are compared with observed data. The observations come from eruption records of 13 individual volcanoes located around the world as well as 11 groups of volcanoes located in various regions surrounded by different tectonic settings. From these, we computed the frequency-size distribution of eruptions and the interevent time distributions for a large number of active volcanoes on Earth. This model allows us to study a
What can we hope for from cellular automata?
NASA Astrophysics Data System (ADS)
Doolen, Gary
Although the idea of using discrete methods for modeling partial differential equations occured very early, the actual statement that cellular automata techniques can approximate the solutions of hydrodynamic partial differential equations was first discovered by Frisch, Hasslacher, and Pomeau. Their description of the derivation, which assumes the validity of the Boltzmann equation, appeared in the Physical Review Letters in April 1986. It is the intent of this article to provide a description of the simplest lattice gas model and to examine the successes and inadequacies of a lattice gas calculation of flow in a two-dimensional channel. Some comments will summarize a recent result of a lattice gas simulation of flow through porous media, a problem which is ideal for the lattice gas method. Finally, some remarks will be focused on the impressive speeds which could be obtained from a dedicated lattice gas computer.
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.
Knot Invariants and Cellular Automata
1993-05-04
lattice gases. Since our approach equates the spacetime evolution of a dynamical system with an equilibrium configuration of a statistical mechanics...model in one higher dimension, a model of ’t Hooft for two dimensional spacetime with discrete local coordinate invariance was a natural inspiration [5...thermodynamic equilibrium, as well as demonstrating the efficacy of constructing and analyzing lattice gas automata according to ( spacetime ) symmetry principles
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.
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.
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.
Magnetohydrodynamic cellular automata
NASA Technical Reports Server (NTRS)
Montgomery, David; Doolen, Gary D.
1987-01-01
A generalization of the hexagonal lattice gas model of Frisch, Hasslacher and Pomeau is shown to lead to two-dimensional magnetohydrodynamics. The method relies on the ideal point-wise conservation law for vector potential.
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
Mente, Carsten; Prade, Ina; Brusch, Lutz; Breier, Georg; Deutsch, Andreas
2011-07-01
Lattice-gas cellular automata (LGCAs) can serve as stochastic mathematical models for collective behavior (e.g. pattern formation) emerging in populations of interacting cells. In this paper, a two-phase optimization algorithm for global parameter estimation in LGCA models is presented. In the first phase, local minima are identified through gradient-based optimization. Algorithmic differentiation is adopted to calculate the necessary gradient information. In the second phase, for global optimization of the parameter set, a multi-level single-linkage method is used. As an example, the parameter estimation algorithm is applied to a LGCA model for early in vitro angiogenic pattern formation.
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…
Mente, Carsten; Voss-Böhme, Anja; Deutsch, Andreas
2015-04-01
Collective dynamics of migrating cell populations drive key processes in tissue formation and maintenance under normal and diseased conditions. Collective cell behavior at the tissue level is typically characterized by considering cell density patterns such as clusters and moving cell fronts. However, there are also important observables of collective dynamics related to individual cell behavior. In particular, individual cell trajectories are footprints of emergent behavior in populations of migrating cells. Lattice-gas cellular automata (LGCA) have proven successful to model and analyze collective behavior arising from interactions of migrating cells. There are well-established methods to analyze cell density patterns in LGCA models. Although LGCA dynamics are defined by cell-based rules, individual cells are not distinguished. Therefore, individual cell trajectories cannot be analyzed in LGCA so far. Here, we extend the classical LGCA framework to allow labeling and tracking of individual cells. We consider cell number conserving LGCA models of migrating cell populations where cell interactions are regulated by local cell density and derive stochastic differential equations approximating individual cell trajectories in LGCA. This result allows the prediction of complex individual cell trajectories emerging in LGCA models and is a basis for model-experiment comparisons at the individual cell level.
Classifying cellular automata using grossone
NASA Astrophysics Data System (ADS)
D'Alotto, Louis
2016-10-01
This paper proposes an application of the Infinite Unit Axiom and grossone, introduced by Yaroslav Sergeyev (see [7] - [12]), to the development and classification of one and two-dimensional cellular automata. By the application of grossone, new and more precise nonarchimedean metrics on the space of definition for one and two-dimensional cellular automata are established. These new metrics allow us to do computations with infinitesimals. Hence configurations in the domain space of cellular automata can be infinitesimally close (but not equal). That is, they can agree at infinitely many places. Using the new metrics, open disks are defined and the number of points in each disk computed. The forward dynamics of a cellular automaton map are also studied by defined sets. It is also shown that using the Infinite Unit Axiom, the number of configurations that follow a given configuration, under the forward iterations of cellular automaton maps, can now be computed and hence a classification scheme developed based on this computation.
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.
Cellular Automata Methods in Mathematical Physics.
NASA Astrophysics Data System (ADS)
Smith, Mark Andrew
Cellular automata (CA) are fully discrete, spatially -distributed dynamical systems which can serve as an alternative framework for mathematical descriptions of physical systems. Furthermore, they constitute intrinsically parallel models of computation which can be efficiently realized with special-purpose cellular automata machines. The basic objective of this thesis is to determine techniques for using CA to model physical phenomena and to develop the associated mathematics. Results may take the form of simulations and calculations as well as proofs, and applications are suggested throughout. We begin by describing the structure, origins, and modeling categories of CA. A general method for incorporating dissipation in a reversible CA rule is suggested by a model of a lattice gas in the presence of an external potential well. Statistical forces are generated by coupling the gas to a low temperature heat bath. The equilibrium state of the coupled system is analyzed using the principle of maximum entropy. Continuous symmetries are important in field theory, whereas CA describe discrete fields. However, a novel CA rule for relativistic diffusion based on a random walk shows how Lorentz invariance can arise in a lattice model. Simple CA models based on the dynamics of abstract atoms are often capable of capturing the universal behaviors of complex systems. Consequently, parallel lattice Monte Carlo simulations of abstract polymers were devised to respect the steric constraints on polymer dynamics. The resulting double space algorithm is very efficient and correctly captures the static and dynamic scaling behavior characteristic of all polymers. Random numbers are important in stochastic computer simulations; for example, those that use the Metropolis algorithm. A technique for tuning random bits is presented to enable efficient utilization of randomness, especially in CA machines. Interesting areas for future CA research include network simulation, long-range forces
NASA Astrophysics Data System (ADS)
Alber, Mark S.; Kiskowski, Maria; Jiang, Yi; Newman, Stuart
Modelling pattern formation and morphogenesis are fundamental problems in biology. One useful approach is lattice gas cellular automata (LGCA) model. This paper reviews several stochastic lattice gas models for pattern formation in myxobacteria fruiting body morphogenesis and vertebrate limb skeletogenesis. The fruiting body formation in myxobacteria is a complex morphological process that requires the organized, collective effort of tens of thousands of cells. It provides new insight into collective microbial behavior since myxobacteria morphogenic pattern formation is governed by cell-cell interactions rather than chemotaxis. We describe LGCA models for the aggregation stage of the fruiting body formation. Limb bud precartilage mesenchymal cells in micromass culture undergo chondrogenic pattern formation, which results in the formation of regularly-spaced "islands" of cartilage analogous to the cartilage primordia of the developing limb skeleton. An LGCA model, based on reaction-diffusion coupling and cell-matrix adhesion, is described for this process.
Cellular automata for traffic simulations
NASA Astrophysics Data System (ADS)
Wolf, Dietrich E.
1999-02-01
Traffic phenomena such as the transition from free to congested flow, lane inversion and platoon formation can be accurately reproduced using cellular automata. Being computationally extremely efficient, they simulate large traffic systems many times faster than real time so that predictions become feasible. A riview of recent results is given. The presence of metastable states at the jamming transition is discussed in detail. A simple new cellular automation is introduced, in which the interaction between cars is Galilei-invariant. It is shown that this type of interaction accounts for metastable states in a very natural way.
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.
Ultradiscrete Systems (Cellular Automata)
NASA Astrophysics Data System (ADS)
Tokihiro, Tetsuji
Ultradiscretization is a limiting procedure which allows one to obtain a cellular automaton (CA) from continuous equations. Using this method, we can construct integrable CAs from integrable partial difference equations. In this course, we focus on a typical integrable CA, called a Box and Ball system (BBS), and review its peculiar features. Since a BBS is an ultradiscrete limit of the discrete KP equation and discrete Toda equation, we can obtain explicit solutions and conserved quantities for the BBS. Furthermore the BBS is also regarded as a limit (crystallization) of an integrable lattice model. Recent topics, and a periodic BBS in particular are also reviewed.
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.
Simulation of two-phase flow using lattice gas automata methods
Tsumaya, Akira; Ohashi, Hirotada; Akiyama, Mamoru
1996-08-01
Two-phase flow simulation has been primarily based on experimental data in the sense that constitutive relations necessary for solving fundamental equations are experimentally determined. This assures validity of simulation of two-phase flow within the experimental conditions, but it is difficult to predict the behavior of two-phase flow under extreme or complex conditions which occur, for example, in severe accidents of nuclear reactors. Lattice gas automaton (LGA) simulation has recently attracted attention as a method for numerical simulation of multi phase flow. The authors extend phase-separation LGA models and develop methods for two-phase flow simulation. First, they newly added a flow model to the immiscible lattice gas model and applied it to two-dimensional Poiseuille flow. They obtained a result looking like lubricated pipelining of crude oil with water. Also, considering the gravity effect, they introduced a buoyancy force into the liquid-gas model. As a result, they demonstrated that gas bubbles of various diameters rise and gradually coalesce each other turning into larger bubbles. Using these newly developed LGA models, they succeeded in simulating various flow patterns of two-phase flow.
Reversibility of a Symmetric Linear Cellular Automata
NASA Astrophysics Data System (ADS)
Del Rey, A. Martín; Sánchez, G. Rodríguez
The characterization of the size of the cellular space of a particular type of reversible symmetric linear cellular automata is introduced in this paper. Specifically, it is shown that those symmetric linear cellular with 2k + 1 cells, and whose transition matrix is a k-diagonal square band matrix with nonzero entries equal to 1 are reversible. Furthermore, in this case the inverse cellular automata are explicitly computed. Moreover, the reversibility condition is also studied for a general number of cells.
Lattice-Gas Automata for the Problem Of Kinetic Theory of Gas During Free Expansion
NASA Astrophysics Data System (ADS)
Khotimah, Siti Nurul; Arif, Idam; Liong, The Houw
The lattice-gas method has been applied to solve the problem of kinetic theory of gas in the Gay-Lussac-Joule experiment. Numerical experiments for a two-dimensional gas were carried out to determine the number of molecules in one vessel (Nr), the ratio between the mean square values of the components of molecule velocity (/line{vx2}//line{v_y^2}), and the change in internal energy (ΔU) as a function of time during free expansion. These experiments were repeated for different sizes of an aperture in the partition between the two vessels. After puncturing the partition, the curve for the particle number in one vessel shows a damped oscillation for about half of the total number. The oscillations do not vanish after a sampling over different initial configurations. The system is in nonequilibrium due to the pressure equilibration, and here the flow is actually compressible. The equilibration time (in time steps) decreases with decreased size of aperture in the partition. For very small apertures (equal or less than 9{√{3}}/{2} lattice units), the number of molecules in one vessel changes with time in a smooth way until it reaches half of the total number; their curves obey the analytical solution for quasi-static processes. The calculations on /line{vx2}//line{v_y^2} and ΔU also support the results that the equilibration time decreases with decreased size of aperture in the partition.
NASA Astrophysics Data System (ADS)
Snider, Gregory
2000-03-01
Quantum-dot Cellular Automata (QCA) [1] is a promising architecture which employs quantum dots for digital computation. It is a revolutionary approach that holds the promise of high device density and low power dissipation. A basic QCA cell consists of four quantum dots coupled capacitively and by tunnel barriers. The cell is biased to contain two excess electrons within the four dots, which are forced to opposite "corners" of the four-dot cell by mutual Coulomb repulsion. These two possible polarization states of the cell will represent logic "0" and "1". Properly arranged, arrays of these basic cells can implement Boolean logic functions. Experimental results from functional QCA devices built of nanoscale metal dots defined by tunnel barriers will be presented. The experimental devices to be presented consist of Al islands, which we will call quantum dots, interconnected by tunnel junctions and lithographically defined capacitors. Aluminum/ aluminum-oxide/aluminum tunnel junctions were fabricated using a standard e-beam lithography and shadow evaporation technique. The experiments were performed in a dilution refrigerator at a temperature of 70 mK. The operation of a cell is evaluated by direct measurements of the charge state of dots within a cell as the input voltage is changed. The experimental demonstration of a functioning cell will be presented. A line of three cells demonstrates that there are no metastable switching states in a line of cells. A QCA majority gate will also be presented, which is a programmable AND/OR gate and represents the basic building block of QCA systems. The results of recent experiments will be presented. 1. C.S. Lent, P.D. Tougaw, W. Porod, and G.H. Bernstein, Nanotechnology, 4, 49 (1993).
Cellular Automata Simulation for Wealth Distribution
NASA Astrophysics Data System (ADS)
Lo, Shih-Ching
2009-08-01
Wealth distribution of a country is a complicate system. A model, which is based on the Epstein & Axtell's "Sugars cape" model, is presented in Netlogo. The model considers the income, age, working opportunity and salary as control variables. There are still other variables should be considered while an artificial society is established. In this study, a more complicate cellular automata model for wealth distribution model is proposed. The effects of social welfare, tax, economical investment and inheritance are considered and simulated. According to the cellular automata simulation for wealth distribution, we will have a deep insight of financial policy of the government.
Fuzzy cellular automata models in immunology
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.
Symmetric Fractals Generated by Cellular Automata
2000-01-01
configuration is, e.g., rotationally symmetric. If is a regular k-invariant of A0, then 6(E fiX j) gives anther top row of a 0-configuration of size kN; what...Technology and Culture (JUAP P4-02). References 1. J.-P. Allouche, F. von Haeseler, E. Lange, A. Petersen, G. Skordev. Linear cellular automata and
Cellular automata in photonic cavity arrays.
Li, Jing; Liew, T C H
2016-10-31
We propose theoretically a photonic Turing machine based on cellular automata in arrays of nonlinear cavities coupled with artificial gauge fields. The state of the system is recorded making use of the bistability of driven cavities, in which losses are fully compensated by an external continuous drive. The sequential update of the automaton layers is achieved automatically, by the local switching of bistable states, without requiring any additional synchronization or temporal control.
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.
Cellular Automata Model of Cardiac Pacemaker
NASA Astrophysics Data System (ADS)
Makowiec, D.
2008-05-01
A network of Greenberg-Hasting cellular automata with cyclic intrinsic dynamics F rightarrow R rightarrow A rightarrow F rightarrow ... is shown to be a reliable approximation to the cardiac pacemaker. The three possible cell's states F, R, A are characterized by fixed timings { nF, nR, nA } -- time steps spent in each state. Dynamical properties of a simple line network are found to be critical with respect to the relation between nF and nR. The properties of a network arisen from a square lattice where some edges are rewired (locally and with the preference to link to cells which are more connected to other cells) are also studied. The resulted system evolves rhythmically with the period determined by timings. The emergence of a small group of neighboring automata where the whole system activity initiates is observed. The dominant evolution is accompanied with other rhythms, characterized by longer periods.
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.
Scalable asynchronous execution of cellular automata
NASA Astrophysics Data System (ADS)
Folino, Gianluigi; Giordano, Andrea; Mastroianni, Carlo
2016-10-01
The performance and scalability of cellular automata, when executed on parallel/distributed machines, are limited by the necessity of synchronizing all the nodes at each time step, i.e., a node can execute only after the execution of the previous step at all the other nodes. However, these synchronization requirements can be relaxed: a node can execute one step after synchronizing only with the adjacent nodes. In this fashion, different nodes can execute different time steps. This can be a notable advantageous in many novel and increasingly popular applications of cellular automata, such as smart city applications, simulation of natural phenomena, etc., in which the execution times can be different and variable, due to the heterogeneity of machines and/or data and/or executed functions. Indeed, a longer execution time at a node does not slow down the execution at all the other nodes but only at the neighboring nodes. This is particularly advantageous when the nodes that act as bottlenecks vary during the application execution. The goal of the paper is to analyze the benefits that can be achieved with the described asynchronous implementation of cellular automata, when compared to the classical all-to-all synchronization pattern. The performance and scalability have been evaluated through a Petri net model, as this model is very useful to represent the synchronization barrier among nodes. We examined the usual case in which the territory is partitioned into a number of regions, and the computation associated with a region is assigned to a computing node. We considered both the cases of mono-dimensional and two-dimensional partitioning. The results show that the advantage obtained through the asynchronous execution, when compared to the all-to-all synchronous approach is notable, and it can be as large as 90% in terms of speedup.
Scaling behavior in probabilistic neuronal cellular automata.
Manchanda, Kaustubh; Yadav, Avinash Chand; Ramaswamy, Ramakrishna
2013-01-01
We study a neural network model of interacting stochastic discrete two-state cellular automata on a regular lattice. The system is externally tuned to a critical point which varies with the degree of stochasticity (or the effective temperature). There are avalanches of neuronal activity, namely, spatially and temporally contiguous sites of activity; a detailed numerical study of these activity avalanches is presented, and single, joint, and marginal probability distributions are computed. At the critical point, we find that the scaling exponents for the variables are in good agreement with a mean-field theory.
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.
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.
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.
A cellular automata model of bone formation.
Van Scoy, Gabrielle K; George, Estee L; Opoku Asantewaa, Flora; Kerns, Lucy; Saunders, Marnie M; Prieto-Langarica, Alicia
2017-04-01
Bone remodeling is an elegantly orchestrated process by which osteocytes, osteoblasts and osteoclasts function as a syncytium to maintain or modify bone. On the microscopic level, bone consists of cells that create, destroy and monitor the bone matrix. These cells interact in a coordinated manner to maintain a tightly regulated homeostasis. It is this regulation that is responsible for the observed increase in bone gain in the dominant arm of a tennis player and the observed increase in bone loss associated with spaceflight and osteoporosis. The manner in which these cells interact to bring about a change in bone quality and quantity has yet to be fully elucidated. But efforts to understand the multicellular complexity can ultimately lead to eradication of metabolic bone diseases such as osteoporosis and improved implant longevity. Experimentally validated mathematical models that simulate functional activity and offer eventual predictive capabilities offer tremendous potential in understanding multicellular bone remodeling. Here we undertake the initial challenge to develop a mathematical model of bone formation validated with in vitro data obtained from osteoblastic bone cells induced to mineralize and quantified at 26 days of culture. A cellular automata model was constructed to simulate the in vitro characterization. Permutation tests were performed to compare the distribution of the mineralization in the cultures and the distribution of the mineralization in the mathematical models. The results of the permutation test show the distribution of mineralization from the characterization and mathematical model come from the same probability distribution, therefore validating the cellular automata model.
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.
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.
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.
Chua's Nonlinear Dynamics Perspective of Cellular Automata
NASA Astrophysics Data System (ADS)
Pazienza, Giovanni E.
2013-01-01
Chua's `Nonlinear Dynamics Perspective of Cellular Automata' represents a genuine breakthrough in this area and it has had a major impact on the recent scientific literature. His results have been accurately described in a series of fourteen papers appeared over the course of eight years but there is no compendious introduction to his work. Therefore, here for the first time, we present Chua's main ideas as well as a few unpublished results that have not been included in his previous papers. This overview illustrates the essence of Chua's work by using a clear terminology and a consistent notation, and it is aimed at those who want to approach this subject through a concise but thorough exposition.
Using cellular automata to generate image representation for biological sequences.
Xiao, X; Shao, S; Ding, Y; Huang, Z; Chen, X; Chou, K-C
2005-02-01
A novel approach to visualize biological sequences is developed based on cellular automata (Wolfram, S. Nature 1984, 311, 419-424), a set of discrete dynamical systems in which space and time are discrete. By transforming the symbolic sequence codes into the digital codes, and using some optimal space-time evolvement rules of cellular automata, a biological sequence can be represented by a unique image, the so-called cellular automata image. Many important features, which are originally hidden in a long and complicated biological sequence, can be clearly revealed thru its cellular automata image. With biological sequences entering into databanks rapidly increasing in the post-genomic era, it is anticipated that the cellular automata image will become a very useful vehicle for investigation into their key features, identification of their function, as well as revelation of their "fingerprint". It is anticipated that by using the concept of the pseudo amino acid composition (Chou, K.C. Proteins: Structure, Function, and Genetics, 2001, 43, 246-255), the cellular automata image approach can also be used to improve the quality of predicting protein attributes, such as structural class and subcellular location.
Simple derivation of the Weyl and Dirac quantum cellular automata
NASA Astrophysics Data System (ADS)
Raynal, Philippe
2017-06-01
We consider quantum cellular automata on a body-centered cubic lattice and provide a simple derivation of the only two homogenous, local, isotropic, and unitary two-dimensional automata [G. M. D'Ariano and P. Perinotti, Phys. Rev. A 90, 062106 (2014), 10.1103/PhysRevA.90.062106]. Our derivation relies on the notion of Gram matrix and emphasizes the link between the transition matrices that characterize the automata and the body-centered cubic lattice: The transition matrices essentially are the matrix representation of the vertices of the lattice's primitive cell. As expected, the dynamics of these two automata reduce to the Weyl equation in the limit of small wave vectors and continuous time. We also briefly examine the four-dimensional case, where we find two one-parameter families of automata that reduce to the Dirac equation in a suitable limit.
On the topological sensitivity of cellular automata.
Baetens, Jan M; De Baets, Bernard
2011-06-01
Ever since the conceptualization of cellular automata (CA), much attention has been paid to the dynamical properties of these discrete dynamical systems, and, more in particular, to their sensitivity to the initial condition from which they are evolved. Yet, the sensitivity of CA to the topology upon which they are based has received only minor attention, such that a clear insight in this dependence is still lacking and, furthermore, a quantification of this so-called topological sensitivity has not yet been proposed. The lack of attention for this issue is rather surprising since CA are spatially explicit, which means that their dynamics is directly affected by their topology. To overcome these shortcomings, we propose topological Lyapunov exponents that measure the divergence of two close trajectories in phase space originating from a topological perturbation, and we relate them to a measure grasping the sensitivity of CA to their topology that relies on the concept of topological derivatives, which is introduced in this paper. The validity of the proposed methodology is illustrated for the 256 elementary CA and for a family of two-state irregular totalistic CA.
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.
On the topological sensitivity of cellular automata
NASA Astrophysics Data System (ADS)
Baetens, Jan M.; De Baets, Bernard
2011-06-01
Ever since the conceptualization of cellular automata (CA), much attention has been paid to the dynamical properties of these discrete dynamical systems, and, more in particular, to their sensitivity to the initial condition from which they are evolved. Yet, the sensitivity of CA to the topology upon which they are based has received only minor attention, such that a clear insight in this dependence is still lacking and, furthermore, a quantification of this so-called topological sensitivity has not yet been proposed. The lack of attention for this issue is rather surprising since CA are spatially explicit, which means that their dynamics is directly affected by their topology. To overcome these shortcomings, we propose topological Lyapunov exponents that measure the divergence of two close trajectories in phase space originating from a topological perturbation, and we relate them to a measure grasping the sensitivity of CA to their topology that relies on the concept of topological derivatives, which is introduced in this paper. The validity of the proposed methodology is illustrated for the 256 elementary CA and for a family of two-state irregular totalistic CA.
Quantum models as classical cellular automata
NASA Astrophysics Data System (ADS)
Elze, Hans-Thomas
2017-05-01
A synopsis is offered of the properties of discrete and integer-valued, hence “natural”, cellular automata (CA). A particular class comprises the “Hamiltonian CA” with discrete updating rules that resemble Hamilton’s equations. The resulting dynamics is linear like the 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 l. Consequently, there is a one-to-one correspondence of quantum mechanical and CA conservation laws. We discuss the important issue of linearity, recalling that nonlinearities imply nonlocal effects in the continuous quantum mechanical description of intrinsically local discrete CA - requiring locality entails linearity. The admissible CA observables and the existence of solutions of the l-dependent dispersion relation for stationary states are mentioned, besides the construction of multipartite CA obeying the Superposition Principle. We point out problems when trying to match the deterministic CA here to those envisioned in ‘t Hooft’s CA Interpretation of Quantum Mechanics.
2006-05-31
methods. LBE is a generalization of LGA, where single- particle distributions are encoded directly using real numbers. The simulation dynamics is driven...local cellular automaton rule (A.14) does not explicitly show any mixing of particle flow directions. That fact that (A.14) does represent collisional ... dynamics simulation , provides the researcher with complete system de- tails not obtainable by either empirical or analytical treatments. LGA as a
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.
NASA Astrophysics Data System (ADS)
Wolnik, Barbara; Dembowski, Marcin; Bołt, Witold; Baetens, Jan M.; De Baets, Bernard
2017-08-01
The focus of this paper is on the density classification problem in the context of affine continuous cellular automata. Although such cellular automata cannot solve this problem in the classical sense, most density-conserving affine continuous cellular automata with a unit neighborhood radius are valid solutions of a slightly relaxed version of this problem. This result follows from a detailed study of the dynamics of the density-conserving affine continuous cellular automata that we introduce.
Simulation of interdiffusion and voids growth based on cellular automata
NASA Astrophysics Data System (ADS)
Zhang, Fan; Zhang, Boyan; Zhang, Nan; Du, Haishun; Zhang, Xinhong
2017-02-01
In the interdiffusion of two solid-state materials, if the diffusion coefficients of the two materials are not the same, the interface of the two materials will shift to the material with the lower diffusion coefficient. This effect is known as the Kirkendall effect. The Kirkendall effect leads to Kirkendall porosity. The pores act as sinks for vacancies and become voids. In this paper, the movement of the Kirkendall plane at interdiffusion is simulated based on cellular automata. The number of vacancies, the critical radius of voids nucleation and the nucleation rate are analysed. The vacancies diffusion, vacancies aggregation and voids growth are also simulated based on cellular automata.
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.
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.
Origin of complexity and conditional predictability in cellular automata.
García-Morales, Vladimir
2013-10-01
A simple mechanism for the emergence of complexity in cellular automata out of predictable dynamics is described. This leads to introduce the concept of conditional predictability for systems whose trajectory can only be piecewise known. The mechanism is used to construct a cellular automaton model for discrete chimeralike states, where synchrony and incoherence in an ensemble of identical oscillators coexist. The incoherent region is shown to have a periodicity that is three orders of magnitude longer than the period of the synchronous oscillation.
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.
Towards the simplest hydrodynamic lattice-gas model.
Boghosian, Bruce M; Love, Peter J; Meyer, David A
2002-03-15
It has been known since 1986 that it is possible to construct simple lattice-gas cellular automata whose hydrodynamics are governed by the Navier-Stokes equations in two dimensions. The simplest such model heretofore known has six bits of state per site on a triangular lattice. In this work, we demonstrate that it is possible to construct a model with only five bits of state per site on a Kagome lattice. Moreover, the model has a simple, deterministic set of collision rules and is easily implemented on a computer. In this work, we derive the equilibrium distribution function for this lattice-gas automaton and carry out the Chapman-Enskog analysis to determine the form of the Navier-Stokes equations.
Quantum cellular automata and free quantum field theory
NASA Astrophysics Data System (ADS)
D'Ariano, Giacomo Mauro; Perinotti, Paolo
2017-02-01
In a series of recent papers [1-4] it has been shown how free quantum field theory can be derived without using mechanical primitives (including space-time, special relativity, quantization rules, etc.), but only considering the easiest quantum algorithm encompassing a countable set of quantum systems whose network of interactions satisfies the simple principles of unitarity, homogeneity, locality, and isotropy. This has opened the route to extending the axiomatic information-theoretic derivation of the quantum theory of abstract systems [5, 6] to include quantum field theory. The inherent discrete nature of the informational axiomatization leads to an extension of quantum field theory to a quantum cellular automata theory, where the usual field theory is recovered in a regime where the discrete structure of the automata cannot be probed. A simple heuristic argument sets the scale of discreteness to the Planck scale, and the customary physical regime where discreteness is not visible is the relativistic one of small wavevectors. In this paper we provide a thorough derivation from principles that in the most general case the graph of the quantum cellular automaton is the Cayley graph of a finitely presented group, and showing how for the case corresponding to Euclidean emergent space (where the group resorts to an Abelian one) the automata leads to Weyl, Dirac and Maxwell field dynamics in the relativistic limit. We conclude with some perspectives towards the more general scenario of non-linear automata for interacting quantum field theory.
Long-range correlations in chaotic cellular automata
NASA Astrophysics Data System (ADS)
Eisele, Michael
1991-03-01
One-dimensional cellular automata of class 3 are studied as models for spatially extended, chaotic systems. Their irreversible dynamics can generate weak, but long-range spatial correlations. The one labelled 22 by Wolfram is treated in an exemplary way. Its stationary state is approximated by a Markov chain. The regular grammar underlying the Markov chain is chosen with care, so that it includes a maximum amount of information on the stationary state. The approximation can be performed without simulating the dynamics of the cellular automaton 22 and reproduces its long-range correlations qualitatively. Their origin is explained intuitively and they are argued to be a frequent feature of cellular automata with more complicated rules.
Cellular automata and its applications in protein bioinformatics.
Xiao, Xuan; Wang, Pu; Chou, Kuo-Chen
2011-09-01
With the explosion of protein sequences generated in the postgenomic era, it is highly desirable to develop high-throughput tools for rapidly and reliably identifying various attributes of uncharacterized proteins based on their sequence information alone. The knowledge thus obtained can help us timely utilize these newly found protein sequences for both basic research and drug discovery. Many bioinformatics tools have been developed by means of machine learning methods. This review is focused on the applications of a new kind of science (cellular automata) in protein bioinformatics. A cellular automaton (CA) is an open, flexible and discrete dynamic model that holds enormous potentials in modeling complex systems, in spite of the simplicity of the model itself. Researchers, scientists and practitioners from different fields have utilized cellular automata for visualizing protein sequences, investigating their evolution processes, and predicting their various attributes. Owing to its impressive power, intuitiveness and relative simplicity, the CA approach has great potential for use as a tool for bioinformatics.
Potential field cellular automata model for pedestrian flow.
Zhang, Peng; Jian, Xiao-Xia; Wong, S C; Choi, Keechoo
2012-02-01
This paper proposes a cellular automata model of pedestrian flow that defines a cost potential field, which takes into account the costs of travel time and discomfort, for a pedestrian to move to an empty neighboring cell. The formulation is based on a reconstruction of the density distribution and the underlying physics, including the rule for resolving conflicts, which is comparable to that in the floor field cellular automaton model. However, we assume that each pedestrian is familiar with the surroundings, thereby minimizing his or her instantaneous cost. This, in turn, helps reduce the randomness in selecting a target cell, which improves the existing cellular automata modelings, together with the computational efficiency. In the presence of two pedestrian groups, which are distinguished by their destinations, the cost distribution for each group is magnified due to the strong interaction between the two groups. As a typical phenomenon, the formation of lanes in the counter flow is reproduced.
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.
A class of cellular automata modeling winnerless competition
NASA Astrophysics Data System (ADS)
Afraimovich, V.; Ordaz, F. C.; Urías, J.
2002-06-01
Neural units introduced by Rabinovich et al. ("Sensory coding with dynamically competitive networks," UCSD and CIT, February 1999) motivate a class of cellular automata (CA) where spatio-temporal encoding is feasible. The spatio-temporal information capacity of a CA is estimated by the information capacity of the attractor set, which happens to be finitely specified. Two-dimensional CA are studied in detail. An example is given for which the attractor is not a subshift.
Physics of Cellular Automata and Quantum Dots Workshop
1990-11-02
Office of Naval Research Workshop The purpose of the workshop was to bring together a select group of physicists and computer ’ scientists to discuss...methods of domesticating quantum ’ dots-’for computational purposes. There are a variety of ways of constructing with modern lithography two- dimensional...case, the arrays to date have been limited to two dimensions, or planar technology. Cellular automata provide a computing paradigm where uniform arrays
The adaptive cruise control vehicles in the cellular automata model
NASA Astrophysics Data System (ADS)
Jiang, Rui; Wu, Qing-Song
2006-11-01
This Letter presented a cellular automata model where the adaptive cruise control vehicles are modelled. In this model, the constant time headway policy is adopted. The fundamental diagram is presented. The simulation results are in good agreement with the analytical ones. The mixture of ACC vehicles with manually driven vehicles is investigated. It is shown that with the introduction of ACC vehicles, the jam can be suppressed.
Massive Cellular Automata in Geosimulation: Antarctica Ice Melting as Example
NASA Astrophysics Data System (ADS)
Lan, H.; Torrens, P.; Lin, J.; Han, R.
2015-12-01
One of the essential features of the cellular automata (CA) model is its high scalability: CA lattices can be theoretically run at gargantuan size to represent intricacies of complex phenomena. However, one barrier in the use of cellular automata for scientific simulations is the issue of scalability in terms of the number of cells, to either model phenomena at finer granularities or at larger scales. Some researchers have developed parallel CA algorithms using MapReduce to eke out efficiency, but MapReduce may not provide the ideal scheme to address messy parallelism in large CA when they require complex rule-sets and broker a lot of state exchange across large solution-space lattices. In this research, we take advantage of the Bulk Synchronous Parallel (BSP) model of distributed computation, via the Giraph open-source implementation, to implement large-scale cellular automata simulations. Additionally, this study also describes a scientifically interesting example, in which ice dynamics in Antarctic is simulated using a melting model. Short-term and medium-term ice sheet dynamics are driven by a variety of forces. We do not fully understand what they might be and how they interplay, and simulation is an important medium for building the science to guide us in finding answers. In our experiments, using a voxel CA comprising 1 trillion cells—by far the largest scale voxel-based CA model reported in literature—which took only 2.48 minutes for per step for processing.
A full computation-relevant topological dynamics classification of elementary cellular automata.
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."
Immune Responses: Getting Close to Experimental Results with Cellular Automata Models
NASA Astrophysics Data System (ADS)
Dos Santos, Rita Maria Zorzenon
Cellular automata approaches are powerful tools to model local and nonlocal interactions generating cooperative behavior. In the last decade, the question of whether cellular automata could embed realistic assumptions about the interactions among cells and molecules of the immune system was quite controversial. Recent results have shown that it is possible to use cellular automata approaches to describe realistically the interactions between the elements of the immune system. The first models using cellular automata approaches, boolean and threshold or window automata, were based on experimental evidence and were mainly used to understand the logic of global immune responses like immunization, tolerance, paralysis, etc. Recently, new classes of cellular automata models which include time delay, stochasticity or adaptation have lead to results that can be compared with in vivo experimental data.
Noisy Quantum Cellular Automata for Quantum versus Classical Excitation Transfer
NASA Astrophysics Data System (ADS)
Avalle, Michele; Serafini, Alessio
2014-05-01
We introduce a class of noisy quantum cellular automata on a qubit lattice that includes all classical Markov chains, as well as maps where quantum coherence between sites is allowed to build up over time. We apply such a construction to the problem of excitation transfer through 1D lattices, and compare the performance of classical and quantum dynamics with equal local transition probabilities. Our discrete approach has the merits of stripping down the complications of the open system dynamics, of clearly isolating coherent effects, and of allowing for an exact treatment of conditional dynamics, all while capturing a rich variety of dynamical behaviors.
Noisy quantum cellular automata for quantum versus classical excitation transfer.
Avalle, Michele; Serafini, Alessio
2014-05-02
We introduce a class of noisy quantum cellular automata on a qubit lattice that includes all classical Markov chains, as well as maps where quantum coherence between sites is allowed to build up over time. We apply such a construction to the problem of excitation transfer through 1D lattices, and compare the performance of classical and quantum dynamics with equal local transition probabilities. Our discrete approach has the merits of stripping down the complications of the open system dynamics, of clearly isolating coherent effects, and of allowing for an exact treatment of conditional dynamics, all while capturing a rich variety of dynamical behaviors.
A Cellular Automata Model of Infection Control on Medical Implants.
Prieto-Langarica, Alicia; Kojouharov, Hristo; Chen-Charpentier, Benito; Tang, Liping
2011-06-01
S. epidermidis infections on medically implanted devices are a common problem in modern medicine due to the abundance of the bacteria. Once inside the body, S. epidermidis gather in communities called biofilms and can become extremely hard to eradicate, causing the patient serious complications. We simulate the complex S. epidermidis-Neutrophils interactions in order to determine the optimum conditions for the immune system to be able to contain the infection and avoid implant rejection. Our cellular automata model can also be used as a tool for determining the optimal amount of antibiotics for combating biofilm formation on medical implants.
Modeling STOCK Market Based on Genetic Cellular Automata
NASA Astrophysics Data System (ADS)
Zhou, Tao; Zhou, Pei-Ling; Wang, Bing-Hong; Tang, Zi-Nan; Liu, Jun
An artificial stock market is established with the modeling method and ideas of cellular automata. Cells are used to represent stockholders, who have the capability of self-teaching and are affected by the investing history of the neighboring ones. The neighborhood relationship among the stockholders is the expanded Von Neumann relationship, and the interaction among them is realized through selection operator and crossover operator. Experiment shows that the large events are frequent in the fluctuations of the stock price generated by the artificial stock market when compared with a normal process and the price returns distribution is a Lévy distribution in the central part followed by an approximately exponential truncation.
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.
Emergence of linguistic-like structures in one-dimensional cellular automata
NASA Astrophysics Data System (ADS)
Bertacchini, Francesca; Bilotta, Eleonora; Caldarola, Fabio; Pantano, Pietro; Bustamante, Leonardo Renteria
2016-10-01
In this paper we give a summary of some empirical investigations which show high analogies between Cellular Automata and linguistic structures. In particular we show as coupling regular domains of Cellular Automata we find complex emerging structures similar to combination of words, phonemes and morphemes in natural languages.
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.
A novel cellular automata based approach to storm sewer design
NASA Astrophysics Data System (ADS)
Guo, Y.; Walters, G. A.; Khu, S. T.; Keedwell, E.
2007-04-01
Optimal storm sewer design aims at minimizing capital investment on infrastructure whilst ensuring good system performance under specified design criteria. An innovative sewer design approach based on cellular automata (CA) principles is introduced in this paper. Cellular automata have been applied as computational simulation devices in various scientific fields. However, some recent research has indicated that CA can also be a viable and efficient optimization engine. This engine is heuristic and largely relies on the key properties of CA: locality, homogeneity, and parallelism. In the proposed approach, the CA-based optimizer is combined with a sewer hydraulic simulator, the EPA Storm Water Management Model (SWMM). At each optimization step, according to a set of transition rules, the optimizer updates all decision variables simultaneously based on the hydraulic situation within each neighbourhood. Two sewer networks (one small artificial network and one large real network) have been tested in this study. The CA optimizer demonstrated its ability to obtain near-optimal solutions in a remarkably small number of computational steps in a comparison of its performance with that of a genetic algorithm.
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.
Resolution scalable image coding with reversible cellular automata.
Cappellari, Lorenzo; Milani, Simone; Cruz-Reyes, Carlos; Calvagno, Giancarlo
2011-05-01
In a resolution scalable image coding algorithm, a multiresolution representation of the data is often obtained using a linear filter bank. Reversible cellular automata have been recently proposed as simpler, nonlinear filter banks that produce a similar representation. The original image is decomposed into four subbands, such that one of them retains most of the features of the original image at a reduced scale. In this paper, we discuss the utilization of reversible cellular automata and arithmetic coding for scalable compression of binary and grayscale images. In the binary case, the proposed algorithm that uses simple local rules compares well with the JBIG compression standard, in particular for images where the foreground is made of a simple connected region. For complex images, more efficient local rules based upon the lifting principle have been designed. They provide compression performances very close to or even better than JBIG, depending upon the image characteristics. In the grayscale case, and in particular for smooth images such as depth maps, the proposed algorithm outperforms both the JBIG and the JPEG2000 standards under most coding conditions.
Simulation of root forms using cellular automata model
Winarno, Nanang Prima, Eka Cahya; Afifah, Ratih Mega Ayu
2016-02-08
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.
NASA Astrophysics Data System (ADS)
Hellouin de Menibus, Benjamin; Sablik, Mathieu
2017-06-01
This article introduces new tools to study self-organisation in a family of simple cellular automata which contain some particle-like objects with good collision properties (coalescence) in their time evolution. We draw an initial configuration at random according to some initial shift-ergodic measure, and use the limit measure to describe the asymptotic behaviour of the automata. We first take a qualitative approach, i.e. we obtain information on the limit measure(s). We prove that only particles moving in one particular direction can persist asymptotically. This provides some previously unknown information on the limit measures of various deterministic and probabilistic cellular automata: 3 and 4-cyclic cellular automata [introduced by Fisch (J Theor Probab 3(2):311-338, 1990; Phys D 45(1-3):19-25, 1990)], one-sided captive cellular automata [introduced by Theyssier (Captive Cellular Automata, 2004)], the majority-traffic cellular automaton, a self stabilisation process towards a discrete line [introduced by Regnault and Rémila (in: Mathematical Foundations of Computer Science 2015—40th International Symposium, MFCS 2015, Milan, Italy, Proceedings, Part I, 2015)]. In a second time we restrict our study to a subclass, the gliders cellular automata. For this class we show quantitative results, consisting in the asymptotic law of some parameters: the entry times [generalising K ůrka et al. (in: Proceedings of AUTOMATA, 2011)], the density of particles and the rate of convergence to the limit measure.
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.
Evolution of cellular automata with memory: The Density Classification Task.
Stone, Christopher; Bull, Larry
2009-08-01
The Density Classification Task is a well known test problem for two-state discrete dynamical systems. For many years researchers have used a variety of evolutionary computation approaches to evolve solutions to this problem. In this paper, we investigate the evolvability of solutions when the underlying Cellular Automaton is augmented with a type of memory based on the Least Mean Square algorithm. To obtain high performance solutions using a simple non-hybrid genetic algorithm, we design a novel representation based on the ternary representation used for Learning Classifier Systems. The new representation is found able to produce superior performance to the bit string traditionally used for representing Cellular automata. Moreover, memory is shown to improve evolvability of solutions and appropriate memory settings are able to be evolved as a component part of these solutions.
Simulations of living cell origins using a cellular automata model.
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.
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.
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.
Quantum state transfer through noisy quantum cellular automata
NASA Astrophysics Data System (ADS)
Avalle, Michele; Genoni, Marco G.; Serafini, Alessio
2015-05-01
We model the transport of an unknown quantum state on one dimensional qubit lattices by means of a quantum cellular automata (QCA) evolution. We do this by first introducing a class of discrete noisy dynamics, in the first excitation sector, in which a wide group of classical stochastic dynamics is embedded within the more general formalism of quantum operations. We then extend the Hilbert space of the system to accommodate a global vacuum state, thus allowing for the transport of initial on-site coherences besides excitations, and determine the dynamical constraints that define the class of noisy QCA in this subspace. We then study the transport performance through numerical simulations, showing that for some instances of the dynamics perfect quantum state transfer is attainable. Our approach provides one with a natural description of both unitary and open quantum evolutions, where the homogeneity and locality of interactions allow one to take into account several forms of quantum noise in a plausible scenario.
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.
Reversible Flip-Flops in Quantum-Dot Cellular Automata
NASA Astrophysics Data System (ADS)
Rad, Samaneh Kazemi; Heikalabad, Saeed Rasouli
2017-09-01
Quantum-dot cellular automata is a new technology to design the efficient combinational and sequential circuits at the nano-scale. This technology has many desirable advantages compared to the CMOS technology such as low power consumption, less occupation area and low latency. These features make it suitable for use in flip-flop design. In this paper, with knowing the characteristics of reversible logic, we design new structures for flip-flops. The operations of these structures are evaluated with QCADesigner Version 2.0.3 simulator. In addition, we calculate the power dissipation of these structures by QCAPro tool. The results illustrated that proposed structures are efficient compared to the previous ones.
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.
Evolving Localizations in Reaction-Diffusion Cellular Automata
NASA Astrophysics Data System (ADS)
Adamatzky, Andrew; Bull, Larry; Collet, Pierre; Sapin, Emmanuel
We consider hexagonal cellular automata with immediate cell neighbourhood and three cell-states. Every cell calculates its next state depending on the integral representation of states in its neighbourhood, i.e., how many neighbours are in each one state. We employ evolutionary algorithms to breed local transition functions that support mobile localizations (gliders), and characterize sets of the functions selected in terms of quasi-chemical systems. Analysis of the set of functions evolved allows to speculate that mobile localizations are likely to emerge in the quasi-chemical systems with limited diffusion of one reagent, a small number of molecules are required for amplification of travelling localizations, and reactions leading to stationary localizations involve relatively equal amount of quasi-chemical species. Techniques developed can be applied in cascading signals in nature-inspired spatially extended computing devices, and phenomenological studies and classification of non-linear discrete systems.
Modeling Evacuation of Emergency Vehicles by Cellular Automata Models
NASA Astrophysics Data System (ADS)
Moussa, Najem
An evacuation of the emergency vehicle (EV) from an origin point (e.g., accident location) to a destination point (e.g., hospital) in lower and higher congestions is simulated using city cellular automata models. We find that the mean speed of the EV and its arrival time all depend enormously on the cars density, the route length of the EV and the turn capability of the cars. Dangerous situations that occurred during the evacuation of the EV are also investigated. By allowing high turning capabilities to cars, considerable improvements are obtained. Indeed, the EV mean speed is enhanced and its arrival time is optimized. Moreover, at relatively high density, a significant reduction of the risk of accident is expected.
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.
Robustness enhancement for image hiding algorithm in cellular automata domain
NASA Astrophysics Data System (ADS)
Li, Xiaowei; Kim, Seok-Tae; Lee, In-Kwon
2015-12-01
In this paper, we present a cellular automata (CA)-domain image hiding scheme that embedding a secret image into a gray-level image, in which an effective image preprocessor technique is introduced to improve the robustness of the secret image. The image preprocessor works by transforming a secret image into many elemental images based on the lensless integral imaging technique. The properties of data redundancy and distributed memory of the elemental images reinforce the ability to resist some data loss attacks. Besides, we study an improved pixel-wise masking model to optimize the imperceptibility of the stego-image. Experiments verify that the imperceptibility and robustness requirements of the image hiding are both satisfied excellently in the proposed image hiding system.
Fault-Tolerant Nanocomputers Based on Asynchronous Cellular Automata
NASA Astrophysics Data System (ADS)
Isokawa, Teijiro; Abo, Fukutaro; Peper, Ferdinand; Adachi, Susumu; Lee, Jia; Matsui, Nobuyuki; Mashiko, Shinro
Cellular Automata (CA) are a promising architecture for computers with nanometer-scale sized components, because their regular structure potentially allows chemical manufacturing techniques based on self-organization. With the increase in integration density, however, comes a decrease in the reliability of the components from which such computers will be built. This paper employs BCH error-correcting codes to construct CA with improved reliability. We construct an asynchronous CA of which a quarter of the (ternary) bits storing a cell's state information may be corrupted without affecting the CA's operations, provided errors are evenly distributed over a cell's bits (no burst errors allowed). Under the same condition, the corruption of half of a cell's bits can be detected.
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.
Reversible Flip-Flops in Quantum-Dot Cellular Automata
NASA Astrophysics Data System (ADS)
Rad, Samaneh Kazemi; Heikalabad, Saeed Rasouli
2017-07-01
Quantum-dot cellular automata is a new technology to design the efficient combinational and sequential circuits at the nano-scale. This technology has many desirable advantages compared to the CMOS technology such as low power consumption, less occupation area and low latency. These features make it suitable for use in flip-flop design. In this paper, with knowing the characteristics of reversible logic, we design new structures for flip-flops. The operations of these structures are evaluated with QCADesigner Version 2.0.3 simulator. In addition, we calculate the power dissipation of these structures by QCAPro tool. The results illustrated that proposed structures are efficient compared to the previous ones.
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.
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.
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.
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.
Novel local rules of cellular automata applied to topology and size optimization
NASA Astrophysics Data System (ADS)
Bochenek, Bogdan; Tajs-Zielińska, Katarzyna
2012-01-01
Cellular automata are mathematical idealization of physical systems in which the design domains are divided into lattices of cells, states of which are updated synchronously in discrete time steps according to some local rules. The principle of the cellular automata is that global behaviour of the system is governed by cells that only interact with their neighbours. Because of its simplicity and versatility the method has been found as useful tool for structural design, especially that cellular automata methodology can be adopted for both optimal sizing and topology optimization. This article presents the application of the cellular automata concept to topology optimization of plane elastic structures. As to the optimal sizing, the design of columns exposed to loss of stability is also discussed. A new local update rule is proposed, selected optimal design problems are formulated, and finally the article is illustrated by results of numerical optimization.
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.
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.
Mammogram segmentation using maximal cell strength updation in cellular automata.
Anitha, J; Peter, J Dinesh
2015-08-01
Breast cancer is the most frequently diagnosed type of cancer among women. Mammogram is one of the most effective tools for early detection of the breast cancer. Various computer-aided systems have been introduced to detect the breast cancer from mammogram images. In a computer-aided diagnosis system, detection and segmentation of breast masses from the background tissues is an important issue. In this paper, an automatic segmentation method is proposed to identify and segment the suspicious mass regions of mammogram using a modified transition rule named maximal cell strength updation in cellular automata (CA). In coarse-level segmentation, the proposed method performs an adaptive global thresholding based on the histogram peak analysis to obtain the rough region of interest. An automatic seed point selection is proposed using gray-level co-occurrence matrix-based sum average feature in the coarse segmented image. Finally, the method utilizes CA with the identified initial seed point and the modified transition rule to segment the mass region. The proposed approach is evaluated over the dataset of 70 mammograms with mass from mini-MIAS database. Experimental results show that the proposed approach yields promising results to segment the mass region in the mammograms with the sensitivity of 92.25% and accuracy of 93.48%.
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.
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.
Stochastic cellular automata model for stock market dynamics
NASA Astrophysics Data System (ADS)
Bartolozzi, M.; Thomas, A. W.
2004-04-01
In the present work we introduce a stochastic cellular automata model in order to simulate the dynamics of the stock market. A direct percolation method is used to create a hierarchy of clusters of active traders on a two-dimensional grid. Active traders are characterized by the decision to buy, σi (t)=+1 , or sell, σi (t)=-1 , a stock at a certain discrete time step. The remaining cells are inactive, σi (t)=0 . The trading dynamics is then determined by the stochastic interaction between traders belonging to the same cluster. Extreme, intermittent events, such as crashes or bubbles, are triggered by a phase transition in the state of the bigger clusters present on the grid, where almost all the active traders come to share the same spin orientation. Most of the stylized aspects of the financial market time series, including multifractal proprieties, are reproduced by the model. A direct comparison is made with the daily closures of the S&P500 index.
Stochastic cellular automata model for stock market dynamics.
Bartolozzi, M; Thomas, A W
2004-04-01
In the present work we introduce a stochastic cellular automata model in order to simulate the dynamics of the stock market. A direct percolation method is used to create a hierarchy of clusters of active traders on a two-dimensional grid. Active traders are characterized by the decision to buy, sigma(i) (t)=+1, or sell, sigma(i) (t)=-1, a stock at a certain discrete time step. The remaining cells are inactive, sigma(i) (t)=0. The trading dynamics is then determined by the stochastic interaction between traders belonging to the same cluster. Extreme, intermittent events, such as crashes or bubbles, are triggered by a phase transition in the state of the bigger clusters present on the grid, where almost all the active traders come to share the same spin orientation. Most of the stylized aspects of the financial market time series, including multifractal proprieties, are reproduced by the model. A direct comparison is made with the daily closures of the S&P 500 index.
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.
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.
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.
A Cellular Automata-Based Mathematical Model for Thymocyte Development
Souza-e-Silva, Hallan; Savino, Wilson; Feijóo, Raúl A.; Vasconcelos, Ana Tereza Ribeiro
2009-01-01
Intrathymic T cell development is an important process necessary for the normal formation of cell-mediated immune responses. Importantly, such a process depends on interactions of developing thymocytes with cellular and extracellular elements of the thymic microenvironment. Additionally, it includes a series of oriented and tunely regulated migration events, ultimately allowing mature cells to cross endothelial barriers and leave the organ. Herein we built a cellular automata-based mathematical model for thymocyte migration and development. The rules comprised in this model take into account the main stages of thymocyte development, two-dimensional sections of the normal thymic microenvironmental network, as well as the chemokines involved in intrathymic cell migration. Parameters of our computer simulations with further adjusted to results derived from previous experimental data using sub-lethally irradiated mice, in which thymus recovery can be evaluated. The model fitted with the increasing numbers of each CD4/CD8-defined thymocyte subset. It was further validated since it fitted with the times of permanence experimentally ascertained in each CD4/CD8-defined differentiation stage. Importantly, correlations using the whole mean volume of young normal adult mice revealed that the numbers of cells generated in silico with the mathematical model fall within the range of total thymocyte numbers seen in these animals. Furthermore, simulations made with a human thymic epithelial network using the same mathematical model generated similar profiles for temporal evolution of thymocyte developmental stages. Lastly, we provided in silico evidence that the thymus architecture is important in the thymocyte development, since changes in the epithelial network result in different theoretical profiles for T cell development/migration. This model likely can be used to predict thymocyte evolution following therapeutic strategies designed for recovery of the thymus in diseases
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.
Ripple Clock Schemes for Quantum-dot Cellular Automata Circuits
NASA Astrophysics Data System (ADS)
Purohit, Prafull
Quantum-dot cellular automata (QCA) is an emerging technology for building digital circuits at nano-scale. It is considered as an alternative to widely used complementary metal oxide semiconductor (CMOS) technology because of its key features, which include low power operation, high density and high operating frequency. Unlike conventional logic circuits in which information is transferred by electrical current, QCA operates with the help of coulomb interaction between two adjacent QCA cells. A QCA cell is a set of four quantum-dots that are placed near the corners of a square. Due to the fact that clocking provides power and control of data flow in QCA, it is considered to be the backbone of QCA operation. This thesis presents the design and simulation of a ripple clock scheme and an enhanced ripple clock scheme for QCA circuits. In the past, different clock schemes were proposed and studied which were focused on data flow in particular direction or reducing delay. This proposed thesis will study the design and simulation of new clock schemes which are more realistic for implementation, give a freedom to propagate logic in all directions, suitable for both combinational and sequential circuits and has potential to support testing and reconfiguration up to some extent. A variety of digital circuits including a 2--to--1 multiplexer, a 1--bit memory, an RS latch, a full adder, a 4--bit adder and a 2--to--4 decoder are implemented and simulated using these clock schemes. A 2--to--4 decoder is used to demonstrate the testing capabilities of these clock schemes. All QCA layouts are drawn and simulated in QCADesigner.
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.
Developing a web-based cellular automata model for urban growth simulation
NASA Astrophysics Data System (ADS)
Liu, Yan; He, Jin
2009-10-01
Cellular automata as an emerging technology have been adapted increasingly by geographers and planners to simulate the spatial and temporal processes of urban growth. While the literature reports many applications of cellular automata models for urban studies, in practice, the operation of the models as well as the configuration and calibration of relevant parameters used in the models were only known to the model builders. This is largely due to the constraint that most cellular automata models were developed based on desktop computer programs, either by incorporating the model within a desktop GIS environment, or developing the model independent of a desktop GIS. Consequently, there is little input from the user to test or visualise the actual operation or evaluate the applicability of the model under different conditions. This paper presents a methodology to implement a fuzzy constrained cellular automata model of urban growth within a web-based GIS environment, using the actual urban growth of Metropolitan Sydney, Australia from 1976 to 2006 as a case study. With the web-based cellular automata model, users can visualise and test the operation of the model; they can also modify or calibrate the model's parameters to evaluate its simulation accuracies, or even feed the model with various 'what-if' conditions to generate alterative outcomes. Such a web-based modelling platform provides a useful and effective channel for government authority and stakeholders to evaluate different urban growth scenarios. It also provides an interactive environment that can foster public participation in urban planning and management.
A simple linearization of the self-shrinking generator by means of cellular automata.
Fúster-Sabater, Amparo; Pazo-Robles, M Eugenia; Caballero-Gil, Pino
2010-04-01
In this work, it is shown that the output sequence of a well-known cryptographic generator, the so-called self-shrinking generator, can be obtained from a simple linear model based on cellular automata. In fact, such a cellular model is a linear version of a nonlinear keystream generator currently used in stream ciphers. The linearization procedure is immediate and is based on the concatenation of a basic structure. The obtained cellular automata can be easily implemented with FPGA logic. Linearity and symmetry properties in such automata can be advantageously exploited for the analysis and/or cryptanalysis of this particular type of sequence generator. Copyright 2009 Elsevier Ltd. All rights reserved.
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.
Generic framework for mining cellular automata models on protein-folding simulations.
Diaz, N; Tischer, I
2016-05-13
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.
Using cellular automata to simulate forest fire propagation in Portugal
NASA Astrophysics Data System (ADS)
Freire, Joana; daCamara, Carlos
2017-04-01
Wildfires in the Mediterranean region have severe damaging effects mainly due to large fire events [1, 2]. When restricting to Portugal, wildfires have burned over 1:4 million ha in the last decade. Considering the increasing tendency in the extent and severity of wildfires [1, 2], the availability of modeling tools of fire episodes is of crucial importance. Two main types of mathematical models are generally available, namely deterministic and stochastic models. Deterministic models attempt a description of fires, fuel and atmosphere as multiphase continua prescribing mass, momentum and energy conservation, which typically leads to systems of coupled PDEs to be solved numerically on a grid. Simpler descriptions, such as FARSITE, neglect the interaction with atmosphere and propagate the fire front using wave techniques. One of the most important stochastic models are Cellular Automata (CA), in which space is discretized into cells, and physical quantities take on a finite set of values at each cell. The cells evolve in discrete time according to a set of transition rules, and the states of the neighboring cells. In the present work, we implement and then improve a simple and fast CA model designed to operationally simulate wildfires in Portugal. The reference CA model chosen [3] has the advantage of having been applied successfully in other Mediterranean ecosystems, namely to historical fires in Greece. The model is defined on a square grid with propagation to 8 nearest and next-nearest neighbors, where each cell is characterized by 4 possible discrete states, corresponding to burning, not-yet burned, fuel-free and completely burned cells, with 4 possible rules of evolution which take into account fuel properties, meteorological conditions, and topography. As a CA model, it offers the possibility to run a very high number of simulations in order to verify and apply the model, and is easily modified by implementing additional variables and different rules for the
Cellular automata model of magnetospheric-ionospheric coupling
NASA Astrophysics Data System (ADS)
Kozelov, B. V.; Kozelova, T. V.
2003-09-01
We propose a cellular automata model (CAM) to describe the substorm activity of the magnetospheric-ionospheric system. The state of each cell in the model is described by two numbers that correspond to the energy content in a region of the current sheet in the magnetospheric tail and to the conductivity of the ionospheric domain that is magnetically connected with this region. The driving force of the system is supposed to be provided by the solar wind that is convected along the two boundaries of the system. The energy flux inside is ensured by the penetration of the energy from the solar wind into the array of cells (magnetospheric tail) with a finite velocity. The third boundary (near to the Earth) is closed and the fourth boundary is opened, thereby modeling the flux far away from the tail. The energy dissipation in the system is quite similar to other CAM models, when the energy in a particular cell exceeds some pre-defined threshold, and the part of the energy excess is redistributed between the neighbouring cells. The second number attributed to each cell mimics ionospheric conductivity that can allow for a part of the energy to be shed on field-aligned currents. The feedback between ionosphere and magnetospheric tail is provided by the change in a part of the energy, which is redistributed in the tail when the threshold is surpassed. The control parameter of the model is the z-component of the interplanetary magnetic field (Bz IMF), frozen into the solar wind. To study the internal dynamics of the system at the beginning, this control parameter is taken to be constant. The dynamics of the system undergoes several bifurcations, when the constant varies from - 0.6 to - 6.0. The Bz IMF input results in the periodic transients (activation regions) and the inter-transient period decreases with the decrease of Bz. At the same time the onset of activations in the array shifts towards the Earth . When the modulus of the Bz IMF exceeds some threshold value, the
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).
Modelling of the cellular automata space deformation within the RCAFE framework
NASA Astrophysics Data System (ADS)
Sitko, Mateusz; Madej, Łukasz
2016-10-01
Development of the innovative approach to micro scale cellular automata (CA) space deformation during dynamic recrystallization process (DRX) is the main goal of the present paper. Major assumptions of the developed CA DRX model as well as novel space deformation algorithm, which is based on the random cellular automata concept and FE method, are described. Algorithms and methods to transfer input/output data between FE and CA are presented in detail. Visualization tool to analyze progress of deformation in the irregular CA space is also highlighted. Finally, initial results in the form of deformed and recrystallized microstructures are presented and discussed.
Two-layer synchronized ternary quantum-dot cellular automata wire crossings.
Bajec, Iztok Lebar; Pečar, Primož
2012-04-16
: Quantum-dot cellular automata are an interesting nanoscale computing paradigm. The introduction of the ternary quantum-dot cell enabled ternary computing, and with the recent development of a ternary functionally complete set of elementary logic primitives and the ternary memorizing cell design of complex processing structures is becoming feasible. The specific nature of the ternary quantum-dot cell makes wire crossings one of the most problematic areas of ternary quantum-dot cellular automata circuit design. We hereby present a two-layer wire crossing that uses a specific clocking scheme, which ensures the crossed wires have the same effective delay.
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.
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 ...
Material representations: from the genetic code to the evolution of cellular automata.
Rocha, Luis Mateus; Hordijk, Wim
2005-01-01
We present a new definition of the concept of representation for cognitive science that is based on a study of the origin of structures that are used to store memory in evolving systems. This study consists of novel computer experiments in the evolution of cellular automata to perform nontrivial tasks as well as evidence from biology concerning genetic memory. Our key observation is that representations require inert structures to encode information used to construct appropriate dynamic configurations for the evolving system. We propose criteria to decide if a given structure is a representation by unpacking the idea of inert structures that can be used as memory for arbitrary dynamic configurations. Using a genetic algorithm, we evolved cellular automata rules that can perform nontrivial tasks related to the density task (or majority classification problem) commonly used in the literature. We present the particle catalogs of the new rules following the computational mechanics framework. We discuss if the evolved cellular automata particles may be seen as representations according to our criteria. We show that while they capture some of the essential characteristics of representations, they lack an essential one. Our goal is to show that artificial life can be used to shed new light on the computation-versus-dynamics debate in cognitive science, and indeed function as a constructive bridge between the two camps. Our definitions of representation and cellular automata experiments are proposed as a complementary approach, with both dynamics and informational modes of explanation.
Simulating invasion with cellular automata: connecting cell-scale and population-scale properties.
Simpson, Matthew J; Merrifield, Alistair; Landman, Kerry A; Hughes, Barry D
2007-08-01
Interpretive and predictive tools are needed to assist in the understanding of cell invasion processes. Cell invasion involves cell motility and proliferation, and is central to many biological processes including developmental morphogenesis and tumor invasion. Experimental data can be collected across a wide range of scales, from the population scale to the individual cell scale. Standard continuum or discrete models used in isolation are insufficient to capture this wide range of data. We develop a discrete cellular automata model of invasion with experimentally motivated rules. The cellular automata algorithm is applied to a narrow two-dimensional lattice and simulations reveal the formation of invasion waves moving with constant speed. The simulation results are averaged in one dimension-these data are used to identify the time history of the leading edge to characterize the population-scale wave speed. This allows the relationship between the population-scale wave speed and the cell-scale parameters to be determined. This relationship is analogous to well-known continuum results for Fisher's equation. The cellular automata algorithm also produces individual cell trajectories within the invasion wave that are analogous to cell trajectories obtained with new experimental techniques. Our approach allows both the cell-scale and population-scale properties of invasion to be predicted in a way that is consistent with multiscale experimental data. Furthermore we suggest that the cellular automata algorithm can be used in conjunction with individual data to overcome limitations associated with identifying cell motility mechanisms using continuum models alone.
Energy dissipation dataset for reversible logic gates in quantum dot-cellular automata.
Bahar, Ali Newaz; Rahman, Mohammad Maksudur; Nahid, Nur Mohammad; Hassan, Md Kamrul
2017-02-01
This paper presents an energy dissipation dataset of different reversible logic gates in quantum-dot cellular automata. The proposed circuits have been designed and verified using QCADesigner simulator. Besides, the energy dissipation has been calculated under three different tunneling energy level at temperature T=2 K. For estimating the energy dissipation of proposed gates; QCAPro tool has been employed.
A Cellular Automata-based Model for Simulating Restitution Property in a Single Heart Cell.
Sabzpoushan, Seyed Hojjat; Pourhasanzade, Fateme
2011-01-01
Ventricular fibrillation is the cause of the most sudden mortalities. Restitution is one of the specific properties of ventricular cell. The recent findings have clearly proved the correlation between the slope of restitution curve with ventricular fibrillation. This; therefore, mandates the modeling of cellular restitution to gain high importance. A cellular automaton is a powerful tool for simulating complex phenomena in a simple language. A cellular automaton is a lattice of cells where the behavior of each cell is determined by the behavior of its neighboring cells as well as the automata rule. In this paper, a simple model is depicted for the simulation of the property of restitution in a single cardiac cell using cellular automata. At first, two state variables; action potential and recovery are introduced in the automata model. In second, automata rule is determined and then recovery variable is defined in such a way so that the restitution is developed. In order to evaluate the proposed model, the generated restitution curve in our study is compared with the restitution curves from the experimental findings of valid sources. Our findings indicate that the presented model is not only capable of simulating restitution in cardiac cell, but also possesses the capability of regulating the restitution curve.
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 ...
Color image encryption based on hybrid hyper-chaotic system and cellular automata
NASA Astrophysics Data System (ADS)
Yaghouti Niyat, Abolfazl; Moattar, Mohammad Hossein; Niazi Torshiz, Masood
2017-03-01
This paper proposes an image encryption scheme based on Cellular Automata (CA). CA is a self-organizing structure with a set of cells in which each cell is updated by certain rules that are dependent on a limited number of neighboring cells. The major disadvantages of cellular automata in cryptography include limited number of reversal rules and inability to produce long sequences of states by these rules. In this paper, a non-uniform cellular automata framework is proposed to solve this problem. This proposed scheme consists of confusion and diffusion steps. In confusion step, the positions of the original image pixels are replaced by chaos mapping. Key image is created using non-uniform cellular automata and then the hyper-chaotic mapping is used to select random numbers from the image key for encryption. The main contribution of the paper is the application of hyper chaotic functions and non-uniform CA for robust key image generation. Security analysis and experimental results show that the proposed method has a very large key space and is resistive against noise and attacks. The correlation between adjacent pixels in the encrypted image is reduced and the amount of entropy is equal to 7.9991 which is very close to 8 which is ideal.
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.
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.
CarboCAT: A cellular automata model of heterogeneous carbonate strata
NASA Astrophysics Data System (ADS)
Burgess, Peter M.
2013-04-01
CarboCAT is a new numerical model of carbonate deposystems that uses a cellular automata to calculate lithofacies spatial distributions and hence to calculate the accumulation of heterogeneous carbonate strata in three dimensions. CarboCAT includes various geological processes, including tectonic subsidence, eustatic sea-level oscillations, water depth-dependent carbonate production rates in multiple carbonate factories, lateral migration of carbonate lithofacies bodies, and a simple representation of sediment transport. Results from the model show stratigraphically interesting phenomena such as heterogeneous strata with complex stacking patterns, laterally discontinuous subaerial exposure surfaces, nonexponential lithofacies thickness distributions, and sensitive dependence on initial conditions whereby small changes in the model initial conditions have a large effect on the final model outcome. More work is required to fully assess CarboCAT, but these initial results suggest that a cellular automata approach to modeling carbonate strata is likely to be a useful tool for investigating the nature and origins of heterogeneity in carbonate strata.
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.
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.
Three-dimensional cellular automata as a model of a seismic fault
NASA Astrophysics Data System (ADS)
Gálvez, G.; Muñoz, A.
2017-01-01
The Earth's crust is broken into a series of plates, whose borders are the seismic fault lines and it is where most of the earthquakes occur. This plating system can in principle be described by a set of nonlinear coupled equations describing the motion of the plates, its stresses, strains and other characteristics. Such a system of equations is very difficult to solve, and nonlinear parts leads to a chaotic behavior, which is not predictable. In 1989, Bak and Tang presented an earthquake model based on the sand pile cellular automata. The model though simple, provides similar results to those observed in actual earthquakes. In this work the cellular automata in three dimensions is proposed as a best model to approximate a seismic fault. It is noted that the three-dimensional model reproduces similar properties to those observed in real seismicity, especially, the Gutenberg-Richter law.
Nishawala, Vinesh V.; Ostoja-Starzewski, Martin; Leamy, Michael J.; ...
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
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.
Modeling of urban growth using cellular automata (CA) optimized by Particle Swarm Optimization (PSO)
NASA Astrophysics Data System (ADS)
Khalilnia, M. H.; Ghaemirad, T.; Abbaspour, R. A.
2013-09-01
In this paper, two satellite images of Tehran, the capital city of Iran, which were taken by TM and ETM+ for years 1988 and 2010 are used as the base information layers to study the changes in urban patterns of this metropolis. The patterns of urban growth for the city of Tehran are extracted in a period of twelve years using cellular automata setting the logistic regression functions as transition functions. Furthermore, the weighting coefficients of parameters affecting the urban growth, i.e. distance from urban centers, distance from rural centers, distance from agricultural centers, and neighborhood effects were selected using PSO. In order to evaluate the results of the prediction, the percent correct match index is calculated. According to the results, by combining optimization techniques with cellular automata model, the urban growth patterns can be predicted with accuracy up to 75 %.
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!
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.
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).
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.
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.
Stability of Cellular Automata Trajectories Revisited: Branching Walks and Lyapunov Profiles
NASA Astrophysics Data System (ADS)
Baetens, Jan M.; Gravner, Janko
2016-10-01
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.
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.
Characterization of one-dimensional cellular automata rules through topological network features
NASA Astrophysics Data System (ADS)
D'Alotto, Lou; Pizzuti, Clara
2016-10-01
The paper investigates the relationship between the classification schemes, defined by Wolfram and Gilman, of one-dimensional cellular automata through concepts coming from network theory. An automaton is represented with a network, generated from the elementary rule defining its behavior. Characteristic features of this graph are computed and machine learning classification models are built. Such models allow to classify automaton rules and to compare Wolfram's and Gilman's classes by comparing the classes predicted by these models.
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.
Ship interaction in narrow water channels: A two-lane cellular automata approach
NASA Astrophysics Data System (ADS)
Sun, Zhuo; Chen, Zhonglong; Hu, Hongtao; Zheng, Jianfeng
2015-08-01
In narrow waterways, closed ships might interact due to hydrodynamic forces. To avoid clashes, different lane-changing rules are required. In this paper, a two-lane cellular automata model is proposed to investigate the traffic flow patterns in narrow water channels. Numerical experiments show that ship interaction can form "lumps" in traffic flow which will significantly depress the flux. We suggest that the lane-changing frequency of fast ships should be limited.
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}.
Vaca-González, J J; Gutiérrez, M L; Guevara, J M; Garzón-Alvarado, D A
2016-01-07
Articular cartilage is characterized by low cell density of only one cell type, chondrocytes, and has limited self-healing properties. When articular cartilage is affected by traumatic injuries, a therapeutic strategy such as autologous chondrocyte implantation is usually proposed for its treatment. This approach requires in vitro chondrocyte expansion to yield high cell number for cell transplantation. To improve the efficiency of this procedure, it is necessary to assess cell dynamics such as migration, proliferation and cell death during culture. Computational models such as cellular automata can be used to simulate cell dynamics in order to enhance the result of cell culture procedures. This methodology has been implemented for several cell types; however, an experimental validation is required for each one. For this reason, in this research a cellular automata model, based on random-walk theory, was devised in order to predict articular chondrocyte behavior in monolayer culture during cell expansion. Results demonstrated that the cellular automata model corresponded to cell dynamics and computed-accurate quantitative results. Moreover, it was possible to observe that cell dynamics depend on weighted probabilities derived from experimental data and cell behavior varies according to the cell culture period. Thus, depending on whether cells were just seeded or proliferated exponentially, culture time probabilities differed in percentages in the CA model. Furthermore, in the experimental assessment a decreased chondrocyte proliferation was observed along with increased passage number. This approach is expected to having other uses as in enhancing articular cartilage therapies based on tissue engineering and regenerative medicine.
On the derivation of approximations to cellular automata models and the assumption of independence.
Davies, K J; Green, J E F; Bean, N G; Binder, B J; Ross, J V
2014-07-01
Cellular automata are discrete agent-based models, generally used in cell-based applications. There is much interest in obtaining continuum models that describe the mean behaviour of the agents in these models. Previously, continuum models have been derived for agents undergoing motility and proliferation processes, however, these models only hold under restricted conditions. In order to narrow down the reason for these restrictions, we explore three possible sources of error in deriving the model. These sources are the choice of limiting arguments, the use of a discrete-time model as opposed to a continuous-time model and the assumption of independence between the state of sites. We present a rigorous analysis in order to gain a greater understanding of the significance of these three issues. By finding a limiting regime that accurately approximates the conservation equation for the cellular automata, we are able to conclude that the inaccuracy between our approximation and the cellular automata is completely based on the assumption of independence.
A Conceptual Data Model for Flood Based on Cellular Automata Using Moving Object Data Model
NASA Astrophysics Data System (ADS)
Rachmatullah, R. S.; Azizah, F. N.
2017-01-01
Flood is considered as the costliest natural disaster in Indonesia due to its frequent occurrences as well as the extensive damage that it causes. Several studies provide different flood prediction models based on various hydrological factors. A lot of these models use grid-to-grid approach, making them suitable to be modelled as cellular automata. This paper presents a conceptual data model for flood based on cellular automata model using spatio-temporal data model, especially the moving object data model, as the modelling approach. The conceptual data model serves as the model of data structures within an environment for flood prediction simulation. We describe two conceptual data models as the alternatives to model the data structures of flood model. We create the data model based on the study to the factors that constitute the flood models. The first conceptual data model alternative focuses on the cell/grid as the main entity type. The changes of the states of the cells are stored as moving integer. The second alternative emphasizes on flood as the main entity type. The changes of the flood area are stored as moving region. Both alternatives introduce some advantages and disadvantages and the choice rely on the purpose of the use of the data model. We present a proposal of the architecture of a flood prediction system using cellular automata as the modelling approach. As the continuation of this work, further design and implementation details must be provided.
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.
López, Leonardo; Burguerner, Germán; Giovanini, Leonardo
2014-04-12
The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. An epidemic is characterized trough an individual-based-model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the
2014-01-01
Background The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. Methods An epidemic is characterized trough an individual–based–model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. Results A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. Conclusions The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area
Image Segmentation Based on Learning Cellular Automata Using Soft Computing Approach
NASA Astrophysics Data System (ADS)
Das, Debasis; Ray, Abhishek
2010-10-01
Image Segmentation refers to the process of partitioning a digital image into multiple segments. The goal of segmentation is to simplify and change the representation of an image into something that is more meaningful and easier to analyze. A Cellular Automata (CA) is a computing model of complex system using simple rule. It divides the problem space into number of cells and each cell can be in one or several final states. Cells are affected by its neighbor's to the simple rule. Learning Cellular Automata (LCA) is a variant of automata that interact with random environment having as goal to improve its behavior. This paper proposes an image segmentation technique based on LCA using soft computing approach. This proposed method works in two steps, the first step is called as soft segmentation where the input image(s) is/are analyzed through LCA and the second step is called as soft computing approach where the analyzed image is segmented through fuzzy C-means algorithm.
Cellular-automata model of oxygen plasma impact on porous low-K dielectric
NASA Astrophysics Data System (ADS)
Rezvanov, Askar; Matyushkin, Igor V.; Gutshin, Oleg P.; Gornev, Evgeny S.
2016-12-01
Cellular-automata model of oxygen plasma influence on the integral properties of porous low-K dielectric is studied. The present work investigates the imitative simulation of this process. In our model we consider one isolated pore, which is simulated by cylinder with length L=200 nm and radius 1 nm ignoring the curvature factor. The simulation was performed for 2 million automata steps that correspond to 2 seconds in the real process time. Extrapolating the data to the longer time shows that more and more •CH3 groups will be replaced by the •OH groups, and over time almost all methyl groups will leave the pore surface (there is not more than 20% of the initial methyl groups amount on the first low-K dielectric 40nm after 2 seconds simulation).
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.
Counting Lattice-Gas Invariants
2007-11-02
Dominique d’Humières, Brosl Hasslacher, Pierre Lallemand, Yves Pomeau, and Jean-Pierre Rivet . Lattice gas hydrodynamics in two and three dimensions...177. Springer -Verlag, Februrary 1989. Proceedings of the Winter School, Les Houches, France. 6
Limit measures for affine cellular automata on topological Markov subgroups
NASA Astrophysics Data System (ADS)
Maass, Alejandro; Martínez, Servet; Sobottka, Marcelo
2006-09-01
Consider a topological Markov subgroup which is ps-torsion (with p prime) and an affine cellular automaton defined on it. We show that the Cesàro mean of the iterates, by the automaton of a probability measure with complete connections and summable memory decay that is compatible with the topological Markov subgroup, converges to the Haar measure.
Spectral representations and global maps of cellular automata dynamics
NASA Astrophysics Data System (ADS)
Raptis, Theophanes E.
2016-10-01
We present a spectral representation of any computation performed by a Cellular Automaton (CA) of arbitrary topology and dimensionality via an appropriate coding scheme in Fourier space that can be implemented in an analog machine ideally circumventing part of the overall waste heat production. We explore further consequences of this encoding and we provide a simple example based on the Game-of-Life where we find global maps for small lattices indicating an interesting underlying recursive structure.
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.
On Detection and Isolation of Defective Cells in Self-Timed Cellular Automata
NASA Astrophysics Data System (ADS)
Isokawa, Teijiro; Peper, Ferdinand; Kowada, Shin'ya; Kamiura, Naotake; Matsui, Nobuyuki
Defect-tolerance, the ability to overcome unreliability of components in a system, will be essential to realize computers built by nanotechnology. This paper reviews two approaches to defect-tolerance for nanocomputers that are based on self-timed cellular automata, a type of asynchronous cellular automaton, where the cells' defects are assumed to be of the stuck-at fault type. One approach for detecting and isolating defective components (cells) is in a so-called off-line manner, i.e., through isolating defective cells and laying out circuits in the cellular space. In the other approach, defective cells can be detected and isolated while computation takes place, i.e., in an on-line manner. We show how to cope with defects in the cellular space in a self-contained way, while a computation task is conducted on it.
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.
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.
NASA Astrophysics Data System (ADS)
Pitsa, Despoina; Vardakis, George; Danikas, Michael G.; Kozako, Masahiro
2010-03-01
In this paper the propagation of electrical treeing in nanodielectrics using the DIMET (Dielectric Inhomogeneity Model for Electrical Treeing) is studied. The DIMET is a model which simulates the growth of electrical treeing based on theory of Cellular Automata. Epoxy/glass nanocomposites are used as samples between a needle-plane electrode arrangement. The diameter of nanofillers is 100 nm. The electric treeing, which starts from the needle electrode, is examined. The treeing growth seems to be stopped by the nanofillers. The latter act as elementary barriers to the treeing propagation.
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.
A Three-Layer Full Adder/Subtractor Structure in Quantum-Dot Cellular Automata
NASA Astrophysics Data System (ADS)
Barughi, Yashar Zirak; Heikalabad, Saeed Rasouli
2017-09-01
Nowadays, quantum-dot cellular automata (QCA) is one of the paramount modern technologies for designing logical structures at the nano-scale. This technology is being used in molecular levels and it is based on QCA cells. High speed data transfer and low consumable power are the advantages of this technology. In this paper, we are designing and simulating a fulladder/subtractor with minimum number of cells and complexities in three layers. QCA designer software has been used to simulate the proposed design.
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.
Stochastic modeling for dynamics of HIV-1 infection using cellular automata: A review.
Precharattana, Monamorn
2016-02-01
Recently, the description of immune response by discrete models has emerged to play an important role to study the problems in the area of human immunodeficiency virus type 1 (HIV-1) infection, leading to AIDS. As infection of target immune cells by HIV-1 mainly takes place in the lymphoid tissue, cellular automata (CA) models thus represent a significant step in understanding when the infected population is dispersed. Motivated by these, the studies of the dynamics of HIV-1 infection using CA in memory have been presented to recognize how CA have been developed for HIV-1 dynamics, which issues have been studied already and which issues still are objectives in future studies.
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.
Open boundaries in a cellular automata model for synchronized flow: effects of nonmonotonicity.
Jiang, Rui; Wu, Qing-Song
2003-08-01
In this paper, we have discussed the traffic situations arising from the open boundary conditions (OBC) of a cellular automata model that can reproduce the synchronized flow. The model is different from the slow-to-start (STS) model in that the upper branch of the fundamental diagram in the periodic boundary conditions (PBC) is not monotonous but has an extremum. The phase diagram and the fundamental diagram of the model in the OBC are investigated. The results are compared with those of the STS model and those in the PBC. The current in the OBC as well as the density profiles in the different phases is also investigated.
Cellular Automata as a Computational Model for Low-Level Vision
NASA Astrophysics Data System (ADS)
Broggi, Alberto; D'Andrea, Vincenzo; Destri, Giulio
In this paper we discuss the use of the Cellular Automata (CA) computational model in computer vision applications on massively parallel architectures. Motivations and guidelines of this approach to low-level vision in the frame of the PROMETHEUS project are discussed. The hard real-time requirement of actual application can be only satisfied using an ad hoc VLSI massively parallel architecture (PAPRICA). The hardware solutions and the specific algorithms can be efficiently verified and tested only using, as a simulator, a general purpose machine with a parent architecture (CM-2). An example of application related to feature extraction is discussed.
A New Cellular Automata Model Considering Finite Deceleration and Braking Distance
NASA Astrophysics Data System (ADS)
Yamg, Meng-Long; Liu, Yi-Guang; You, Zhi-Sheng
2007-10-01
We present a new cellular automata model for one-lane traffic flow. In this model, we consider the driver prejudgment according to the state of the leading car. We also consider that the vehicle deceleration capability is finite and the braking distance of the high-speed running cars cannot be ignored, which is not considered in most models. Furthermore, comfortable driving is considered, too. Using computer simulations we obtain some basic qualitative results and the fundamental diagram of the proposed model. In comparison with the known models, we find that the fundamental diagram of the proposed model is more realistic than that of the known models.
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.
A Three-Layer Full Adder/Subtractor Structure in Quantum-Dot Cellular Automata
NASA Astrophysics Data System (ADS)
Barughi, Yashar Zirak; Heikalabad, Saeed Rasouli
2017-06-01
Nowadays, quantum-dot cellular automata (QCA) is one of the paramount modern technologies for designing logical structures at the nano-scale. This technology is being used in molecular levels and it is based on QCA cells. High speed data transfer and low consumable power are the advantages of this technology. In this paper, we are designing and simulating a fulladder/subtractor with minimum number of cells and complexities in three layers. QCA designer software has been used to simulate the proposed design.
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.
A new simulation system of traffic flow based on cellular automata principle
NASA Astrophysics Data System (ADS)
Shan, Junru
2017-05-01
Traffic flow is a complex system of multi-behavior so it is difficult to give a specific mathematical equation to express it. With the rapid development of computer technology, it is an important method to study the complex traffic behavior by simulating the interaction mechanism between vehicles and reproduce complex traffic behavior. Using the preset of multiple operating rules, cellular automata is a kind of power system which has discrete time and space. It can be a good simulation of the real traffic process and a good way to solve the traffic problems.
Understanding the complex dynamics of stock markets through cellular automata
NASA Astrophysics Data System (ADS)
Qiu, G.; Kandhai, D.; Sloot, P. M. A.
2007-04-01
We present a cellular automaton (CA) model for simulating the complex dynamics of stock markets. Within this model, a stock market is represented by a two-dimensional lattice, of which each vertex stands for a trader. According to typical trading behavior in real stock markets, agents of only two types are adopted: fundamentalists and imitators. Our CA model is based on local interactions, adopting simple rules for representing the behavior of traders and a simple rule for price updating. This model can reproduce, in a simple and robust manner, the main characteristics observed in empirical financial time series. Heavy-tailed return distributions due to large price variations can be generated through the imitating behavior of agents. In contrast to other microscopic simulation (MS) models, our results suggest that it is not necessary to assume a certain network topology in which agents group together, e.g., a random graph or a percolation network. That is, long-range interactions can emerge from local interactions. Volatility clustering, which also leads to heavy tails, seems to be related to the combined effect of a fast and a slow process: the evolution of the influence of news and the evolution of agents’ activity, respectively. In a general sense, these causes of heavy tails and volatility clustering appear to be common among some notable MS models that can confirm the main characteristics of financial markets.
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?
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.
Awazu, Akinori
2008-07-01
Dynamical aspects of the asymmetric cellular automata were investigated to consider the signaling processes in biological systems. As a meta-model of the cascade of feed-forward loop type network motifs in biological reaction networks, we consider the one dimensional asymmetric cellular automata where the state of each cell is controlled by a trio of cells, the cell itself, the nearest upstream cell and the next nearest upstream cell. Through the systematic simulations, some novel input-dependent wave propagations were found in certain asymmetric CA, which may be useful for the signaling processes like the distinction, the filtering and the memory of external stimuli.
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).
NASA Astrophysics Data System (ADS)
Ma, Xiao; Zheng, Wei-Fan; Jiang, Bao-Shan; Zhang, Ji-Ye
2016-10-01
With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations. Project supported by the National Natural Science Foundation of China (Grant Nos. 11572264, 11172247, 11402214, and 61373009).
Decentralized Cooperation Strategies in Two-Dimensional Traffic of Cellular Automata
NASA Astrophysics Data System (ADS)
Fang, Jun; Qin, Zheng; Chen, Xi-Qun; Leng, Biao; Xu, Zhao-Hui; Jiang, Zi-Neng
2012-12-01
We study the two-dimensional traffic of cellular automata using computer simulation. We propose two type of decentralized cooperation strategies, which are called stepping aside (CS-SA) and choosing alternative routes (CS-CAR) respectively. We introduce them into an existing two-dimensional cellular automata (CA) model. CS-SA is designed to prohibit a kind of ping-pong jump when two objects standing together try to move in opposite directions. CS-CAR is designed to change the solution of conflict in parallel update. CS-CAR encourages the objects involved in parallel conflicts choose their alternative routes instead of waiting. We also combine the two cooperation strategies (CS-SA-CAR) to test their combined effects. It is found that the system keeps on a partial jam phase with nonzero velocity and flow until the density reaches one. The ratios of the ping-pong jump and the waiting objects involved in conflict are decreased obviously, especially at the free phase. And the average flow is improved by the three cooperation strategies. Although the average travel time is lengthened a bit by CS-CAR, it is shorten by CS-SA and CS-SA-CAR. In addition, we discuss the advantage and applicability of decentralized cooperation modeling.
An energy and cost efficient majority-based RAM cell in quantum-dot cellular automata
NASA Astrophysics Data System (ADS)
Khosroshahy, Milad Bagherian; Moaiyeri, Mohammad Hossein; Navi, Keivan; Bagherzadeh, Nader
Nanotechnologies, notably quantum-dot cellular automata, have achieved major attentions for their prominent features as compared to the conventional CMOS circuitry. Quantum-dot cellular automata, particularly owning to its considerable reduction in size, high switching speed and ultra-low energy consumption, is considered as a potential alternative for the CMOS technology. As the memory unit is one of the most essential components in a digital system, designing a well-optimized QCA random access memory (RAM) cell is an important area of research. In this paper, a new five-input majority gate is presented which is suitable for implementing efficient single-layer QCA circuits. In addition, a new RAM cell with set and reset capabilities is designed based on the proposed majority gate, which has an efficient and low-energy structure. The functionality, performance and energy consumption of the proposed designs are evaluated based on the QCADesigner and QCAPro tools. According to the simulation results, the proposed RAM design leads to on average 38% lower total energy dissipation, 25% smaller area, 20% lower cell count, 28% lower delay and 60% lower QCA cost as compared to its previous counterparts.
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.
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.
Simulation of Rock Mass Horizontal Displacements with Usage of Cellular Automata Theory.
NASA Astrophysics Data System (ADS)
Sikora, Paweł
2016-12-01
In the article there was presented two dimensional rock mass model as a deterministic finite cellular automata. Used to describe the distribution of subsidence of rock mass inside and on its surface the theory of automata makes it relatively simple way to get a subsidence trough profile consistent with the profile observed by geodetic measurements on the land surface. As a development of an existing concept of the rock mass model, as a finite cellular automaton, there was described distribution function that allows, simultaneously with the simulation of subsidence, to simulate horizontal displacements inside the rock mass model and on its surface in accordance with real observations. On the basis of the results of numerous computer simulations there was presented fundamental mathematical relationship that determines the ratio of maximum horizontal displacement and maximum subsidence, in case of full subsidence trough, in relation to the basic parameters of the rock mass model. The possibilities of presented model were shown on the example of simulation results of deformation distribution caused by extraction of abstract coal panel. Obtained results were consistent with results obtained by geometric-integral theory.
Zhu, Hao; Sun, Yan; Rajagopal, Gunaretnam; Mondry, Adrian; Dhar, Pawan
2004-01-01
Background Many arrhythmias are triggered by abnormal electrical activity at the ionic channel and cell level, and then evolve spatio-temporally within the heart. To understand arrhythmias better and to diagnose them more precisely by their ECG waveforms, a whole-heart model is required to explore the association between the massively parallel activities at the channel/cell level and the integrative electrophysiological phenomena at organ level. Methods We have developed a method to build large-scale electrophysiological models by using extended cellular automata, and to run such models on a cluster of shared memory machines. We describe here the method, including the extension of a language-based cellular automaton to implement quantitative computing, the building of a whole-heart model with Visible Human Project data, the parallelization of the model on a cluster of shared memory computers with OpenMP and MPI hybrid programming, and a simulation algorithm that links cellular activity with the ECG. Results We demonstrate that electrical activities at channel, cell, and organ levels can be traced and captured conveniently in our extended cellular automaton system. Examples of some ECG waveforms simulated with a 2-D slice are given to support the ECG simulation algorithm. A performance evaluation of the 3-D model on a four-node cluster is also given. Conclusions Quantitative multicellular modeling with extended cellular automata is a highly efficient and widely applicable method to weave experimental data at different levels into computational models. This process can be used to investigate complex and collective biological activities that can be described neither by their governing differentiation equations nor by discrete parallel computation. Transparent cluster computing is a convenient and effective method to make time-consuming simulation feasible. Arrhythmias, as a typical case, can be effectively simulated with the methods described. PMID:15339335
Dynamic Simulation of 1D Cellular Automata in the Active aTAM.
Jonoska, Nataša; Karpenko, Daria; Seki, Shinnosuke
2015-07-01
The Active aTAM is a tile based model for self-assembly where tiles are able to transfer signals and change identities according to the signals received. We extend Active aTAM to include deactivation signals and thereby allow detachment of tiles. We show that the model allows a dynamic simulation of cellular automata with assemblies that do not record the entire computational history but only the current updates of the states, and thus provide a way for (a) algorithmic dynamical structural changes in the assembly and (b) reusable space in self-assembly. The simulation is such that at a given location the sequence of tiles that attach and detach corresponds precisely to the sequence of states the synchronous cellular automaton generates at that location.
Dynamic Simulation of 1D Cellular Automata in the Active aTAM
Jonoska, Nataša; Karpenko, Daria; Seki, Shinnosuke
2016-01-01
The Active aTAM is a tile based model for self-assembly where tiles are able to transfer signals and change identities according to the signals received. We extend Active aTAM to include deactivation signals and thereby allow detachment of tiles. We show that the model allows a dynamic simulation of cellular automata with assemblies that do not record the entire computational history but only the current updates of the states, and thus provide a way for (a) algorithmic dynamical structural changes in the assembly and (b) reusable space in self-assembly. The simulation is such that at a given location the sequence of tiles that attach and detach corresponds precisely to the sequence of states the synchronous cellular automaton generates at that location. PMID:27789918
Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks
Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez
2016-01-01
Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability. PMID:27874024
Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks
NASA Astrophysics Data System (ADS)
Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez
2016-11-01
Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.
Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks.
Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez
2016-11-22
Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.
Garijo, N; Manzano, R; Osta, R; Perez, M A
2012-12-07
Cell migration and proliferation has been modelled in the literature as a process similar to diffusion. However, using diffusion models to simulate the proliferation and migration of cells tends to create a homogeneous distribution in the cell density that does not correlate to empirical observations. In fact, the mechanism of cell dispersal is not diffusion. Cells disperse by crawling or proliferation, or are transported in a moving ﬂuid. The use of cellular automata, particle models or cell-based models can overcome this limitation. This paper presents a stochastic cellular automata model to simulate the proliferation, migration and differentiation of cells. These processes are considered as completely stochastic as well as discrete. The model developed was applied to predict the behaviour of in vitro cell cultures performed with adult muscle satellite cells. Moreover, non homogeneous distribution of cells has been observed inside the culture well and, using the above mentioned stochastic cellular automata model, we have been able to predict this heterogeneous cell distribution and compute accurate quantitative results. Differentiation was also incorporated into the computational simulation. The results predicted the myotube formation that typically occurs with adult muscle satellite cells. In conclusion, we have shown how a stochastic cellular automata model can be implemented and is capable of reproducing the in vitro behaviour of adult muscle satellite cells.
NASA Astrophysics Data System (ADS)
Fischer, P.; Jardani, A.; Lecoq, N.
2017-03-01
Inverse problem permits to map the subsurface properties from a few observed data. The inverse problem can be physically constrained by a priori information on the property distribution in order to limit the nonuniqueness of the solution. The geostatistical information is often chosen as a priori information; however, when the field properties present a spatial locally distributed high variability, the geostatistical approach becomes inefficient. Therefore, we propose a new method adapted for fields presenting linear structures (such as a fractured field). The Cellular Automata-based Deterministic Inversion (CADI) method is, as far as we know when this paper is produced, the first inversion method which permits a deterministic inversion based on a Bayesian approach and using a dynamic optimization to generate different linear structures iteratively. The model is partitioned in cellular automaton subspaces, each one controlling a different zone of the model. A cellular automata subspace structures the properties of the model in two units ("structure" and "background") and control their dispensing direction and their values. The partitioning of the model in subspaces permits to monitor a large-scale structural model with only a few pilot-parameters and to generate linear structures with local direction changes. Thereby, the algorithm can easily handle with large-scale structures, and a sensitivity analysis is possible on these structural pilot-parameters, which permits to considerably accelerate the optimization process in order to find the best structural geometry. The algorithm has been successfully tested on simple, to more complex, theoretical models with different inversion techniques by using seismic and hydraulic data.
NASA Astrophysics Data System (ADS)
Jardani, A.; Fischer, P.; Lecoq, N.
2016-12-01
Inverse problem permits to map the subsurface properties from the data of a field investigation. The inverse problem can be physically constrained by a priori information on the properties distribution in order to limit the non-uniqueness of the solution. In this case, geostatistical information are often chosen as a priori information, because they are simple to incorporate as a covariance function and they produce realistic model in many cases. But when field properties present a spatial locally-distributed high variability, a geostatistical approach on the properties distribution becomes inefficient. Therefore, we propose a new method adapted for fields presenting linear structures (such as a fractured field). The Cellular Automata-based Deterministic Inversion (CADI) method is, as far as we know, the first inversion method which permits a deterministic inversion based on a Bayesian approach and using a dynamic optimization to generate different linear structures iteratively. The model is partitioned in cellular automaton subspaces, each one controlling a different zone of the model. A cellular automata subspace structures the properties of the model in two units (`structure' and `background') and control their dispensing direction and their values. The partitioning of the model in subspaces permit to monitor a large-scale structural model with only a few pilot-parameters and to generate linear structures with local direction changes. Thereby, the algorithm can easily handle with large-scale structures, and a sensitivity analysis is possible on these structural pilot-parameters, which permits to considerably accelerate the optimization process in order to find the best structural geometry to reproduce the data. The algorithm has been successfully tested on simple, to more complex, theoretical models with different inversion technics (linear, non-linear and joint inversion), by using seismic and hydraulic data.
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.
Cellular automata traffic flow behavior at the intersection of two roads
NASA Astrophysics Data System (ADS)
Marzoug, R.; Ez-Zahraouy, H.; Benyoussef, A.
2014-06-01
The control of vehicles in urban traffic is a requirement to maximize the flow and to ensure the safety of traffic. Using the cellular automata Nagel-Schreckenberg (NaSch) model within a parallel dynamic update, we studied the effect of the intersection of two symmetrical roads, with typical periodic boundary conditions. It is found that the fundamental diagram depends strongly on the probability P of priority and the probability P1 of changing the road at the intersection. Beside the free flow, the platoon and the jamming phases, the fundamental diagram exhibits a fourth new phase occurring for any value of P ≠ 0.5, which disappears gradually as one increases the probability P, and disappears completely for P = 0.5. The effects of the braking probability Pb on the fundamental diagram and space time structures are also computed for different values of maximal velocities.
Modeling and Simulation for Urban Rail Traffic Problem Based on Cellular Automata
NASA Astrophysics Data System (ADS)
Xu, Yan; Cao, Cheng-Xun; Li, Ming-Hua; Luo, Jin-Long
2012-12-01
Based on the Nagel-Schreckenberg model, we propose a new cellular automata model to simulate the urban rail traffic flow under moving block system and present a new minimum instantaneous distance formula under pure moving block. We also analyze the characteristics of the urban rail traffic flow under the influence of train density, station dwell times, the length of train, and the train velocity. Train delays can be decreased effectively through flexible departure intervals according to the preceding train type before its departure. The results demonstrate that a suitable adjustment of the current train velocity based on the following train velocity can greatly shorten the minimum departure intervals and then increase the capacity of rail transit.
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.
Modeling Immune Network Through Cellular Automata:. a Unified Mechanism of Immunological Memory
NASA Astrophysics Data System (ADS)
Chowdhury, Debashish; Deshpande, Varsha; Stauffer, Dietrich
The populations of the various types of immunocompetent cells in the immune system are described as cellular automata and the population dynamics of these cells are formulated in terms of dynamical maps in discrete time. Both intra-clonal interactions (i.e., interactions among the cell types belonging to the same clone) and inter-clonal interactions (i.e., interactions among the cell types belonging to different clones) are included in the models proposed here. While the intra-clonal interactions are shown to play a crucial role in the primary response of some clones and in the formation of the immunological memory, the inter-clonal interactions are responsible for retaining the memory through a dynamical process driven by the mutual stimulation of the clones. We present the results for two different types of connectivity, namely, a “necklace” network and a network in “shape space”.
Benzhai, Hai; Lei, Liu; Ge, Qin; Yuwan, Peng; Ping, Li; Qingxiang, Yang; Hailei, Wang
2014-10-01
In the present paper, aerobic granules were developed in a sequencing batch reactor (SBR) using synthetic wastewater, and 81 % of granular rate was obtained after 15-day cultivation. Aerobic granules have a 96 % BOD removal to the wastewater, and the reactor harbors a mount of biomass including bacteria, fungi and protozoa. In view of the complexity of kinetic behaviors of sludge and biological mechanisms of the granular SBR, a cellular automata model was established to simulate the process of wastewater treatment. The results indicate that the model not only visualized the complex adsorption and degradation process of aerobic granules, but also well described the BOD removal of wastewater and microbial growth in the reactor. Thus, CA model is suitable for simulation of synthetic wastewater treatment. This is the first report about dynamical and visual simulation of treatment process of synthetic wastewater in a granular SBR.
A testable parity conservative gate in quantum-dot cellular automata
NASA Astrophysics Data System (ADS)
Karkaj, Ehsan Taher; Heikalabad, Saeed Rasouli
2017-01-01
There are important challenges in current VLSI technology such as feature size. New technologies are emerging to overcome these challenges. One of these technologies is quantum-dot cellular automata (QCA) but it also has some disadvantages. One of the very important challenges in QCA is the occurrence of faults due to its very small area. There are different ways to overcome this challenge, one of which is the testable logic gate. There are two types of testable gate; reversible gate, and conservative gate. We propose a new testable parity conservative gate in this paper. This gate is simulated with QCADesigner and compared with previous structures. Power dissipation of proposed gate investigated using QCAPro simulator as an accurate power estimator tool.
NASA Astrophysics Data System (ADS)
Vargas, David L.
Emerging quantum simulator technologies provide a new challenge to quantum many body theory. Quantifying the emergent order in and predicting the dynamics of such complex quantum systems requires a new approach. We develop such an approach based on complex network analysis of quantum mutual information. First, we establish the usefulness of quantum mutual information complex networks by reproducing the phase diagrams of transverse Ising and Bose-Hubbard models. By quantifying the complexity of quantum cellular automata we then demonstrate the applicability of complex network theory to non-equilibrium quantum dynamics. We conclude with a study of student collaboration networks, correlating a student's role in a collaboration network with their grades. This work thus initiates a quantitative theory of quantum complexity and provides a new tool for physics education research. (Abstract shortened by ProQuest.).
New insights into discretization effects in cellular automata models for pedestrian evacuation
NASA Astrophysics Data System (ADS)
Guo, Ren-Yong
2014-04-01
We develop a cellular automata model with finer discretization of space and higher walking velocities more than one cell. The model is used to simulate the evacuation process of pedestrians from a room with an exit. By simulation experiments, we find subtle effects of the discretization degree and walking velocities on the shape of the crowd near the exit, the evacuation time of each individual at different locations, and the evacuation efficiency of pedestrians formulated by two time indicators. We also investigate the relations between the exit flow and the exit width, formulated by the model, and compare the flow-width relations with those obtained by laboratory experiments in the existing literatures. This study is helpful for the validation and calibration of microscopic pedestrian models with discrete space representation and further narrowing the gap between these models’ theory and their application to engineering.
A novel FPGA-programmable switch matrix interconnection element in quantum-dot cellular automata
NASA Astrophysics Data System (ADS)
Hashemi, Sara; Rahimi Azghadi, Mostafa; Zakerolhosseini, Ali; Navi, Keivan
2015-04-01
The Quantum-dot cellular automata (QCA) is a novel nanotechnology, promising extra low-power, extremely dense and very high-speed structure for the construction of logical circuits at a nanoscale. In this paper, initially previous works on QCA-based FPGA's routing elements are investigated, and then an efficient, symmetric and reliable QCA programmable switch matrix (PSM) interconnection element is introduced. This element has a simple structure and offers a complete routing capability. It is implemented using a bottom-up design approach that starts from a dense and high-speed 2:1 multiplexer and utilise it to build the target PSM interconnection element. In this study, simulations of the proposed circuits are carried out using QCAdesigner, a layout and simulation tool for QCA circuits. The results demonstrate high efficiency of the proposed designs in QCA-based FPGA routing.
NASA Astrophysics Data System (ADS)
Argollo de Menezes, Marcio; Brigatti, Edgardo; Schwämmle, Veit
2013-08-01
Microbiological systems evolve to fulfil their tasks with maximal efficiency. The immune system is a remarkable example, where the distinction between self and non-self is made by means of molecular interaction between self-proteins and antigens, triggering affinity-dependent systemic actions. Specificity of this binding and the infinitude of potential antigenic patterns call for novel mechanisms to generate antibody diversity. Inspired by this problem, we develop a genetic algorithm where agents evolve their strings in the presence of random antigenic strings and reproduce with affinity-dependent rates. We ask what is the best strategy to generate diversity if agents can rearrange their strings a finite number of times. We find that endowing each agent with an inheritable cellular automaton rule for performing rearrangements makes the system more efficient in pattern-matching than if transformations are totally random. In the former implementation, the population evolves to a stationary state where agents with different automata rules coexist.
Traffic Cellular Automata Simulation of a Congested Round-About in Mauritius
NASA Astrophysics Data System (ADS)
Fowdur, S. C.; Rughooputh, S. D. D. V.
In this paper a Traffic Cellular Automata (TCA) simulation of a highly congested round-about in Mauritius is performed. The simulations are performed using a multi-cell model that includes anticipation and probability randomization. The simulation model is first calibrated to match actual traffic count statistics taken at the round-about. The topology of the round-about is then modified and the TCA model is used to predict the impact on the congestion level of different changes made. The simulation results enable the assessment of the impact on the traffic density and travel time of the different modifications made. It has been found that the construction of a flyover bridge at the round-about will be the most convenient solution to alleviate congestion and improve the flux significantly.
Simulation of abrasive water jet cutting process: Part 2. Cellular automata approach
NASA Astrophysics Data System (ADS)
Orbanic, Henri; Junkar, Mihael
2004-11-01
A new two-dimensional cellular automata (CA) model for the simulation of the abrasive water jet (AWJ) cutting process is presented. The CA calculates the shape of the cutting front, which can be used as an estimation of the surface quality. The cutting front is formed based on material removal rules and AWJ propagation rules. The material removal rule calculates when a particular part of the material will be removed with regard to the energy of AWJ. The AWJ propagation rule calculates the distribution of AWJ energy through CA by using a weighted average. The modelling with CA also provides a visual narrative of the moving of the cutting front, which is hard to observe in real process. The algorithm is fast and has been successfully tested in comparison to cutting fronts obtained with cutting experiments of aluminium alloy.
Structural distortions in molecular-based quantum cellular automata: a minimal model based study.
Bonilla, Alejandro Santana; Gutierrez, Rafael; Sandonas, Leonardo Medrano; Nozaki, Daijiro; Bramanti, Alessandro Paolo; Cuniberti, Gianaurelio
2014-09-07
Molecular-based quantum cellular automata (m-QCA), as an extension of quantum-dot QCAs, offer a novel alternative in which binary information can be encoded in the molecular charge configuration of a cell and propagated via nearest-neighbor Coulombic cell-cell interactions. Appropriate functionality of m-QCAs involves a complex relationship between quantum mechanical effects, such as electron transfer processes within the molecular building blocks, and electrostatic interactions between cells. The influence of structural distortions of single m-QCA are addressed in this paper within a minimal model using an diabatic-to-adiabatic transformation. We show that even small changes of the classical square geometry between driver and target cells, such as those induced by distance variations or shape distortions, can make cells respond to interactions in a far less symmetric fashion, modifying and potentially impairing the expected computational behavior of the m-QCA.
[Allelopathy of invasive weeds: a simulation study with cellular automata model].
Liu, Yinghu; Xie, Li; Luo, Shiming; Chen, Shi; Zeng, Rensen
2006-02-01
Cellular automata model is a simulation approach to describe the complicate behavior of a system, and suitable to study the spatial and temporal dynamics of plant community. In this paper, the model was used to simulate the different sensitivity toall invasion process of an allelochemicals-containing exotic species to the community of two native species with different sensitivity to allelochemicals, and the spatial and temporal dynamics of native and invasive species. The simulation was conducted by biological response and negative exponential distribution models, and the results showed that exotic species could successfully invade the community of two native species with different sensitivity to allelochemicals, but only coexist with one sensitive and one resistant species. The resistance of plant community to invasive weeds depended on its species function structure.
NASA Astrophysics Data System (ADS)
Adamatzky, Andrew
2012-11-01
Excitable cellular automata with dynamical excitation interval exhibit a wide range of space-time dynamics based on an interplay between propagating excitation patterns which modify excitability of the automaton cells. Such interactions leads to formation of standing domains of excitation, stationary waves and localized excitations. We analyzed morphological and generative diversities of the functions studied and characterized the functions with highest values of the diversities. Amongst other intriguing discoveries we found that upper boundary of excitation interval more significantly affects morphological diversity of configurations generated than lower boundary of the interval does and there is no match between functions which produce configurations of excitation with highest morphological diversity and configurations of interval boundaries with highest morphological diversity. Potential directions of future studies of excitable media with dynamically changing excitability may focus on relations of the automaton model with living excitable media, e.g. neural tissue and muscles, novel materials with memristive properties and networks of conductive polymers.
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.
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.
Emergency evacuation models based on cellular automata with route changes and group fields
NASA Astrophysics Data System (ADS)
Pereira, L. A.; Burgarelli, D.; Duczmal, L. H.; Cruz, F. R. B.
2017-05-01
In this paper, we propose an extension of cellular automata models applied to emergency evacuation pedestrian dynamics. The new extensions are the route change probabilities and group fields. The first extension allows for pedestrians to change direction when necessary to access an alternate exit route. The second extension adds a field that makes groups of pedestrians always walk close to each other and exit together. Several experiments were conducted to study the effects of these new extensions, first to verify the associated collective phenomena and to verify the effect with the security performance measures, more precisely, in the evacuation time, as well as to perform comparisons with other previous models. The main conclusions are that the effects of these new extensions effectively modify the security performance measures and can therefore be important for improving the models and providing better estimates.
Design of efficient full adder in quantum-dot cellular automata.
Sen, Bibhash; Rajoria, Ayush; 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 μ m(2)) 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.
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
Performance of 1D quantum cellular automata in the presence of error
NASA Astrophysics Data System (ADS)
McNally, Douglas M.; Clemens, James P.
2016-09-01
This work expands a previous block-partitioned quantum cellular automata (BQCA) model proposed by Brennen and Williams [Phys. Rev. A. 68, 042311 (2003)] to incorporate physically realistic error models. These include timing errors in the form of over- and under-rotations of quantum states during computational gate sequences, stochastic phase and bit flip errors, as well as undesired two-bit interactions occurring during single-bit gate portions of an update sequence. A compensation method to counteract the undesired pairwise interactions is proposed and investigated. Each of these error models is implemented using Monte Carlo simulations for stochastic errors and modifications to the prescribed gate sequences to account for coherent over-rotations. The impact of these various errors on the function of a QCA gate sequence is evaluated using the fidelity of the final state calculated for four quantum information processing protocols of interest: state transfer, state swap, GHZ state generation, and entangled pair generation.
Optimal placement of fast cut back units based on the theory of cellular automata and agent
NASA Astrophysics Data System (ADS)
Yan, Jun; Yan, Feng
2017-06-01
The thermal power generation units with the function of fast cut back could serve power for auxiliary system and keep island operation after a major blackout, so they are excellent substitute for the traditional black-start power sources. Different placement schemes for FCB units have different influence on the subsequent restoration process. Considering the locality of the emergency dispatching rules, the unpredictability of specific dispatching instructions and unexpected situations like failure of transmission line energization, a novel deduction model for network reconfiguration based on the theory of cellular automata and agent is established. Several indexes are then defined for evaluating the placement schemes for FCB units. The attribute weights determination method based on subjective and objective integration and grey relational analysis are combinatorically used to determine the optimal placement scheme for FCB unit. The effectiveness of the proposed method is validated by the test results on the New England 10-unit 39-bus power system.
Electoral surveys’ influence on the voting processes: a cellular automata model
NASA Astrophysics Data System (ADS)
Alves, S. G.; Oliveira Neto, N. M.; Martins, M. L.
2002-12-01
Nowadays, in societies threatened by atomization, selfishness, short-term thinking, and alienation from political life, there is a renewed debate about classical questions concerning the quality of democratic decision making. In this work a cellular automata model for the dynamics of free elections, based on the social impact theory is proposed. By using computer simulations, power-law distributions for the size of electoral clusters and decision time have been obtained. The major role of broadcasted electoral surveys in guiding opinion formation and stabilizing the “status quo” was demonstrated. Furthermore, it was shown that in societies where these surveys are manipulated within the universally accepted statistical error bars, even a majoritary opposition could be hindered from reaching power through the electoral path.
Operator-sum models of quantum decoherence in molecular quantum-dot cellular automata
NASA Astrophysics Data System (ADS)
Ramsey, Jackson S.; Blair, Enrique P.
2017-08-01
Quantum-dot cellular automata is a paradigm for classical computing which departs from the transistor paradigm and provides a system in which quantum phenomena may be studied. Here, the elementary computing device is a cell, a structure having multiple quantum dots and a few mobile charges. A specific operator-sum representation is developed for an exactly modeled double-dot, molecular cell within an environment of N similar neighboring molecules. While an operator-sum representation is not unique, a specific model can be determined by selecting a particular environmental basis. We select the environment's computational basis and calculate the specific and full set of 2N Kraus operators, which match exactly previous models of quantum decoherence in this system. Finally, the timescale for environmental interaction is characterized, enabling the reduction of the large set of Kraus operators to an approximate pair of Kraus operators, exact in the limit of large N.
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.
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.
Consequences of landscape fragmentation on Lyme disease risk: a cellular automata approach.
Li, Sen; Hartemink, Nienke; Speybroeck, Niko; Vanwambeke, Sophie O
2012-01-01
The abundance of infected Ixodid ticks is an important component of human risk of Lyme disease, and various empirical studies have shown that this is associated, at least in part, to landscape fragmentation. In this study, we aimed at exploring how varying woodland fragmentation patterns affect the risk of Lyme disease, through infected tick abundance. A cellular automata model was developed, incorporating a heterogeneous landscape with three interactive components: an age-structured tick population, a classical disease transmission function, and hosts. A set of simplifying assumptions were adopted with respect to the study objective and field data limitations. In the model, the landscape influences both tick survival and host movement. The validation of the model was performed with an empirical study. Scenarios of various landscape configurations (focusing on woodland fragmentation) were simulated and compared. Lyme disease risk indices (density and infection prevalence of nymphs) differed considerably between scenarios: (i) the risk could be higher in highly fragmented woodlands, which is supported by a number of recently published empirical studies, and (ii) grassland could reduce the risk in adjacent woodland, which suggests landscape fragmentation studies of zoonotic diseases should not focus on the patch-level woodland patterns only, but also on landscape-level adjacent land cover patterns. Further analysis of the simulation results indicated strong correlations between Lyme disease risk indices and the density, shape and aggregation level of woodland patches. These findings highlight the strong effect of the spatial patterns of local host population and movement on the spatial dynamics of Lyme disease risks, which can be shaped by woodland fragmentation. In conclusion, using a cellular automata approach is beneficial for modelling complex zoonotic transmission systems as it can be combined with either real world landscapes for exploring direct spatial
Consequences of Landscape Fragmentation on Lyme Disease Risk: A Cellular Automata Approach
Li, Sen; Hartemink, Nienke; Speybroeck, Niko; Vanwambeke, Sophie O.
2012-01-01
The abundance of infected Ixodid ticks is an important component of human risk of Lyme disease, and various empirical studies have shown that this is associated, at least in part, to landscape fragmentation. In this study, we aimed at exploring how varying woodland fragmentation patterns affect the risk of Lyme disease, through infected tick abundance. A cellular automata model was developed, incorporating a heterogeneous landscape with three interactive components: an age-structured tick population, a classical disease transmission function, and hosts. A set of simplifying assumptions were adopted with respect to the study objective and field data limitations. In the model, the landscape influences both tick survival and host movement. The validation of the model was performed with an empirical study. Scenarios of various landscape configurations (focusing on woodland fragmentation) were simulated and compared. Lyme disease risk indices (density and infection prevalence of nymphs) differed considerably between scenarios: (i) the risk could be higher in highly fragmented woodlands, which is supported by a number of recently published empirical studies, and (ii) grassland could reduce the risk in adjacent woodland, which suggests landscape fragmentation studies of zoonotic diseases should not focus on the patch-level woodland patterns only, but also on landscape-level adjacent land cover patterns. Further analysis of the simulation results indicated strong correlations between Lyme disease risk indices and the density, shape and aggregation level of woodland patches. These findings highlight the strong effect of the spatial patterns of local host population and movement on the spatial dynamics of Lyme disease risks, which can be shaped by woodland fragmentation. In conclusion, using a cellular automata approach is beneficial for modelling complex zoonotic transmission systems as it can be combined with either real world landscapes for exploring direct spatial
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.
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.
Cellular automata and integrodifferential equation models for cell renewal in mosaic tissues
Bloomfield, J. M.; Sherratt, J. A.; Painter, K. J.; Landini, G.
2010-01-01
Mosaic tissues are composed of two or more genetically distinct cell types. They occur naturally, and are also a useful experimental method for exploring tissue growth and maintenance. By marking the different cell types, one can study the patterns formed by proliferation, renewal and migration. Here, we present mathematical modelling suggesting that small changes in the type of interaction that cells have with their local cellular environment can lead to very different outcomes for the composition of mosaics. In cell renewal, proliferation of each cell type may depend linearly or nonlinearly on the local proportion of cells of that type, and these two possibilities produce very different patterns. We study two variations of a cellular automaton model based on simple rules for renewal. We then propose an integrodifferential equation model, and again consider two different forms of cellular interaction. The results of the continuous and cellular automata models are qualitatively the same, and we observe that changes in local environment interaction affect the dynamics for both. Furthermore, we demonstrate that the models reproduce some of the patterns seen in actual mosaic tissues. In particular, our results suggest that the differing patterns seen in organ parenchymas may be driven purely by the process of cell replacement under different interaction scenarios. PMID:20375040
Cellular automata and integrodifferential equation models for cell renewal in mosaic tissues.
Bloomfield, J M; Sherratt, J A; Painter, K J; Landini, G
2010-11-06
Mosaic tissues are composed of two or more genetically distinct cell types. They occur naturally, and are also a useful experimental method for exploring tissue growth and maintenance. By marking the different cell types, one can study the patterns formed by proliferation, renewal and migration. Here, we present mathematical modelling suggesting that small changes in the type of interaction that cells have with their local cellular environment can lead to very different outcomes for the composition of mosaics. In cell renewal, proliferation of each cell type may depend linearly or nonlinearly on the local proportion of cells of that type, and these two possibilities produce very different patterns. We study two variations of a cellular automaton model based on simple rules for renewal. We then propose an integrodifferential equation model, and again consider two different forms of cellular interaction. The results of the continuous and cellular automata models are qualitatively the same, and we observe that changes in local environment interaction affect the dynamics for both. Furthermore, we demonstrate that the models reproduce some of the patterns seen in actual mosaic tissues. In particular, our results suggest that the differing patterns seen in organ parenchymas may be driven purely by the process of cell replacement under different interaction scenarios.
Cellular automaton formulation of passive scalar dynamics
NASA Technical Reports Server (NTRS)
Chen, Hudong; Matthaeus, William H.
1987-01-01
Cellular automata modeling of the advection of a passive scalar in a two-dimensional flow is examined in the context of discrete lattice kinetic theory. It is shown that if the passive scalar is represented by tagging or 'coloring' automation particles a passive advection-diffusion equation emerges without use of perturbation expansions. For the specific case of the hydrodynamic lattice gas model of Frisch et al. (1986), the diffusion coefficient is calculated by perturbation.
Cellular automaton formulation of passive scalar dynamics
NASA Technical Reports Server (NTRS)
Chen, Hudong; Matthaeus, William H.
1987-01-01
Cellular automata modeling of the advection of a passive scalar in a two-dimensional flow is examined in the context of discrete lattice kinetic theory. It is shown that if the passive scalar is represented by tagging or 'coloring' automation particles a passive advection-diffusion equation emerges without use of perturbation expansions. For the specific case of the hydrodynamic lattice gas model of Frisch et al. (1986), the diffusion coefficient is calculated by perturbation.
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.
NASA Astrophysics Data System (ADS)
Pandey, Ras B.
1998-03-01
A stochastic cellular automata (SCA) approach is introduced to study the growth and decay of cellular population in an immune response model relevant to HIV. Four cell types are considered: macrophages (M), helper cells (H), cytotoxic cells (C), and viral infected cells (V). Mobility of the cells is introduced and viral mutation is considered probabilistically. In absence of mutation, the population of the host cells, helper (N_H) and cytotxic (N_C) cells in particular, dominates over the viral population (N_V), i.e., N_H, NC > N_V, the immune system wins over the viral infection. Variation of cellular population with time exhibits oscillations. The amplitude of oscillations in variation of N_H, NC and NV with time decreases at high mobility even at low viral mutation; the rate of viral growth is nonmonotonic with NV > N_H, NC in the long time regime. The viral population is much higher than that of the host cells at higher mutation rate, a possible cause of AIDS.
Cellular automata models for diffusion of information and highway traffic flow
NASA Astrophysics Data System (ADS)
Fuks, Henryk
In the first part of this work we study a family of deterministic models for highway traffic flow which generalize cellular automaton rule 184. This family is parameterized by the speed limit m and another parameter k that represents degree of 'anticipatory driving'. We compare two driving strategies with identical maximum throughput: 'conservative' driving with high speed limit and 'anticipatory' driving with low speed limit. Those two strategies are evaluated in terms of accident probability. We also discuss fundamental diagrams of generalized traffic rules and examine limitations of maximum achievable throughput. Possible modifications of the model are considered. For rule 184, we present exact calculations of the order parameter in a transition from the moving phase to the jammed phase using the method of preimage counting, and use this result to construct a solution to the density classification problem. In the second part we propose a probabilistic cellular automaton model for the spread of innovations, rumors, news, etc., in a social system. We start from simple deterministic models, for which exact expressions for the density of adopters are derived. For a more realistic model, based on probabilistic cellular automata, we study the influence of a range of interaction R on the shape of the adoption curve. When the probability of adoption is proportional to the local density of adopters, and individuals can drop the innovation with some probability p, the system exhibits a second order phase transition. Critical line separating regions of parameter space in which asymptotic density of adopters is positive from the region where it is equal to zero converges toward the mean-field line when the range of the interaction increases. In a region between R=1 critical line and the mean-field line asymptotic density of adopters depends on R, becoming zero if R is too small (smaller than some critical value). This result demonstrates the importance of connectivity in
Kavianpour, Hamidreza; Vasighi, Mahdi
2017-02-01
Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.
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.
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)
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.
Gary Achtemeier
2012-01-01
A cellular automata fire model represents âelementsâ of fire by autonomous agents. A few simple algebraic expressions substituted for complex physical and meteorological processes and solved iteratively yield simulations for âsuper-diffusiveâ fire spread and coupled surface-layer (2-m) fireâatmosphere processes. Pressure anomalies, which are integrals of the thermal...
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.
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
Toward quantum-dot cellular automata units: thiolated-carbazole linked bisferrocenes
NASA Astrophysics Data System (ADS)
Arima, Valentina; Iurlo, Matteo; Zoli, Luca; Kumar, Susmit; Piacenza, Manuel; Della Sala, Fabio; Matino, Francesca; Maruccio, Giuseppe; Rinaldi, Ross; Paolucci, Francesco; Marcaccio, Massimo; Cozzi, Pier Giorgio; Bramanti, Alessandro Paolo
2012-01-01
Quantum-dot Cellular Automata (QCA) exploit quantum confinement, tunneling and electrostatic interaction for transistorless digital computing. Implementation at the molecular scale requires carefully tailored units which must obey several structural and functional constraints, ranging from the capability to confine charge efficiently on different `quantum-dot centers'--in order to sharply encode the Boolean states--up to the possibility of having their state blanked out upon application of an external signal. In addition, the molecular units must preserve their geometry in the solid state, to interact electrostatically in a controlled way. Here, we present a novel class of organometallic molecules, 6-3,6-bis(1-ethylferrocen)-9H-carbazol-9-yl-6-hexan-1-thiols, which are engineered to satisfy all such crucial requirements at once, as confirmed by electrochemistry and scanning tunneling microscopy measurements, and first principles density functional calculations.Quantum-dot Cellular Automata (QCA) exploit quantum confinement, tunneling and electrostatic interaction for transistorless digital computing. Implementation at the molecular scale requires carefully tailored units which must obey several structural and functional constraints, ranging from the capability to confine charge efficiently on different `quantum-dot centers'--in order to sharply encode the Boolean states--up to the possibility of having their state blanked out upon application of an external signal. In addition, the molecular units must preserve their geometry in the solid state, to interact electrostatically in a controlled way. Here, we present a novel class of organometallic molecules, 6-3,6-bis(1-ethylferrocen)-9H-carbazol-9-yl-6-hexan-1-thiols, which are engineered to satisfy all such crucial requirements at once, as confirmed by electrochemistry and scanning tunneling microscopy measurements, and first principles density functional calculations. Electronic supplementary information (ESI
Quantum Dot Cellular Automata: Computing with Coupled Quantum-Dot Molecules
NASA Astrophysics Data System (ADS)
Porod, Wolfgang
1998-05-01
We have recently proposed a scheme of using coupled quantum dots to realize digital computing elements.(C. S. Lent, P. D. Tougaw, W. Porod, and G. H. Bernstein, Nanotechnology 4, 49 (1993); C. S. Lent, P. D. Tougaw, and W. Porod, Applied Physics Letters 62, 714 (1993).) Our scheme was inspired by recent work on nanometer-scale lithography in semiconductors which has permitted the construction of quantum dots which may be viewed as artificial atoms; furthermore, the principle of dot-dot coupling has also been demonstrated, thus realizing artificial semiconductor molecules. This talk will review the work of the Notre Dame group on the theory and modeling of cellular arrays of coupled quantum-dot molecules, which we refer to as quantum-dot cellular automata (QCA). We consider inhomogeneous arrays of quantum-dot molecules, where each molecule forms the basic unit in a cellular automaton-type array architecture. These cells (molecules) consists of four or five quantum dots in close enough proximity to enable electron tunneling between dots. Coulomb repulsion between electrons in the cell results in a bistable ground state whose configuration is determined by the configuration of neighboring cells. The electrons tend to occupy antipodal sites in one of two ground-state configurations which may be used to encode binary information. We have demonstrated that Boolean logic gates can be constructed, and simple design rules permit the fabrication of any logic function. The basic principle of QCA operation was demonstrated in recent experiments.(A. O. Orlov, I. Amlani, G. H. Bernstein, C. S. Lent, and G. L. Snider, Science 277, 928, (1997).)
Baradaran, Samaneh; Maleknasr, Niaz; Setayeshi, Saeed; Akbari, Mohammad Esmaeil
2014-01-01
Background Alpha particle irradiation from radon progeny is one of the major natural sources of effective dose in the public population. Oncogenic transformation is a biological effectiveness of radon progeny alpha particle hits. The biological effects which has caused by exposure to radon, were the main result of a complex series of physical, chemical, biological and physiological interactions. The cellular and molecular mechanisms for radon-induced carcinogenesis have not been clear yet. Methods Various biological models, including cultured cells and animals, have been found useful for studying the carcinogenesis effects of radon progeny alpha particles. In this paper, sugars cape cellular automata have been presented for computational study of complex biological effect of radon progeny alpha particles in lung bronchial airways. The model has included mechanism of DNA damage, which has been induced alpha particles hits, and then formation of transformation in the lung cells. Biomarkers were an objective measure or evaluation of normal or abnormal biological processes. In the model, the metabolism rate of infected cell has been induced alpha particles traversals, as a biomarker, has been followed to reach oncogenic transformation. Results The model results have successfully validated in comparison with “in vitro oncogenic transformation data” for C3H 10T1/2 cells. This model has provided an opportunity to study the cellular and molecular changes, at the various stages in radiation carcinogenesis, involving human cells. Conclusion It has become well known that simulation could be used to investigate complex biomedical systems, in situations where traditional methodologies were difficult or too costly to employ. PMID:25250147
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
Cellular automata for simulating land use changes based on support vector machines
NASA Astrophysics Data System (ADS)
Yang, Qingsheng; Li, Xia; Shi, Xun
2008-06-01
Cellular automata (CA) have been increasingly used to simulate urban sprawl and land use dynamics. A major issue in CA is defining appropriate transition rules based on training data. Linear boundaries have been widely used to define the rules. However, urban land use dynamics and many other geographical phenomena are highly complex and require nonlinear boundaries for the rules. In this study, we tested the support vector machines (SVM) as a method for constructing nonlinear transition rules for CA. SVM is good at dealing with nonlinear complex relationships. Its basic idea is to project input vectors to a higher dimensional Hilbert feature space, in which an optimal classifying hyperplane can be constructed through structural risk minimization and margin maximization. The optimal hyperplane is unique and its optimality is global. The proposed SVM-CA model was implemented using Visual Basic, ArcObjects®, and OSU-SVM. A case study simulating the urban development in the Shenzhen City, China demonstrates that the proposed model can achieve high accuracy and overcome some limitations of existing CA models in simulating complex urban systems.
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.
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.
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.
Impact of time delay on the dynamics of SEIR epidemic model using cellular automata
NASA Astrophysics Data System (ADS)
Sharma, Natasha; Gupta, Arvind Kumar
2017-04-01
The delay of an infectious disease is significant when aiming to predict its strength and spreading patterns. In this paper the SEIR (susceptible-exposed-infected-recovered) epidemic spread with time delay is analyzed through a two-dimensional cellular automata model. The time delay corresponding to the infectious span, predominantly, includes death during the latency period in due course of infection. The advancement of whole system is described by SEIR transition function complemented with crucial factors like inhomogeneous population distribution, birth and disease independent mortality. Moreover, to reflect more realistic population dynamics some stochastic parameters like population movement and connections at local level are also considered. The existence and stability of disease free equilibrium is investigated. Two prime behavioral patterns of disease dynamics is found depending on delay. The critical value of delay, beyond which there are notable variations in spread patterns, is computed. The influence of important parameters affecting the disease dynamics on basic reproduction number is also examined. The results obtained show that delay plays an affirmative role to control disease progression in an infected host.
Estimation of the spatiotemporal dynamics of snow covered area by using cellular automata models
NASA Astrophysics Data System (ADS)
Pardo-Igúzquiza, Eulogio; Collados-Lara, Antonio-Juan; Pulido-Velazquez, David
2017-07-01
Given the need to consider the cryosphere in water resources management for mountainous regions, the purpose of this paper is to model the daily spatially distributed dynamics of snow covered area (SCA) by using calibrated cellular automata models. For the operational use of the calibrated model, the only data requirements are the altitude of each cell of the spatial discretization of the area of interest and precipitation and temperature indexes for the area of interest. For the calibration step, experimental snow covered area data are needed. Potential uses of the model are to estimate the snow covered area when satellite data are absent, or when they provide a temporal resolution different from the operational resolution, or when the satellite images are useless because they are covered by clouds or because there has been a sensor failure. Another interesting application is the simulation of SCA dynamics for the snow covered area under future climatic scenarios. The model is applied to the Sierra Nevada mountain range, in southern Spain, which is home to significant biodiversity, contains important water resources in its snowpack, and contains the most meridional ski resort in Europe.
Cellular automata simulation of osteoblast growth on microfibrous-carbon-based scaffolds.
Czarnecki, Jarema S; Jolivet, Simon; Blackmore, Mary E; Lafdi, Khalid; Tsonis, Panagiotis A
2014-12-01
The objective of this study was to investigate the use of three fibrous carbon materials (T300, P25, and P120) for bone repair and develop and validate theoretical and computational methods in which bone tissue regeneration and repair could be accurately predicted. T300 was prepared from polyacrylonitrile precursor while P25 and P120 fibers were prepared from pitch, both common fiber precursors. Results showed that osteoblast growth on carbon scaffolds was enhanced with increased crystallinity, surface roughness, and material orientation. For unidirectional scaffolds at 120 h, there was 33% difference in cell growth between T300 and P25 fibers and 64% difference between P25 and P120 fibers. Moreover, for multidirectional fibers at 120 h, there was 35% difference in cell growth between T300 and P25 fibers and 43% difference between P25 and P120 fibers. Results showed that material alignment was integral to promoting cell growth with multidirectional scaffolds having the capacity for greater growth over unidirectional scaffolds. At 120 h there was 24% increase in cell growth between unidirectional alignment and multidirectional alignment on high-crystalline carbon fibers. Ultimately, data indicated that carbon scaffolds exhibited excellent bioactivity and may be tuned to stimulate unique reactions. Additionally, numerical and computational simulations provided evidence that corroborated experimental data with simulations. Results illustrated the capability of cellular automata models for assessing osteoblast cell response to biomaterials.
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 BZ 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.
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.
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.
Computer simulation of a cellular automata model for the immune response in a retrovirus system
NASA Astrophysics Data System (ADS)
Pandey, R. B.
1989-02-01
Immune response in a retrovirus system is modeled by a network of three binary cell elements to take into account some of the main functional features of T4 cells, T8 cells, and viruses. Two different intercell interactions are introduced, one of which leads to three fixed points while the other yields bistable fixed points oscillating between a healthy state and a sick state in a mean field treatment. Evolution of these cells is studied for quenched and annealed random interactions on a simple cubic lattice with a nearest neighbor interaction using inhomogenous cellular automata. Populations of T4 cells and viral cells oscillate together with damping (with constant amplitude) for annealed (quenched) interaction on increasing the value of mixing probability B from zero to a characteristic value B ca ( B cq). For higher B, the average number of T4 cells increases while that of the viral infected cells decreases monotonically on increasing B, suggesting a phase transition at B ca ( B cq).
Computer simulation of a cellular automata model for the immune response in a retrovirus system
Pandey, R.B.
1989-02-01
Immune response in a retrovirus system is modeled by a network of three binary cell elements to take into account some of the main functional features of T4 cells, T8 cells, and viruses. Two different intercell interactions are introduced, one of which leads to three fixed points while the other yields bistable fixed points oscillating between a healthy state and a sick state in a mean field treatment. Evolution of these cells is studied for quenched and annealed random interactions on a simple cubic lattice with a nearest neighbor interaction using inhomogenous cellular automata. Populations of T4 cells and viral cells oscillate together with damping (with constant amplitude) for annealed (quenched) interaction on increasing the value of mixing probability B from zero to a characteristic value B/sub ca/ (B/sub cq/). For higher B, the average number of T4 cells increases while that of the viral infected cells decreases monotonically on increasing B, suggesting a phase transition at B/sub ca/ (B/sub cq/).
On Cesàro Limit Distribution of a Class of Permutative Cellular Automata
NASA Astrophysics Data System (ADS)
Maass, Alejandro; Martinez, Servet
1998-01-01
We study Cesàro means (time averages) of the evolution measures of the class of permutative cellular automata over {0, 1}ℕ defined by (\\varphi _B x)_n = x_{n{kern 1pt} {kern 1pt} + {kern 1pt} {kern 1pt} R} + Pi _{j{kern 1pt} {kern 1pt} = {kern 1pt} {kern 1pt} 0}^{R{kern 1pt} {kern 1pt} - {kern 1pt} {kern 1pt} 1} {kern 1pt} {kern 1pt} {kern 1pt} {kern 1pt} {kern 1pt} {kern 1pt} (1 + b_j + x_{n{kern 1pt} {kern 1pt} + {kern 1pt} {kern 1pt} j} ) where B= b 0 ⋯ b R-1is an aperiodic block in {0, 1} R and operations are taken mod 2. If the initial measure is Bernoulli, we prove that the limit of the Cesàro mean of the first column distribution exists. When R = 1 and B = 1, φ B is the mod 2 sum automaton. For this automaton we show that the limit is the (1/2, 1/2(-Bernoulli measure, and if the initial measure is Markov, we show that the limit of Cesàro mean of the one-site distribution is equidistributed.
Li, Xia; Lao, Chunhua; Liu, Yilun; Liu, Xiaoping; Chen, Yimin; Li, Shaoying; Ai, Bing; He, Zijian
2013-11-30
Ecological security has become a major issue under fast urbanization in China. As the first two cities in this country, Shenzhen and Dongguan issued the ordinance of Eco-designated Line of Control (ELC) to "wire" ecologically important areas for strict protection in 2005 and 2009 respectively. Early warning systems (EWS) are a useful tool for assisting the implementation ELC. In this study, a multi-model approach is proposed for the early warning of illegal development by integrating cellular automata (CA) and artificial neural networks (ANN). The objective is to prevent the ecological risks or catastrophe caused by such development at an early stage. The integrated model is calibrated by using the empirical information from both remote sensing and handheld GPS (global positioning systems). The MAR indicator which is the ratio of missing alarms to all the warnings is proposed for better assessment of the model performance. It is found that the fast urban development has caused significant threats to natural-area protection in the study area. The integration of CA, ANN and GPS provides a powerful tool for describing and predicting illegal development which is in highly non-linear and fragmented forms. The comparison shows that this multi-model approach has much better performances than the single-model approach for the early warning. Compared with the single models of CA and ANN, this integrated multi-model can improve the value of MAR by 65.48% and 5.17% respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.
Palii, Andrew; Tsukerblat, Boris
2016-10-25
In this article we consider two coupled tetrameric mixed-valence (MV) units accommodating electron pairs, which play the role of cells in molecular quantum cellular automata. It is supposed that the Coulombic interaction between instantly localized electrons within the cell markedly inhibits the transfer processes between the redox centers. Under this condition, as well as due to the vibronic localization of the electron pair, the cell can encode binary information, which is controlled by neighboring cells. We show that under certain conditions the two low-lying vibronic spin levels of the cell (ground and first excited states) can be regarded as originating from an effective spin-spin interaction. This is shown to depend on the internal parameters of the cell as well as on the induced polarization. Within this simplified two-level picture we evaluate the quantum entanglement in the system represented by the two electrons in the cell and show how the entanglement within the cell and concurrence can be controlled via polarization of the neighboring cells and temperature.
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.
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.
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.
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.
Emergent protein folding modeled with evolved neural cellular automata using the 3D HP model.
Santos, José; Villot, Pablo; Diéguez, Martin
2014-11-01
We used cellular automata (CA) for the modeling of the temporal folding of proteins. Unlike the focus of the vast research already done on the direct prediction of the final folded conformations, we will model the temporal and dynamic folding process. To reduce the complexity of the interactions and the nature of the amino acid elements, lattice models like HP were used, a model that categorizes the amino acids regarding their hydrophobicity. Taking into account the restrictions of the lattice model, the CA model defines how the amino acids interact through time to obtain a folded conformation. We extended the classical CA models using artificial neural networks for their implementation (neural CA), and we used evolutionary computing to automatically obtain the models by means of Differential Evolution. As the iterative folding also provides the final folded conformation, we can compare the results with those from direct prediction methods of the final protein conformation. Finally, as the neural CA that provides the iterative folding process can be evolved using several protein sequences and used as operators in the folding of another protein with different length, this represents an advantage over the NP-hard complexity of the original problem of the direct prediction.
[A Cellular Automata Model for a Community Comprising Two Plant Species of Different Growth Forms].
Frolov, P V; Zubkova, E V; Komarov, A S
2015-01-01
A cellular automata computer model for the interactions between two plant species of different growth forms--the lime hairgrass Deschampsia caespitosa (L.) P. Beauv., a sod cereal, and the moneywort Lysimachia nummularia L., a ground creeping perennial herb--is considered. Computer experiments on the self-maintenance of the populations of each species against the background of a gradual increase in the share of randomly eliminated individuals, coexistence of the populations of two species, and the effect of the phytogenous field have been conducted. As has been shown, all the studied factors determine the number of individuals and self-sustainability of the simulated populations by the degree of their impact. The limits of action have been determined for individual factors; within these limits, the specific features in plant reproduction and dispersal provide sustainable coexistence of the simulated populations. It has been demonstrated that the constructed model allows for studying the long-term developmental dynamics of the plants belonging to the selected growth forms.
NASA Astrophysics Data System (ADS)
Chen, Tinghuan; Zhang, Meng; Wu, Jianhui; Yuen, Chau; Tong, You
2016-10-01
Because of simple encryption and compression procedure in single step, compressed sensing (CS) is utilized to encrypt and compress an image. Difference of sparsity levels among blocks of the sparsely transformed image degrades compression performance. In this paper, motivated by this difference of sparsity levels, we propose an encryption and compression approach combining Kronecker CS (KCS) with elementary cellular automata (ECA). In the first stage of encryption, ECA is adopted to scramble the sparsely transformed image in order to uniformize sparsity levels. A simple approximate evaluation method is introduced to test the sparsity uniformity. Due to low computational complexity and storage, in the second stage of encryption, KCS is adopted to encrypt and compress the scrambled and sparsely transformed image, where the measurement matrix with a small size is constructed from the piece-wise linear chaotic map. Theoretical analysis and experimental results show that our proposed scrambling method based on ECA has great performance in terms of scrambling and uniformity of sparsity levels. And the proposed encryption and compression method can achieve better secrecy, compression performance and flexibility.
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.
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.
Simulation of bi-direction pedestrian movement using a cellular automata model
NASA Astrophysics Data System (ADS)
Weifeng, Fang; Lizhong, Yang; Weicheng, Fan
2003-04-01
A cellular automata model is presented to simulate the bi-direction pedestrian movement. The pedestrian movement is more complex than vehicular flow for the reason that people are more flexible than cars. Some special technique is introduced considering simple human judgment to make the rules more reasonable. Also the custom in the countries where the pedestrian prefer to walk on the right-hand side of the road are highlighted. By using the model to simulate the bi-direction pedestrian movement, the phase transition phenomena in pedestrian counter flow is presented. Furthermore, the introduction of back stepping breaks the deadlock at the relatively low pedestrian density. By studying the critical density of changing from freely moving state to jammed state with different system sizes and different probabilities of back stepping, we find the critical density increases as the probability of back stepping increases at the same system size. And with the increasing system size, the critical density decreases at the same probability of back stepping according to the scope of system size studied in this paper.
A cellular automata based FPGA realization of a new metaheuristic bat-inspired algorithm
NASA Astrophysics Data System (ADS)
Progias, Pavlos; Amanatiadis, Angelos A.; Spataro, William; Trunfio, Giuseppe A.; Sirakoulis, Georgios Ch.
2016-10-01
Optimization algorithms are often inspired by processes occuring in nature, such as animal behavioral patterns. The main concern with implementing such algorithms in software is the large amounts of processing power they require. In contrast to software code, that can only perform calculations in a serial manner, an implementation in hardware, exploiting the inherent parallelism of single-purpose processors, can prove to be much more efficient both in speed and energy consumption. Furthermore, the use of Cellular Automata (CA) in such an implementation would be efficient both as a model for natural processes, as well as a computational paradigm implemented well on hardware. In this paper, we propose a VHDL implementation of a metaheuristic algorithm inspired by the echolocation behavior of bats. More specifically, the CA model is inspired by the metaheuristic algorithm proposed earlier in the literature, which could be considered at least as efficient than other existing optimization algorithms. The function of the FPGA implementation of our algorithm is explained in full detail and results of our simulations are also demonstrated.
NASA Astrophysics Data System (ADS)
Guo, Fang; Li, Xingli; Kuang, Hua; Bai, Yang; Zhou, Huaguo
2016-11-01
The original cost potential field cellular automata describing normal pedestrian evacuation is extended to study more general evacuation scenarios. Based on the cost potential field function, through considering the psychological characteristics of crowd under emergencies, the quantitative formula of behavior variation is introduced to reflect behavioral changes caused by psychology tension. The numerical simulations are performed to investigate the effects of the magnitude of behavior variation, the different pedestrian proportions with different behavior variation and other factors on the evacuation efficiency and process in a room. The spatiotemporal dynamic characteristic during the evacuation process is also discussed. The results show that compared with the normal evacuation, the behavior variation under an emergency does not necessarily lead to the decrease of the evacuation efficiency. At low density, the increase of the behavior variation can improve the evacuation efficiency, while at high density, the evacuation efficiency drops significantly with the increasing amplitude of the behavior variation. In addition, the larger proportion of pedestrian affected by the behavior variation will prolong the evacuation time.
NASA Astrophysics Data System (ADS)
Alonso, J.; Fernández, A.; Fort, H.
2006-06-01
We propose an extension of the evolutionary Prisoner's Dilemma cellular automata, introduced by Nowak and May (1992 Nature 359 826), in which the pressure of the environment is taken into account. This is implemented by requiring that individuals need to collect a minimum score Umin, representing indispensable resources (nutrients, energy, money, etc) to prosper in this environment. So the agents, instead of evolving just by adopting the behaviour of the most successful neighbour (who got Umsn), also take into account if Umsn is above or below the threshold Umin. If Umsn
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.
NASA Astrophysics Data System (ADS)
Tambunan, L.; Salamah, H.; Asriana, N.
2017-03-01
This study aims to determine the influence of architectural design on the risk of fire spread in densely urban settlement area. Cellular Automata (CA) is used to analyse the fire spread pattern, speed, and the extent of damage. Four cells represent buildings, streets, and fields characteristic in the simulated area, as well as their flammability level and fire spread capabilities. Two fire scenarios are used to model the spread of fire: (1) fire origin in a building with concrete and wood material majority, and (2) fire origin in building with wood material majority. Building shape, building distance, road width, and total area of wall openings are considered constant, while wind is ignored. The result shows that fire spread faster in the building area with wood majority than with concrete majority. Significant amount of combustible building material, absence of distance between buildings, narrow streets and limited fields are factors which influence fire spread speed and pattern as well as extent of damage when fire occurs in the densely urban settlement area.
Molecular quantum-dot cellular automata--from molecular structure to circuit dynamics
NASA Astrophysics Data System (ADS)
Lu, Yuhui; Lent, Craig
2008-03-01
Quantum-dot cellular automata (QCA) [1] provides a transistor-less paradigm for molecular electronics. In the QCA approach, binary information is stored in the charge configuration of single cells, and transferred via Coulomb coupling between neighboring cells. Single-molecule QCA cells can be realized by using as quantum dots the localized states of mixed-valence complexes. Several candidate QCA molecules have been synthesized and shown to have the required field-induced switching properties [2]. We report progress towards a hierarchic dynamic theory of QCA circuits. We use ab initio techniques to calculate the relevant molecular electronic structure, and extract parameters for a simpler Hamiltonian to describe switching behavior. We then apply a coherence vector formalism to model interaction with the thermal environment and generate a circuit-dynamic description. [1] C. S. Lent, P. D. Tougaw, W. Porod, and G. H. Bernstein, Nanotechnology, vol. 4, pp. 49, 1993. [2] H. Qi, S. Sharma, Z. Li, G. L. Snider, A. O. Orlov, C. S. Lent, and T. P. Fehlner, J.Am.Chem.Soc., vol. 125, pp. 15250, 2003.
NASA Astrophysics Data System (ADS)
Xu, Xiaoming; Du, Ziqiang; Zhang, Hong
2016-10-01
Land use and land cover change (LULCC) is a widely researched topic in related studies. A number of models have been established to simulate LULCC patterns. However, the integration of the system dynamic (SD) and the cellular automata (CA) model have been rarely employed in LULCC simulations, although it allows for combining the advantages of each approach and therefore improving the simulation accuracy. In this study, we integrated an SD model and a CA model to predict LULCC under three future development scenarios in Northern Shanxi province of China, a typical agro-pastoral transitional zone. The results indicated that our integrated approach represented the impacts of natural and socioeconomic factors on LULCC well, and could accurately simulate the magnitude and spatial pattern of LULCC. The modeling scenarios illustrated that different development pathways would lead to various LULCC patterns. This study demonstrated the advantages of the integration approach for simulating LULCC and suggests that LULCC is affected to a large degree by natural and socioeconomic factors.
Studying the role of lipid rafts on protein receptor bindings with cellular automata.
Haack, Fiete; Burrage, Kevin; Redmer, Ronald; Uhrmacher, Adelinde M
2013-01-01
It is widely accepted that lipid rafts promote receptor clustering and thereby facilitate signaling transduction. The role of lipid rafts in inducing and promoting receptor accumulation within the cell membrane has been explored by several computational and experimental studies. However, it remains unclear whether lipid rafts influence the recruitment and binding of proteins from the cytosol as well. To provide an answer to this question a spatial membrane model has been developed based on cellular automata. Our results indicate that lipid rafts indeed influence protein receptor bindings. In particular processes with slow dissociation and binding kinetics are promoted by lipid rafts, whereas fast binding processes are slightly hampered. However, the impact depends on a variety of parameters, such as the size and mobility of the lipid rafts, the induced slow down of receptors within rafts, and also the dissociation and binding kinetics of the cytosolic proteins. Thus, for any individual signaling pathway the influence of lipid rafts on protein binding might be different. To facilitate analyzing this influence given a specific pathway, our approach has been generalized into LiRaM, a modeling and simulation tool for lipid rafts models.
NASA Astrophysics Data System (ADS)
Liucci, Luisa; Melelli, Laura; Suteanu, Cristian; Ponziani, Francesco
2017-08-01
Power law scaling has been widely observed in the frequency distribution of landslide sizes. The exponent of the power-law characterizes the probability of landslide magnitudes and it thus represents an important parameter for hazard assessment. The reason for the universal scaling behavior of landslides is still debated and the role of topography has been explored in terms of possible explanation for this type of behavior. We built a simple cellular automata model to investigate this issue, as well as the relationships between the scaling properties of landslide areas and the changes suffered by the topographic surface affected by landslides. The dynamics of the model is controlled by a temporal rate of weakening, which drives the system to instability, and by topography, which defines both the quantity of the displaced mass and the direction of the movement. Results show that the model is capable of reproducing the scaling behavior of real landslide areas and suggest that topography is a good candidate to explain their scale-invariance. In the model, the values of the scaling exponents depend on how fast the system is driven to instability; they are less sensitive to the duration of the driving rate, thus suggesting that the probability of landslide areas could depend on the intensity of the triggering mechanism rather than on its duration, and on the topographic setting of the area. Topography preserves the information concerning the statistical distribution of areas of landslides caused by a driving mechanism of given intensity and duration.
Cellular automata model for urban road traffic flow considering pedestrian crossing street
NASA Astrophysics Data System (ADS)
Zhao, Han-Tao; Yang, Shuo; Chen, Xiao-Xu
2016-11-01
In order to analyze the effect of pedestrians' crossing street on vehicle flows, we investigated traffic characteristics of vehicles and pedestrians. Based on that, rules of lane changing, acceleration, deceleration, randomization and update are modified. Then we established two urban two-lane cellular automata models of traffic flow, one of which is about sections with non-signalized crosswalk and the other is on uncontrolled sections with pedestrians crossing street at random. MATLAB is used for numerical simulation of the different traffic conditions; meanwhile space-time diagram and relational graphs of traffic flow parameters are generated and then comparatively analyzed. Simulation results indicate that when vehicle density is lower than around 25 vehs/(km lane), pedestrians have modest impact on traffic flow, whereas when vehicle density is higher than about 60 vehs/(km lane), traffic speed and volume will decrease significantly especially on sections with non-signal-controlled crosswalk. The results illustrate that the proposed models reconstruct the traffic flow's characteristic with the situation where there are pedestrians crossing and can provide some practical reference for urban traffic management.
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.
Self-doping of molecular quantum-dot cellular automata: mixed valence zwitterions.
Lu, Yuhui; Lent, Craig
2011-09-07
Molecular quantum-dot cellular automata (QCA) is a promising paradigm for realizing molecular electronics. In molecular QCA, binary information is encoded in the distribution of intramolecular charge, and Coulomb interactions between neighboring molecules combine to create long-range correlations in charge distribution that can be exploited for signal transfer and computation. Appropriate mixed-valence species are promising candidates for single-molecule device operation. A complication arises because many mixed-valence compounds are ions and the associated counterions can potentially disrupt the correct flow of information through the circuit. We suggest a self-doping mechanism which incorporates the counterion covalently into the structure of a neutral molecular cell, thus producing a zwitterionic mixed-valence complex. The counterion is located at the geometrical center of the QCA molecule and bound to the working dots via covalent bonds, thus avoiding counterion effects that bias the system toward one binary information state or the other. We investigate the feasibility of using multiply charged anion (MCA) boron clusters, specifically closo-borate dianion, as building blocks. A first principle calculation shows that neutral, bistable, and switchable QCA molecules are possible. The self-doping mechanism is confirmed by molecular orbital analysis, which shows that MCA counterions can be stabilized by the electrostatic interaction between negatively charged counterions and positively charged working dots. This journal is © the Owner Societies 2011
NASA Astrophysics Data System (ADS)
Zhao, Yaolong; Zhao, Junsan; Murayama, Yuji
2008-10-01
The period of high economic growth in Japan which began in the latter half of the 1950s led to a massive migration of population from rural regions to the Tokyo metropolitan area. This phenomenon brought about rapid urban growth and urban structure changes in this area. Purpose of this study is to establish a constrained CA (Cellular Automata) model with GIS (Geographical Information Systems) to simulate urban growth pattern in the Tokyo metropolitan area towards predicting urban form and landscape for the near future. Urban land-use is classified into multi-categories for interpreting the effect of interaction among land-use categories in the spatial process of urban growth. Driving factors of urban growth pattern, such as land condition, railway network, land-use zoning, random perturbation, and neighborhood interaction and so forth, are explored and integrated into this model. These driving factors are calibrated based on exploratory spatial data analysis (ESDA), spatial statistics, logistic regression, and "trial and error" approach. The simulation is assessed at both macro and micro classification levels in three ways: visual approach; fractal dimension; and spatial metrics. Results indicate that this model provides an effective prototype to simulate and predict urban growth pattern of the Tokyo metropolitan area.
Modelling land use/cover changes with markov-cellular automata in Komering Watershed, South Sumatera
NASA Astrophysics Data System (ADS)
Kusratmoko, E.; Albertus, S. D. Y.; Supriatna
2017-01-01
This research has a purpose to study and develop a model that can representing and simulating spatial distribution pattern of land use change in Komering watershed. The Komering watershed is one of nine sub Musi river basin and is located in the southern part of Sumatra island that has an area of 8060,62 km2. Land use change simulations, achieved through Markov-cellular automata (CA) methodologies. Slope, elevation, distance from road, distance from river, distance from capital sub-district, distance from settlement area area were driving factors that used in this research. Land use prediction result in 2030 also shows decrease of forest acreage up to -3.37%, agricultural land decreased up to -2.13%, and open land decreased up to -0.13%. On the other hand settlement area increased up to 0.07%, and plantation land increased up to 5.56%. Based on the predictive result, land use unconformity percentage to RTRW in Komering watershed is 18.62 % and land use conformity is 58.27%. Based on the results of the scenario, where forest in protected areas and agriculture land are maintained, shows increase the land use conformity amounted to 60.41 % and reduce unconformity that occur in Komering watershed to 17.23 %.
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.
Predicting nonlinear cellular automata quickly by decomposing them into linear ones
NASA Astrophysics Data System (ADS)
Moore, Cristopher
1998-01-01
We show that a wide variety of nonlinear cellular automata (CAs) can be decomposed into a quasidirect product of linear ones. These CAs can be predicted by parallel circuits of depth O(log 2t) using gates with binary inputs, or O(log t) depth if “sum mod p” gates with an unbounded number of inputs are allowed. Thus these CAs can be predicted by (idealized) parallel computers much faster than by explicit simulation, even though they are nonlinear. This class includes any CA whose rule, when written as an algebra, is a solvable group. We also show that CAs based on nilpotent groups can be predicted in depth O(log t) or O(1) by circuits with binary or “sum mod p” gates, respectively. We use these techniques to give an efficient algorithm for a CA rule which, like elementary CA rule 18, has diffusing defects that annihilate in pairs. This can be used to predict the motion of defects in rule 18 in O(log 2t) parallel time.
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.
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.
A probabilistic seismic hazard model based on cellular automata and information theory
NASA Astrophysics Data System (ADS)
Jiménez, A.; Posadas, A. M.; Marfil, J. M.
2005-03-01
We try to obtain a spatio-temporal model of earthquakes occurrence based on Information Theory and Cellular Automata (CA). The CA supply useful models for many investigations in natural sciences; here, it have been used to establish temporal relations between the seismic events occurring in neighbouring parts of the crust. The catalogue used is divided into time intervals and the region into cells, which are declared active or inactive by means of a certain energy release criterion (four criteria have been tested). A pattern of active and inactive cells which evolves over time is given. A stochastic CA is constructed with the patterns to simulate their spatio-temporal evolution. The interaction between the cells is represented by the neighbourhood (2-D and 3-D models have been tried). The best model is chosen by maximizing the mutual information between the past and the future states. Finally, a Probabilistic Seismic Hazard Map is drawn up for the different energy releases. The method has been applied to the Iberian Peninsula catalogue from 1970 to 2001. For 2-D, the best neighbourhood has been the Moore's one of radius 1; the von Neumann's 3-D also gives hazard maps and takes into account the depth of the events. Gutenberg-Richter's law and Hurst's analysis have been obtained for the data as a test of the catalogue. Our results are consistent with previous studies both of seismic hazard and stress conditions in the zone, and with the seismicity occurred after 2001.
A novel cellular automata based technique for visual multimedia content encryption
NASA Astrophysics Data System (ADS)
Chatzichristofis, Savvas A.; Mitzias, Dimitris A.; Sirakoulis, Georgios Ch.; Boutalis, Yiannis S.
2010-11-01
This paper proposes a new method for visual multimedia content encryption using Cellular Automata (CA). The encryption scheme is based on the application of an attribute of the CLF XOR filter, according to which the original content of a cellular neighborhood can be reconstructed following a predetermined number of repeated applications of the filter. The encryption is achieved using a key image of the same dimensions as the image being encrypted. This technique is accompanied by the one-time pad (OTP) encryption method, rendering the proposed method reasonably powerful, given the very large number of resultant potential security keys. The method presented here makes encryption possible in cases where there is more than one image with the use of just one key image. A further significant characteristic of the proposed method is that it demonstrates how techniques from the field of image retrieval can be used in the field of image encryption. The proposed method is further strengthened by the fact that the resulting encrypted image for a given key image is different each time. The encryption result depends on the structure of an artificial image produced by the superposition of four 1-D CA time-space diagrams as well as from a CA random number generator. A semi-blind source separation algorithm is used to decrypt the encrypted image. The result of the decryption is a lossless representation of the encrypted image. Simulation results demonstrate the effectiveness of the proposed encryption method. The proposed method is implemented in C# and is available online through the img(Rummager) application.
Alemani, Davide; Pappalardo, Francesco; Pennisi, Marzio; Motta, Santo; Brusic, Vladimir
2012-02-28
In the last decades the Lattice Boltzmann method (LB) has been successfully used to simulate a variety of processes. The LB model describes the microscopic processes occurring at the cellular level and the macroscopic processes occurring at the continuum level with a unique function, the probability distribution function. Recently, it has been tried to couple deterministic approaches with probabilistic cellular automata (probabilistic CA) methods with the aim to model temporal evolution of tumor growths and three dimensional spatial evolution, obtaining hybrid methodologies. Despite the good results attained by CA-PDE methods, there is one important issue which has not been completely solved: the intrinsic stochastic nature of the interactions at the interface between cellular (microscopic) and continuum (macroscopic) level. CA methods are able to cope with the stochastic phenomena because of their probabilistic nature, while PDE methods are fully deterministic. Even if the coupling is mathematically correct, there could be important statistical effects that could be missed by the PDE approach. For such a reason, to be able to develop and manage a model that takes into account all these three level of complexity (cellular, molecular and continuum), we believe that PDE should be replaced with a statistic and stochastic model based on the numerical discretization of the Boltzmann equation: The Lattice Boltzmann (LB) method. In this work we introduce a new hybrid method to simulate tumor growth and immune system, by applying Cellular Automata Lattice Boltzmann (CA-LB) approach.
An enhanced high-speed multi-digit BCD adder using quantum-dot cellular automata
NASA Astrophysics Data System (ADS)
Ajitha, D.; Ramanaiah, K. V.; Sumalatha, V.
2017-02-01
The advent of development of high-performance, low-power digital circuits is achieved by a suitable emerging nanodevice called quantum-dot cellular automata (QCA). Even though many efficient arithmetic circuits were designed using QCA, there is still a challenge to implement high-speed circuits in an optimized manner. Among these circuits, one of the essential structures is a parallel multi-digit decimal adder unit with significant speed which is very attractive for future environments. To achieve high speed, a new correction logic formulation method is proposed for single and multi-digit BCD adder. The proposed enhanced single-digit BCD adder (ESDBA) is 26% faster than the carry flow adder (CFA)-based BCD adder. The multi-digit operations are also performed using the proposed ESDBA, which is cascaded innovatively. The enhanced multi-digit BCD adder (EMDBA) performs two 4-digit and two 8-digit BCD addition 50% faster than the CFA-based BCD adder with the nominal overhead of the area. The EMDBA performs two 4-digit BCD addition 24% faster with 23% decrease in the area, similarly for 8-digit operation the EMDBA achieves 36% increase in speed with 21% less area compared to the existing carry look ahead (CLA)-based BCD adder design. The proposed multi-digit adder produces significantly less delay of (N –1) + 3.5 clock cycles compared to the N* One digit BCD adder delay required by the conventional BCD adder method. It is observed that as per our knowledge this is the first innovative proposal for multi-digit BCD addition using QCA.
Mixed-spin [2 × 2] Fe4 grid complex optimized for quantum cellular automata.
Schneider, Benjamin; Demeshko, Serhiy; Neudeck, Sven; Dechert, Sebastian; Meyer, Franc
2013-11-18
The new pyrazolate-bridged proligand 4-methyl-3,5-bis{6-(2,2'-bipyridyl)}pyrazole ((Me)LH) has been synthesized. Similar to its congener that lacks the backbone methyl substituent ((H)LH) it forms a robust Fe(II)4 grid complex, [(Me)L4Fe(II)4](BF4)4. The molecular structure of [(Me)L4Fe(II)4](BF4)4·2MeCN has been elucidated by X-ray diffraction, revealing two high-spin (HS) and two low-spin (LS) ferrous ions at opposite corners of the rhombic metal ion arrangement. SQUID and (57)Fe Mössbauer data for solid material showed that this [HS-LS-HS-LS] configuration persists over a wide temperature range, between 7 and 250 K, while spin-crossover sets in only above 250 K. According to Mössbauer spectroscopy a [1HS-3LS] configuration is present in solution at 80 K. Thus, the methyl substituent in [(Me)L](-) leads to a stronger ligand field compared to parent [(H)L](-) and hence to a higher LS fraction both in the solid state and in solution. Cyclic voltammetry of [(Me)L4Fe(II)4](BF4)4 reveals four sequential oxidations coming in two pairs with pronounced stability of the di-mixed-valence species [(Me)L4Fe(II)2Fe(III)2](6+) (K(C) = 3.35 × 10(8)). The particular [HS-LS-HS-LS] configuration as well as the di-mixed-valence configuration, both with identical spin or redox states at diagonally opposed vertices of the grid, make this system attractive as a molecular component for quantum cellular automata.
Structure and Reversibility of 2D von Neumann Cellular Automata Over Triangular Lattice
NASA Astrophysics Data System (ADS)
Uguz, Selman; Redjepov, Shovkat; Acar, Ecem; Akin, Hasan
2017-06-01
Even though the fundamental main structure of cellular automata (CA) is a discrete special model, the global behaviors at many iterative times and on big scales could be a close, nearly a continuous, model system. CA theory is a very rich and useful phenomena of dynamical model that focuses on the local information being relayed to the neighboring cells to produce CA global behaviors. The mathematical points of the basic model imply the computable values of the mathematical structure of CA. After modeling the CA structure, an important problem is to be able to move forwards and backwards on CA to understand their behaviors in more elegant ways. A possible case is when CA is to be a reversible one. In this paper, we investigate the structure and the reversibility of two-dimensional (2D) finite, linear, triangular von Neumann CA with null boundary case. It is considered on ternary field ℤ3 (i.e. 3-state). We obtain their transition rule matrices for each special case. For given special triangular information (transition) rule matrices, we prove which triangular linear 2D von Neumann CAs are reversible or not. It is known that the reversibility cases of 2D CA are generally a much challenged problem. In the present study, the reversibility problem of 2D triangular, linear von Neumann CA with null boundary is resolved completely over ternary field. As far as we know, there is no structure and reversibility study of von Neumann 2D linear CA on triangular lattice in the literature. Due to the main CA structures being sufficiently simple to investigate in mathematical ways, and also very complex to obtain in chaotic systems, it is believed that the present construction can be applied to many areas related to these CA using any other transition rules.
Simulation of Corrosion Process for Structure with the Cellular Automata Method
NASA Astrophysics Data System (ADS)
Chen, M. C.; Wen, Q. Q.
2017-06-01
In this paper, from the mesoscopic point of view, under the assumption of metal corrosion damage evolution being a diffusive process, the cellular automata (CA) method was proposed to simulate numerically the uniform corrosion damage evolution of outer steel tube of concrete filled steel tubular columns subjected to corrosive environment, and the effects of corrosive agent concentration, dissolution probability and elapsed etching time on the corrosion damage evolution were also investigated. It was shown that corrosion damage increases nonlinearly with increasing elapsed etching time, and the longer the etching time, the more serious the corrosion damage; different concentration of corrosive agents had different impacts on the corrosion damage degree of the outer steel tube, but the difference between the impacts was very small; the heavier the concentration, the more serious the influence. The greater the dissolution probability, the more serious the corrosion damage of the outer steel tube, but with the increase of dissolution probability, the difference between its impacts on the corrosion damage became smaller and smaller. To validate present method, corrosion damage measurements for concrete filled square steel tubular columns (CFSSTCs) sealed at both their ends and immersed fully in a simulating acid rain solution were conducted, and Faraday’s law was used to predict their theoretical values. Meanwhile, the proposed CA mode was applied for the simulation of corrosion damage evolution of the CFSSTCs. It was shown by the comparisons of results from the three methods aforementioned that they were in good agreement, implying that the proposed method used for the simulation of corrosion damage evolution of concrete filled steel tubular columns is feasible and effective. It will open a new approach to study and evaluate further the corrosion damage, loading capacity and lifetime prediction of concrete filled steel tubular structures.
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
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.
Causal architecture, complexity and self-organization in time series and cellular automata
NASA Astrophysics Data System (ADS)
Shalizi, Cosma Rohilla
2001-10-01
All self-respecting nonlinear scientists know self- organization when they see it: except when we disagree. For this reason, if no other, it is important to put some mathematical spine into our floppy intuitive notion of self-organization. Only a few measures of self- organization have been proposed; none can be adopted in good intellectual conscience. To find a decent formalization of self-organization, we need to pin down what we mean by organization. The best answer is that the organization of a process is its causal architecture-its internal, possibly hidden, causal states and their interconnections. Computational mechanics is a method for inferring causal architecture-represented by a mathematical object called the ɛ-machine-from observed behavior. The ɛ-machine captures all patterns in the process which have any predictive power, so computational mechanics is also a method for pattern discovery. In this work, I develop computational mechanics for four increasingly sophisticated types of process-memoryless transducers, time series, transducers with memory, and cellular automata. In each case I prove the optimality and uniqueness of the ɛ-machine's representation of the causal architecture, and give reliable algorithms for pattern discovery. The ɛ-machine is the organization of the process, or at least of the part of it which is relevant to our measurements. It leads to a natural measure of the statistical complexity of processes, namely the amount of information needed to specify the state of the E-machine. Self-organization is a self- generated increase in statistical complexity. This fulfills various hunches which have been advanced in the literature, seems to accord with people's intuitions, and is both mathematically precise and operational.
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)
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.
Heckerling, P S; Gerber, B S; Weiner, S J
2006-01-01
Medical residents engage in formal and informal education interactions with fellow residents during the working day, and can choose whether to spend time and effort on such interactions. Time and effort spent on such interactions can bring learning and personal satisfaction to residents, but may also delay completion of clinical work. Using hypothetical cases, we assessed the values and strategies of internal medicine residents at one hospital for both cooperative and non-cooperative education interactions with fellow residents. We then used these data and cellular automata models of two-person games to simulate repeated interactions between residents, and to determine which strategies resulted in greatest accrued value. We conducted sensitivity analyses on several model parameters, to test the robustness of dominant strategies to model assumptions. Twenty-nine of the 57 residents (50.9%) valued cooperation more than non-cooperation no matter what the other resident did during the current interaction. Similarly, thirty-six residents (63.2%) endorsed an unconditional always-cooperate strategy no matter what the other resident had done during their previous interaction. In simulations, an always-cooperate strategy accrued more value (776.42 value units) than an aggregate of strategies containing non-cooperation components (675.0 value units, p = 0.052). Only when the probability of strategy errors reached 50%, or when values were re-ordered to match those of a Prisoner's Dilemma, did non-cooperation-based strategies accrue the most value. Cooperation-based values and strategies were most frequent among our residents, and dominated in simulations of repeated education interactions between them.
NASA Astrophysics Data System (ADS)
Mujiono, Indra, T. L.; Harmantyo, D.; Rukmana, I. P.; Nadia, Z.
2017-07-01
The purpose of this study was to simulate land use change in 1996-2016 and its prediction in 2035 as well as its potential to deforestation. Both of these purposes were obtained through modeling analysis using Markov Chain Cellular Automata. This modeling method was considered important for understanding the causes and impacts. Based on the analysis, the land use change between 1996 to 2007 has caused forest loss (the region and non-region) covering an area of 62,012 ha. While in the period of 2007 to 2016, the change has lead to the east side of the slope grade of 0-15 percent and an altitude between 500-1000 meters above sea level. In this period, plantation area has increased by 50,822 ha, while the forest area has reduced from 80,038 ha. In a period of 20 years, North Bengkulu Regency has lost the forest area of 80,038 ha. The amount of intervention against forest suggested the potential for deforestation in this area. Simulation of land use change in 2035 did not indicate significant deforestation due to the limited land on physical factors such as slope and elevation. However, it should be noted that, in 2035, the area of conservation forest was reduced by 16,793 ha (29 %), while the areas of protected and production forest were reduced by 4,933 ha (19 %) and 2,114 ha (3 %), respectively. Land use change is a serious threat of deforestation, especially in forest areas in North Bengkulu Regency, where any decline in forest area means the addition of plantation area.
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
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
NASA Astrophysics Data System (ADS)
Li, Xin-Gang; Jia, Bin; Gao, Zi-You; Jiang, Rui
2006-07-01
In real traffic, a vehicle may perform different lane-changing behavior if its preceding vehicle is different. Fast vehicle usually has aggressive lane-changing behavior when its preceding vehicle is a slow one. In this paper, we take the factor into account and propose a new symmetric two-lane cellular automata model. It is shown that aggressive lane-changing behavior of fast vehicle can depress the plug formed by slow vehicles and improve traffic flow in mixed traffic in the intermediate density range. The simulation results also indicate that ping-pang lane-changing behavior is mainly caused by fast vehicles that are hindered by fast vehicles.
NASA Astrophysics Data System (ADS)
Imre, Alexandra
Nanomagnets that exhibit only two stable states of magnetization can represent digital bits. Magnetic random access memories store binary information in such nanomagnets, and currently, fabrication of dense arrays of nanomagnets is also under development for application in hard disk drives. The latter faces the challenge of avoiding magnetic dipole interactions between the individual elements in the arrays, which limits data storage density. On the contrary, these interactions are utilized in the magnetic quantum-dot cellular automata (MQCA) system, which is a network of closely-spaced, dipole-coupled, single-domain nanomagnets designed for digital computation. MQCA offers very low power dissipation together with high integration density of functional devices, as QCA implementations do in general. In addition, MQCA can operate over a wide temperature range from sub-Kelvin to the Curie temperature. Information propagation and inversion have previously been demonstrated in MQCA. In this dissertation, room temperature operation of the basic MQCA logic gate, i.e. the three-input majority gate, is demonstrated for the first time. The samples were fabricated on silicon wafers by using electron-beam lithography for patterning thermally evaporated ferromagnetic metals. The networks of nanomagnets were imaged by magnetic force microscopy (MFM), with which individual magnetization states were distinguished and mapped. Magnetic dipole-ordering in the networks was investigated in different samples. Average ordering lengths were calculated by statistical analysis of the MFM images taken after several independent demagnetization processes. The average ordering length was found to be dependent on the shape and size of the nanomagnets and limited by defects introduced during fabrication. Defect tolerant shape-design was investigated in samples of many different ring-shaped and elongated nanomagnets. The shape-effects were explained by means of micromagnetic simulations. The
Social interactions of eating behaviour among high school students: a cellular automata approach.
Dabbaghian, Vahid; Mago, Vijay K; Wu, Tiankuang; Fritz, Charles; Alimadad, Azadeh
2012-10-09
Overweight and obesity in children and adolescents is a global epidemic posing problems for both developed and developing nations. The prevalence is particularly alarming in developed nations, such as the United States, where approximately one in three school-aged adolescents (ages 12-19) are overweight or obese. Evidence suggests that weight gain in school-aged adolescents is related to energy imbalance exacerbated by the negative aspects of the school food environment, such as presence of unhealthy food choices. While a well-established connection exists between the food environment, presently there is a lack of studies investigating the impact of the social environment and associated interactions of school-age adolescents. This paper uses a mathematical modelling approach to explore how social interactions among high school adolescents can affect their eating behaviour and food choice. In this paper we use a Cellular Automata (CA) modelling approach to explore how social interactions among school-age adolescents can affect eating behaviour, and food choice. Our CA model integrates social influences and transition rules to simulate the way individuals would interact in a social community (e.g., school cafeteria). To replicate these social interactions, we chose the Moore neighbourhood which allows all neighbours (eights cells in a two-dimensional square lattice) to influence the central cell. Our assumption is that individuals belong to any of four states; Bring Healthy, Bring Unhealthy, Purchase Healthy, and Purchase Unhealthy, and will influence each other according to parameter settings and transition rules. Simulations were run to explore how the different states interact under varying parameter settings. This study, through simulations, illustrates that students will change their eating behaviour from unhealthy to healthy as a result of positive social and environmental influences. In general, there is one common characteristic of changes across time
Social interactions of eating behaviour among high school students: a cellular automata approach
2012-01-01
Background Overweight and obesity in children and adolescents is a global epidemic posing problems for both developed and developing nations. The prevalence is particularly alarming in developed nations, such as the United States, where approximately one in three school-aged adolescents (ages 12-19) are overweight or obese. Evidence suggests that weight gain in school-aged adolescents is related to energy imbalance exacerbated by the negative aspects of the school food environment, such as presence of unhealthy food choices. While a well-established connection exists between the food environment, presently there is a lack of studies investigating the impact of the social environment and associated interactions of school-age adolescents. This paper uses a mathematical modelling approach to explore how social interactions among high school adolescents can affect their eating behaviour and food choice. Methods In this paper we use a Cellular Automata (CA) modelling approach to explore how social interactions among school-age adolescents can affect eating behaviour, and food choice. Our CA model integrates social influences and transition rules to simulate the way individuals would interact in a social community (e.g., school cafeteria). To replicate these social interactions, we chose the Moore neighbourhood which allows all neighbours (eights cells in a two-dimensional square lattice) to influence the central cell. Our assumption is that individuals belong to any of four states; Bring Healthy, Bring Unhealthy, Purchase Healthy, and Purchase Unhealthy, and will influence each other according to parameter settings and transition rules. Simulations were run to explore how the different states interact under varying parameter settings. Results This study, through simulations, illustrates that students will change their eating behaviour from unhealthy to healthy as a result of positive social and environmental influences. In general, there is one common characteristic of
Wu, Yina; Abdel-Aty, Mohamed; Ding, Yaoxian; Jia, Bin; Shi, Qi; Yan, Xuedong
2017-09-11
The Type II dilemma zone describes the road segment to a signalized intersection where drivers have difficulties to decide either stop or go at the onset of yellow signal. Such phenomenon can result in an increased crash risk at signalized intersections. Different types of warning systems have been proposed to help drivers make decisions. Although the warning systems help to improve drivers' behavior, they also have several disadvantages such as increasing rear-end crashes or red-light running (RLR) violations. In this study, a new warning system called pavement marking with auxiliary countermeasure (PMAIC) is proposed to reduce the dilemma zone and enhance the traffic safety at signalized intersections. The proposed warning system integrates the pavement marking and flashing yellow system which can provide drivers with better suggestions about stop/go decisions based on their arriving time and speed. In order to evaluate the performance of the proposed warning system, this paper presents a cellular automata (CA) simulation study. The CA simulations are conducted for four different scenarios in total, including the typical intersection without warning system, the intersection with flashing green countermeasure, the intersection with pavement marking, and the intersection with the PMAIC warning system. Before the specific CA simulation analysis, a logistic regression model is calibrated based on field video data to predict drivers' general stop/go decisions. Also, the rules of vehicle movements in the CA models under the influence by different warning systems are proposed. The proxy indicators of rear-end crash and potential RLR violations were estimated and used to evaluate safety levels for the different scenarios. The simulation results showed that the PMAIC countermeasure consistently offered best performance to reduce rear-end crash and RLR violation. Meanwhile, the results indicate that the flashing-green countermeasure could not effectively reduce either rear
NASA Astrophysics Data System (ADS)
Casey, Alex; Iannacchione, Germano; Georgiev, Georgi; Cebe, Peggy
2014-03-01
A computational algorithm has been developed to simulate the transport properties of oriented and un-oriented thin film nanocomposites of isotactic Polypropylene (iPP) and carbon nanotubes (CNT) with increasing CNT concentration. Our goal is to be able to design materials with optimal properties using simulations. We use cellular automata approach in Matlab simulation environment. The percolation threshold is reproduced in the simulations, matching experimental data. Upon percolation, the thermal transport in the films increases sharply, more so for the electrical than for the thermal conductivity, due to the larger difference in the electric conductivities of the CNTs and the polymer. To verify the simulation, the thin-film samples were sheared in the melt at 200 C at 1 Hz in a Linkan microscope shearing hot stage. The thermal and electrical conductivity measurements were performed on the same cell arrangement with the transport perpendicular to the thin-film plane using a DC method. The thermal and electrical conductivity are higher for the un-sheared as compared to the sheared samples with stronger temperature dependence for the latter as compared to the former. Our cellular automata simulations provide information about the microstructure-macroscopic property relation in the thin film nanocomposites and can be extended to simulations of other important materials.
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.
Lattice gas methods for computational aeroacoustics
NASA Technical Reports Server (NTRS)
Sparrow, Victor W.
1995-01-01
This paper presents the lattice gas solution to the category 1 problems of the ICASE/LaRC Workshop on Benchmark Problems in Computational Aeroacoustics. The first and second problems were solved for Delta t = Delta x = 1, and additionally the second problem was solved for Delta t = 1/4 and Delta x = 1/2. The results are striking: even for these large time and space grids the lattice gas numerical solutions are almost indistinguishable from the analytical solutions. A simple bug in the Mathematica code was found in the solutions submitted for comparison, and the comparison plots shown at the end of this volume show the bug. An Appendix to the present paper shows an example lattice gas solution with and without the bug.
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
Molina, Mario Martínez; Moreno-Armendáriz, Marco A; Carlos Seck Tuoh Mora, Juan
2013-11-07
A two-dimensional lattice model based on Cellular Automata theory and swarm intelligence is used to study the spatial and population dynamics of a theoretical ecosystem. It is found that the social interactions among predators provoke the formation of clusters, and that by increasing the mobility of predators the model enters into an oscillatory behavior.
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
A novel multiplexer-based structure for random access memory cell in quantum-dot cellular automata
NASA Astrophysics Data System (ADS)
Naji Asfestani, Mazaher; Rasouli Heikalabad, Saeed
2017-09-01
Quantum-dot cellular automata (QCA) is a new technology in scale of nano and perfect replacement for CMOS circuits in the future. Memory is one of the basic components in any digital system, so designing the random access memory (RAM) with high speed and optimal in QCA is important. In this paper, by employing the structure of multiplexer, a novel RAM cell architecture is proposed. The proposed architecture is implemented without the coplanar crossover approach. The proposed architecture is simulated using the QCADesigner version 2.0.3 and QCAPro. The simulation results demonstrate that the proposed QCA RAM architecture has the best performance in terms of delay, circuit complexity, area, cell count and energy consumption in comparison with other QCA RAM architectures.
Bahar, Ali Newaz; Waheed, Sajjad
2016-01-01
The fundamental logical element of a quantum-dot cellular automata (QCA) circuit is majority voter gate (MV). The efficiency of a QCA circuit is depends on the efficiency of the MV. This paper presents an efficient single layer five-input majority voter gate (MV5). The structure of proposed MV5 is very simple and easy to implement in any logical circuit. This proposed MV5 reduce number of cells and use conventional QCA cells. However, using MV5 a multilayer 1-bit full-adder (FA) is designed. The functional accuracy of the proposed MV5 and FA are confirmed by QCADesigner a well-known QCA layout design and verification tools. Furthermore, the power dissipation of proposed circuits are estimated, which shows that those circuits dissipate extremely small amount of energy and suitable for reversible computing. The simulation outcomes demonstrate the superiority of the proposed circuit.
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.
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.
NASA Astrophysics Data System (ADS)
He, Dong; Zhu, Jing Chuan; Wang, Yang; Liu, Yong
The dynamic recrystallization (DRX) of TA15 (Ti-6Al-2Zr-1Mo-1V) titanium alloy during the hot deformation process was studied by the Cellular Automata (CA) model which is base on the dislocation density theory. To build the CA model, the dislocation density model, dynamic recovery model, nucleation model and grain growth model were introduced and developed. The influences of strain rate on the microstructure evolution and flow stress character were investigated which shows that high strain rate leads to later DRX appearance, high flow stress peak value, small mean size of recrystallizing grains(R-grains) and low DRX percentage, but they have the similar Avrami curve. The characteristic of DRX process in a modeling non-uniform temperature filed (NTF) has been studied. All the simulation results show good agreement with the pioneer's work and experimental results.
NASA Astrophysics Data System (ADS)
Naji Asfestani, Mazaher; Rasouli Heikalabad, Saeed
2017-05-01
Quantum-dot cellular automata (QCA) is the advent of technology and suitable replacement for semiconductor transistor technology. In this paper, a unique structure for the 2:1 multiplexer is presented in QCA. The structure of this component is simple, ultra-efficient and very useful to implement the various logical functions. The proposed structure does not follow any Boolean function. It takes advantage of the inherent characteristics of quantum technology to produce the desired output. Based on these principles, we design the new and efficient structures for the 4:1 multiplexer and 8:1 multiplexer in the QCA technology. These structures are designed with QCADesigner simulator and simulation results are examined. Investigation results indicate the amazing performance of proposed structure compared to existing structures in terms of area, complexity, power consumption and latency.
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.
Lattice gas models with long range interactions
NASA Astrophysics Data System (ADS)
Aristoff, David; Zhu, Lingjiong
2017-02-01
We study microcanonical lattice gas models with long range interactions, including power law interactions. We rigorously obtain a variational principle for the entropy. In a one dimensional example, we find a first order phase transition by proving the entropy is non-differentiable along a certain curve.
An Overview of Lattice-Gas Dynamics
1997-11-01
irreversible. There- fore, the CAM-8 dissipates heat like any conventional computer even though the Szilard entropy of the lattice gas is unchanged, but an...Reviews of Modern Physics, 49(3):435–479, 1977. [37] Leo P. Kadanoff and Jack Swift. Transport coefficients near the critical point: A master-equation
Monteagudo, Ángel; Santos, José
2015-01-01
Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC) and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation.
Multisite Interactions in Lattice-Gas Models
NASA Astrophysics Data System (ADS)
Einstein, T. L.; Sathiyanarayanan, R.
For detailed applications of lattice-gas models to surface systems, multisite interactions often play at least as significant a role as interactions between pairs of adatoms that are separated by a few lattice spacings. We recall that trio (3-adatom, non-pairwise) interactions do not inevitably create phase boundary asymmetries about half coverage. We discuss a sophisticated application to an experimental system and describe refinements in extracting lattice-gas energies from calculations of total energies of several different ordered overlayers. We describe how lateral relaxations complicate matters when there is direct interaction between the adatoms, an issue that is important when examining the angular dependence of step line tensions. We discuss the connector model as an alternative viewpoint and close with a brief account of recent work on organic molecule overlayers.
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
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."
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."
The Transition Rules of 2D Linear Cellular Automata Over Ternary Field and Self-Replicating Patterns
NASA Astrophysics Data System (ADS)
Sahin, Uḡur; Uguz, Selman; Akin, Hasan
In this paper we start with two-dimensional (2D) linear cellular automata (CA) in relation with basic mathematical structure. We investigate uniform linear 2D CA over ternary field, i.e. ℤ3. Present work is related to theoretical and imaginary investigations of 2D linear CA. Even though the basic construction of a CA is a discrete model, its macroscopic level behavior at large times and on large scales could be a close approximation to a continuous system. Considering some statistical properties, someone may also study geometrical aspects of patterns generated by cellular automaton evolution. After iteratively applying the linear rules, CA have been shown capable of producing interesting complex behaviors. Some examples of CA produce remarkably regular behavior on finite configurations. Using some simple initial configurations, the produced pattern can be self-replicating regarding some linear rules. Here we deal with the theory 2D uniform periodic, adiabatic and reflexive boundary CA (2D PB, AB and RB) over the ternary field ℤ3 and the applications of image processing for patterns generation. From the visual appearance of the patterns, it is seen that some rules display sensitive dependence on boundary conditions and their rule numbers.
Xiao, Xuan; Qiu, Wang-Ren
2010-06-01
G-Protein-Coupled Receptors (GPCRs) are the largest of cell surface receptor, accounting for >1% of the human genome. They play a key role in cellular signaling networks that regulate various physiological processes. The functions of many of GPCRs are unknown, because they are difficult to crystallize and most of them will not dissolve in normal solvents. This difficulty has motivated and challenged the development of a computational method which can predict the classification of the families and subfamilies of GPCRs based on their primary sequence so as to help us classify drugs. In this paper the adaptive K-nearest neighbor algorithm and protein cellular automata image (CAI) is introduced. Based on the CAI, the complexity measure factors derived from each of the protein sequences concerned are adopted for its Pseudo amino acid composition. GPCRs were categorized into nine subtypes. The overall success rate in identifying GPCRs among their nine family classes was about 83.5%. The high success rate suggests that the adaptive K-nearest neighbor algorithm and protein CAI holds very high potential to become a useful tool for understanding the actions of drugs that target GPCRs and designing new medications with fewer side effects and greater efficacy.
Shrestha, Sachin Man Bajimaya; Joldes, Grand Roman; Wittek, Adam; Miller, Karol
2013-04-01
We model complete growth of an avascular tumour by employing cellular automata for the growth of cells and steady-state equation to solve for nutrient concentrations. Our modelling and computer simulation results show that, in the case of a brain tumour, oxygen distribution in the tumour volume may be sufficiently described by a time-independent steady-state equation without losing the characteristics of a time-dependent diffusion equation. This makes the solution of oxygen concentration in the tumour volume computationally more efficient, thus enabling simulation of tumour growth on a large scale. We solve this steady-state equation using a central difference method. We take into account the composition of cells and intercellular adhesion in addition to processes involved in cell cycle--proliferation, quiescence, apoptosis, and necrosis--in the tumour model. More importantly, we consider cell mutation that gives rise to different phenotypes and therefore a tumour with heterogeneous population of cells. A new phenotype is probabilistically chosen and has the ability to survive at lower levels of nutrient concentration and reproduce faster. We show that heterogeneity of cells that compose a tumour leads to its irregular growth and that avascular growth is not supported for tumours of diameter above 18 mm. We compare results from our growth simulation with existing experimental data on Ehrlich ascites carcinoma and tumour spheroid cultures and show that our results are in good agreement with the experimental findings.
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.
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.
Gangadari, Bhoopal Rao; Ahamed, Shaik Rafi
2016-12-01
In this paper, we presented a novel approach of low energy consumption architecture of S-Box used in Advanced Encryption Standard (AES) algorithm using programmable second order reversible cellular automata (RCA (2)). The architecture entails a low power implementation with minimal delay overhead and the performance of proposed RCA (2) based S-Box in terms of security is evaluated using the cryptographic properties such as nonlinearity, correlation immunity bias, strict avalanche criteria, entropy and also found that the proposed architecture is secure enough for cryptographic applications. Moreover, the proposed AES algorithm architecture simulation studies show that energy consumption of 68.726 nJ, power dissipation of 3.856 mW for 0.18- μm at 13.69 MHz and energy consumption of 29.408 nJ, power dissipation of 1.65 mW for 0.13- μm at 13.69 MHz. The proposed AES algorithm with RCA (2) based S-Box shows a reduction power consumption by 50 % and energy consumption by 5 % compared to best classical S-Box and composite field arithmetic based AES algorithm. Apart from that, it is also shown that RCA (2) based S-Boxes are dynamic in nature, invertible, low power dissipation compared to that of LUT based S-Box and hence suitable for Wireless Body Area Network (WBAN) applications.
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
NASA Astrophysics Data System (ADS)
Zhao, Y.; Qin, R. S.; Chen, D. F.
2013-08-01
A three-dimensional (3D) cellular automata (CA) model has been developed for the simulation of microstructure evolution in alloy solidification. The governing rule for the CA model is associated with the phase transition driving force which is obtained via a thermodynamic database. This determines the migration rate of the non-equilibrium solid-liquid (SL) interface and is calculated according to the local temperature and chemical composition. The curvature of the interface and the anisotropic property of the surface energy are taken into consideration. A 3D finite element (FE) method is applied for the calculation of transient heat and mass transfer. Numerical calculations for the solidification of Fe-1.5 wt% C alloy have been performed. The morphological evolution of dendrites, carbon segregation and temperature distribution in both isothermal and non-isothermal conditions are studied. The parameters affecting the growth of equiaxed and columnar dendrites are discussed. The calculated results are verified using the analytical model and previous experiments. The method provides a sophisticated approach to the solidification of multi-phase and multi-component systems.
A novel power-efficient high-speed clock management unit using quantum-dot cellular automata
NASA Astrophysics Data System (ADS)
Abutaleb, M. M.
2017-04-01
Quantum-dot cellular automata (QCA) is one of the most attractive alternatives for complementary metal-oxide semiconductor technology. The QCA widely supports a new paradigm in the field of nanotechnology that has the potential for high density, low power, and high speed. The clock manager is an essential building block in the new microwave and radio frequency integrated circuits. This paper describes a novel QCA-based clock management unit (CMU) that provides innovative clocking capabilities. The proposed CMU is achieved by utilizing edge-triggered D-type flip-flops (D-FFs) in the design of frequency synthesizer and phase splitter. Edge-triggered D-FF structures proposed in this paper have the successful QCA implementation and simulation with the least complexity and power dissipation as compared to earlier structures. The frequency synthesizer is used to generate new clock frequencies from the reference clock frequency based on a combination of power-of-two frequency dividers. The phase splitter is integrated with the frequency synthesizer to generate four clock signals that are 90o out of phase with each other. This paper demonstrates that the proposed QCA CMU structure has a superior performance. Furthermore, the proposed CMU is straightforwardly scalable due to the use of modular component architecture.
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.
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.
NASA Astrophysics Data System (ADS)
Wang, Min; Zhou, Jianxin; Yin, Yajun; Nan, Hai; Zhang, Dongqiao; Tu, Zhixin
2017-10-01
A 3D cellular automata model is used to simulate normal austenitic grain growth in this study. The proposed model considers both the curvature- and thermodynamics-driven mechanisms of growth. The 3D grain growth kinetics shows good agreement with the Beck equation. Moreover, the growth exponent and grain size distribution calculated by the proposed model coincides well with experimental and simulation results from other researchers. A linear relationship is found between the average relative grain size and the grain face number. More specifically, for average relative grain sizes exceeding 0.5, the number of faces increases linearly with relative grain size. For average relative grain sizes <0.5, this relationship is changed. Results simulated by the proposed model are translated to physical meaning by adjusting the actual temperature, space, and time for austenitic grain growth. The calibrated results are found to be in agreement with the simulation results from other research as well as the experimental results. By means of calibration of the proposed model, we can reliably predict the grain size in actual grain growth.
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)
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.
Tokunaga, Ken
2009-03-14
Signal transmission through Creutz-Taube complexes [(NH(3))(5)Ru-BL-Ru(NH(3))(5)](5+)(BL = pyrazine (py), 4,4'-bipyridine (bpy)), which are simplified models of the molecular quantum-dot cellular automata (molecular QCA), is discussed both statically and dynamically with a view to designing useful molecular QCA. In the static treatment, the difference between stationary states before and after the switch of the input to the molecular QCA is discussed. In the dynamic treatment, time-evolution of electronic structure after the moment of the switch is simulated, and a simple method for the simulation is also proposed. Geometric and electronic structures are obtained by density functional theory (UB3LYP) and Hartree-Fock (UHF) calculations, and discussions are based on the Mulliken charge. It is found that signal amplitude (A) is strongly dependent on the position and charge of the input to the molecular QCA, but signal period (T) is almost independent of them. These results are explained from molecular orbitals and orbital energies, and a set of large A (large overlap between orbitals) and small T (large energy gap) generally leads to a prompt signal transmission.
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)
Aburas, Maher Milad; Ho, Yuek Ming; Ramli, Mohammad Firuz; Ash'aari, Zulfa Hanan
2016-10-01
In recent years, several types of simulation and prediction models have been used within a GIS environment to determine a realistic future for urban growth patterns. These models include quantitative and spatio-temporal techniques that are implemented to monitor urban growth. The results derived through these techniques are used to create future policies that take into account sustainable development and the demands of future generations. The aim of this paper is to provide a basis for a literature review of urban Cellular Automata (CA) models to find the most suitable approach for a realistic simulation of land use changes. The general characteristics of simulation models of urban growth and urban CA models are described, and the different techniques used in the design of these models are classified. The strengths and weaknesses of the various models are identified based on the analysis and discussion of the characteristics of these models. The results of the review confirm that the CA model is one of the strongest models for simulating urban growth patterns owing to its structure, simplicity, and possibility of evolution. Limitations of the CA model, namely weaknesses in the quantitative aspect, and the inability to include the driving forces of urban growth in the simulation process, may be minimized by integrating it with other quantitative models, such as via the Analytic Hierarchy Process (AHP), Markov Chain and frequency ratio models. Realistic simulation can be achieved when socioeconomic factors and spatial and temporal dimensions are integrated in the simulation process.
Gradient Driven Flow: Lattice Gas, Diffusion Equation and Measurement Scales
2001-01-01
03-200 1 Journal Article (refereed) 2001 4. TITLE AND SUBTITLE Sa. CONTRACT NUMBER Gradient Driven Flow : Lattice Gas, Diffusion Equation and...time regime, the collective motion exhibits an onset of oscillation. 15. SUBJECT TERMS Diffusion; Fick’s Law; Gradient Driven Flow ; Lattice Gas 16...Form 298 (Rev. 8-98) Prescribed by ANSI Std. Z39.18 20010907 062 Gradient driven flow : lattice gas, diffusion equation and measurement scales R.B
NASA Astrophysics Data System (ADS)
Ohmori, Shousuke; Yamazaki, Yoshihiro
2016-01-01
Ultradiscrete equations are derived from a set of reaction-diffusion partial differential equations, and cellular automaton rules are obtained on the basis of the ultradiscrete equations. Some rules reproduce the dynamical properties of the original reaction-diffusion equations, namely, bistability and pulse annihilation. Furthermore, other rules bring about soliton-like preservation and periodic pulse generation with a pacemaker, which are not obtained from the original reaction-diffusion equations.
Escobar Ospina, María Elena; Perdomo, Jonatan Gómez
2013-01-01
simulated under the combined technique of cellular automata and agent-based models, the HPV life cycle can be simulated allowing for observations at different stages. The proposed model then can be used as a support tool in the investigation of HPV16, in particular (as part of our future work) to develop drugs as agents in the control of the HPV16 disease. Copyright © 2012 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Behera, Mukunda D.; Borate, Santosh N.; Panda, Sudhindra N.; Behera, Priti R.; Roy, Partha S.
2012-08-01
Improper practices of land use and land cover (LULC) including deforestation, expansion of agriculture and infrastructure development are deteriorating watershed conditions. Here, we have utilized remote sensing and GIS tools to study LULC dynamics using Cellular Automata (CA)-Markov model and predicted the future LULC scenario, in terms of magnitude and direction, based on past trend in a hydrological unit, Choudwar watershed, India. By analyzing the LULC pattern during 1972, 1990, 1999 and 2005 using satellite-derived maps, we observed that the biophysical and socio-economic drivers including residential/industrial development, road-rail and settlement proximity have influenced the spatial pattern of the watershed LULC, leading to an accretive linear growth of agricultural and settlement areas. The annual rate of increase from 1972 to 2004 in agriculture land, settlement was observed to be 181.96, 9.89 ha/year, respectively, while decrease in forest, wetland and marshy land were 91.22, 27.56 and 39.52 ha/year, respectively. Transition probability and transition area matrix derived using inputs of (i) residential/industrial development and (ii) proximity to transportation network as the major causes. The predicted LULC scenario for the year 2014, with reasonably good accuracy would provide useful inputs to the LULC planners for effective management of the watershed. The study is a maiden attempt that revealed agricultural expansion is the main driving force for loss of forest, wetland and marshy land in the Choudwar watershed and has the potential to continue in future. The forest in lower slopes has been converted to agricultural land and may soon take a call on forests occurring on higher slopes. Our study utilizes three time period changes to better account for the trend and the modelling exercise; thereby advocates for better agricultural practices with additional energy subsidy to arrest further forest loss and LULC alternations.
NASA Astrophysics Data System (ADS)
Dottori, F.; Todini, E.
2011-01-01
Over the last decade, several flood inundation models based on a reduced complexity approach have been developed and successfully applied in a wide range of practical cases. In the present paper, a model based on the cellular automata approach is analyzed in detail and tested in several numerical cases, comparing the results both with analytical solutions and different hydraulic models. In order to improve the model’s performance, the original code based on the diffusive wave equations and a constant time step scheme is modified through the implementation of two techniques available in literature: an inertial formulation for the computation of discharges, originally developed for the LISFLOOD-FP model by Bates et al. (2010); and the incorporation of a local adaptive time step algorithm, based on a technique originally presented by Zhang et al. (1994). The analysis of the numerical cases showed that the proposed model can be a valuable tool for the simulation of flood inundation events. When applied to one-dimensional numerical cases, the model well reproduced the wave propagation, whereas it showed some limitations in reproducing two-dimensional flow dynamics in respect to a model based on the full shallow water equations. However, differences were found to be comparable with the uncertainty level related to available data for actual flood events. The use of the inertial formulation was very effective in all the cases, and reduced run time up to 97% as compared with the diffusive formulation, although it did not improve the overall accuracy of results. Finally, the incorporation of the local time step algorithm produced a speedup from 1.2 x to 4 x, depending on the simulation and the model version in use, with no loss of accuracy in the results.
Sarkar, Chinmoy; Abbasi, S A
2006-09-01
The strategies to prevent accidents from occurring in a process industry, or to minimize the harm if an accident does take place, always revolve around forecasting the likely accidents and their impacts. Based on the likely frequency and severity of the accidents, resources are committed towards preventing the accidents. Nearly all techniques of ranking hazardous units, be it the hazard and operability studies, fault tree analysis, hazard indice, etc.--qualitative as well as quantitative--depend essentially on the assessment of the likely frequency and the likely harm accidents in different units may cause. This fact makes it exceedingly important that the forecasting the accidents and their likely impact is done as accurately as possible. In the present study we introduce a new approach to accident forecasting based on the discrete modeling paradigm of cellular automata. In this treatment an accident is modeled as a self-evolving phenomena, the impact of which is strongly influenced by the size, nature, and position of the environmental components which lie in the vicinity of the accident site. The outward propagation of the mass, energy and momentum from the accident epicenter is modeled as a fast diffusion process occurring in discrete space-time coordinates. The quantum of energy and material that would flow into each discrete space element (cell) due to the accidental release is evaluated and the degree of vulnerability posed to the receptors if present in the cell is measured at the end of each time element. This approach is able to effectively take into account the modifications in the flux of energy and material which occur as a result of the heterogeneous environment prevailing between the accident epicenter and the receptor. Consequently, more realistic accident scenarios are generated than possible with the prevailing techniques. The efficacy of the approach has been illustrated with case studies.
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.
Lattice gas dynamics under continuous measurement
NASA Astrophysics Data System (ADS)
Patil, Yogesh Sharad; Cheung, Hil F. H.; Madjarov, Ivaylo S.; Chen, Huiyao Y.; Vengalattore, Mukund
2016-05-01
The act of measurement has a profound consequences quantum systems. While this backaction has so far been discussed as being a limitation on the precision of measurements, it is increasingly being appreciated that measurement backaction is a powerful and versatile 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. Here, we show how spatially designed measurement landscapes can be used to realize entropy segregation in lattice gases. This presents an alternate path to the longstanding challenge of realizing lattice gases with sufficiently low entropy to access regimes of correlated quantum behavior such as Néel ordered states. This work is supported by the ARO MURI on non-equilibrium dynamics.
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.
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.
On Localizations in Minimal Cellular Automata Model of Two-Species Mutualism
NASA Astrophysics Data System (ADS)
Adamatzky, Andrew; Grube, Martin
A mutualism is an interaction where the involved species benefit from each other. We study a two-dimensional hexagonal three-state cellular automaton model of a two-species mutualistic system. The simple model is characterized by four parameters of propagation and survival dependencies between the species. We map the parametric set onto the basic types of space-time structures emerged in the mutualistic population dynamic. The structures discovered include propagating quasi-one dimensional patterns, very slowly growing clusters, still and oscillatory stationary localizations. Although we hardly find such idealized patterns in nature, due to increased complexity of interaction phenomena, we recognize our findings as basic spatial patterns of mutualistic systems, which can be used as baseline to build up more complex models.
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.
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.
2016-01-01
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
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 1f 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.
Using economy of means to evolve transition rules within 2D cellular automata.
Ripps, David L
2010-01-01
Running a cellular automaton (CA) on a rectangular lattice is a time-honored method for studying artificial life on a digital computer. Commonly, the researcher wishes to investigate some specific or general mode of behavior, say, the ability of a coherent pattern of points to glide within the lattice, or to generate copies of itself. This technique has a problem: how to design the transitions table-the set of distinct rules that specify the next content of a cell from its current content and that of its near neighbors. Often the table is painstakingly designed manually, rule by rule. The problem is exacerbated by the potentially vast number of individual rules that need be specified to cover all combinations of center and neighbors when there are several symbols in the alphabet of the CA. In this article a method is presented to have the set of rules evolve automatically while running the CA. The transition table is initially empty, with rules being added as the need arises. A novel principle drives the evolution: maximum economy of means-maximizing the reuse of rules introduced on previous cycles. This method may not be a panacea applicable to all CA studies. Nevertheless, it is sufficiently potent to evolve sets of rules and associated patterns of points that glide (periodically regenerate themselves at another location) and to generate gliding "children" that then "mate" by collision.
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.
Convergence Time and Phase Transition in a Non-monotonic Family of Probabilistic Cellular Automata
NASA Astrophysics Data System (ADS)
Ramos, A. D.; Leite, A.
2017-08-01
In dynamical systems, some of the most important questions are related to phase transitions and convergence time. We consider a one-dimensional probabilistic cellular automaton where their components assume two possible states, zero and one, and interact with their two nearest neighbors at each time step. Under the local interaction, if the component is in the same state as its two neighbors, it does not change its state. In the other cases, a component in state zero turns into a one with probability α , and a component in state one turns into a zero with probability 1-β . For certain values of α and β , we show that the process will always converge weakly to δ 0, the measure concentrated on the configuration where all the components are zeros. Moreover, the mean time of this convergence is finite, and we describe an upper bound in this case, which is a linear function of the initial distribution. We also demonstrate an application of our results to the percolation PCA. Finally, we use mean-field approximation and Monte Carlo simulations to show coexistence of three distinct behaviours for some values of parameters α and β.
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.
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
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)
Marko, K.; Zulkarnain, F.; Kusratmoko, E.
2016-11-01
Land cover changes particular in urban catchment area has been rapidly occur. Land cover changes occur as a result of increasing demand for built-up area. Various kinds of environmental and hydrological problems e.g. floods and urban heat island can happen if the changes are uncontrolled. This study aims to predict land cover changes using coupling of Markov chains and cellular automata. One of the most rapid land cover changes is occurs at upper Ci Leungsi catchment area that located near Bekasi City and Jakarta Metropolitan Area. Markov chains has a good ability to predict the probability of change statistically while cellular automata believed as a powerful method in reading the spatial patterns of change. Temporal land cover data was obtained by remote sensing satellite imageries. In addition, this study also used multi-criteria analysis to determine which driving factor that could stimulate the changes such as proximity, elevation, and slope. Coupling of these two methods could give better prediction model rather than just using it separately. The prediction model was validated using existing 2015 land cover data and shown a satisfactory kappa coefficient. The most significant increasing land cover is built-up area from 24% to 53%.
NASA Astrophysics Data System (ADS)
Mendonça, J. Ricardo G.; Gevorgyan, Yeva
2017-05-01
We investigate one-dimensional elementary probabilistic cellular automata (PCA) whose dynamics in first-order mean-field approximation yields discrete logisticlike growth models for a single-species unstructured population with nonoverlapping generations. Beginning with a general six-parameter model, we find constraints on the transition probabilities of the PCA that guarantee that the ensuing approximations make sense in terms of population dynamics and classify the valid combinations thereof. Several possible models display a negative cubic term that can be interpreted as a weak Allee factor. We also investigate the conditions under which a one-parameter PCA derived from the more general six-parameter model can generate valid population growth dynamics. Numerical simulations illustrate the behavior of some of the PCA found.
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.
Mendonça, J Ricardo G; Gevorgyan, Yeva
2017-05-01
We investigate one-dimensional elementary probabilistic cellular automata (PCA) whose dynamics in first-order mean-field approximation yields discrete logisticlike growth models for a single-species unstructured population with nonoverlapping generations. Beginning with a general six-parameter model, we find constraints on the transition probabilities of the PCA that guarantee that the ensuing approximations make sense in terms of population dynamics and classify the valid combinations thereof. Several possible models display a negative cubic term that can be interpreted as a weak Allee factor. We also investigate the conditions under which a one-parameter PCA derived from the more general six-parameter model can generate valid population growth dynamics. Numerical simulations illustrate the behavior of some of the PCA found.
NASA Astrophysics Data System (ADS)
Bhowmik, Dhrubajyoti; Saha, Apu Kr; Dutta, Paramartha; Nandi, Supratim
2017-08-01
Quantum-dot Cellular Automata (QCA) is one of the most substitutes developing nanotechnologies for electronic circuits, as a result of lower force utilization, higher speed and smaller size in correlation with CMOS innovation. The essential devices, a Quantum-dot cell can be utilized to logic gates and wires. As it is the key building block on nanotechnology circuits. By applying simple gates, the hardware requirements for a QCA circuit can be decreased and circuits can be less complex as far as level, delay and cell check. This article exhibits an unobtrusive methodology for actualizing novel upgraded simple and universal gates, which can be connected to outline numerous variations of complex QCA circuits. Proposed gates are straightforward in structure and capable as far as implementing any digital circuits. The main aim is to build all basic and universal gates in a simple circuit with and without crossbar-wire. Simulation results and physical relations affirm its handiness in actualizing each advanced circuit.
NASA Astrophysics Data System (ADS)
Minkoff, Darío R.; Escapa, Mauricio; Ferramola, Félix E.; Maraschín, Silvio D.; Pierini, Jorge O.; Perillo, Gerardo M. E.; Delrieux, Claudio
2006-09-01
The Bahía Blanca Estuary (38° 50' S, and 62° 30' W) presents salt marshes where interactions between the local flora ( Sarcocornia perennis) and fauna ( Chasmagnathus granulatus) generate some kind of salt pans that alter the normal water circulation and condition its flow and course towards tidal creeks. The crab-vegetation dynamics in the salt marsh presents variations that cannot be quantified in a reasonable period of time. The interaction between S. perennis plant and C. granulatus crab is based on simple laws, but its result is a complex biological mechanism that causes an erosive process on the salt marsh and favors the formation of tidal creeks. To study it, a Cellular Automata model is proposed, based on the laws deduced from the observation of these phenomena in the field, and then verified with measurable data within macroscale time units. Therefore, the objective of this article is to model how the interaction between C. granulatus and S. perennis modifies the landscape of the salt marsh and influences the path of tidal creeks. The model copies the basic laws that rule the problem based on purely biological factors. The Cellular Automata model proved capable of reproducing the effects of the interaction between plants and crabs in the salt marsh. A study of the water drainage of the basins showed that this interaction does indeed modify the development of tidal creeks. Model dynamics would likewise follow different laws, which would provide a different formula for the probability of patch dilation. The patch shape can be obtained changing the pattern that dilates.
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
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.
Machineni, Lakshmi; Rajapantul, Anil; Nandamuri, Vandana; Pawar, Parag D
2017-03-01
The resistance of bacterial biofilms to antibiotic treatment has been attributed to the emergence of structurally heterogeneous microenvironments containing metabolically inactive cell populations. In this study, we use a three-dimensional individual-based cellular automata model to investigate the influence of nutrient availability and quorum sensing on microbial heterogeneity in growing biofilms. Mature biofilms exhibited at least three structurally distinct strata: a high-volume, homogeneous region sandwiched between two compact sections of high heterogeneity. Cell death occurred preferentially in layers in close proximity to the substratum, resulting in increased heterogeneity in this section of the biofilm; the thickness and heterogeneity of this lowermost layer increased with time, ultimately leading to sloughing. The model predicted the formation of metabolically dormant cellular microniches embedded within faster-growing cell clusters. Biofilms utilizing quorum sensing were more heterogeneous compared to their non-quorum sensing counterparts, and resisted sloughing, featuring a cell-devoid layer of EPS atop the substratum upon which the remainder of the biofilm developed. Overall, our study provides a computational framework to analyze metabolic diversity and heterogeneity of biofilm-associated microorganisms and may pave the way toward gaining further insights into the biophysical mechanisms of antibiotic resistance.
Local lattice-gas model for immiscible fluids
NASA Technical Reports Server (NTRS)
Chen, S.; Doolen, G. D.; Eggert, K.; Grunau, D.; Loh, E. Y.
1991-01-01
A lattice-gas model is presented for two-dimensional immiscible fluid flows with surface tension that uses strictly local collision rules. Instead of using a local total color flux as Somers and Rem (1991), local colored holes are used to be the memory of particles of the same color. Interactions between walls and fluids are included that produce arbitrary contact angles.
Noise and compressibility in lattice-gas fluids
NASA Technical Reports Server (NTRS)
Dahlburg, Jill P.; Montgomery, David; Doolen, Gary D.
1987-01-01
Computations are reported in which the hexagonal lattice gas is used to simulate two-dimensional Navier-Stokes shear flows. Limitations associated with noise in the initial loading and compressible effects associated with a velocity-dependent equation of state arise and interact with each other. A relatively narrow window in density and flow speed exhibits physical behavior.
An evolving algebra approach to formal description of a class of automata networks
NASA Astrophysics Data System (ADS)
Severyanov, V. M.
2003-04-01
The Automata Networks considered here and called Hyperbolic Cellular Automata are based on Iterated Function Systems and can be considered as a generalization of Cellular Automata. The Evolving Algebras have been proposed by Yuri Gurevich to be the models for arbitrary computational processes. They provide a formal method for executable specifications. In the paper, an evolving algebra approach to formal description of Hyperbolic Cellular Automata is presented.
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
Tsukerblat, Boris; Palii, Andrew; 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)
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
NASA Astrophysics Data System (ADS)
Crisci, G. M.; Avolio, M. V.; D'Ambrosio, D.; di Gregorio, S.; Lupiano, G. V.; Rongo, R.; Spataro, W.; Benhcke, B.; Neri, M.
2009-04-01
Forecasting the time, character and impact of future eruptions is difficult at volcanoes with complex eruptive behaviour, such as Mount Etna, where eruptions occur from the summit and on the flanks, affecting areas distant from each other. Modern efforts for hazard evaluation and contingency planning in volcanic areas draw heavily on hazard maps and numerical simulations. The computational model here applied belongs to the SCIARA family of lava flow simulation models. In the specific case this is the SCIARA-fv release, which is considered to give the most accurate and efficient performance, given the extent (567 km2) of the study area and the great number of simulations to be carried out. The model is based on the Cellular Automata computational paradigm and, specifically, on the Macroscopic Cellular Automata approach for the modelling of spatially extended dynamic systems2. This work addresses the problem of compiling high-detailed susceptibility maps with an elaborate approach in the numerical simulation of Etnean lava flows, based on the results of 39,300 simulations of flows erupted from a grid of 393 hypothetical vents in the eastern sector of Etna. This sector was chosen because it is densely populated and frequently affected by flank eruptions. Besides the definition of general susceptibility maps, the availability of a large number of lava flows of different eruption types, magnitudes and locations simulated for this study allows the instantaneous extraction of various scenarios on demand. For instance, in a Civil Defence oriented application, it is possible to identify all source areas of lava flows capable of affecting a given area of interest, such as a town or a major infrastructure. Indeed, this application is rapidly accomplished by querying the simulation database, by selecting the lava flows that affect the area of interest and by circumscribing their sources. Eventually, a specific category of simulation is dedicated to the assessment of protective
Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin
2017-01-01
Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study—simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan. PMID:28617348
Dakua, Sarada Prasad; Abinahed, Julien; Al-Ansari, Abdulla
2015-04-01
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 [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text], 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.
Gangadari, Bhoopal Rao; Rafi Ahamed, Shaik
2016-09-01
In biomedical, data security is the most expensive resource for wireless body area network applications. Cryptographic algorithms are used in order to protect the information against unauthorised access. Advanced encryption standard (AES) cryptographic algorithm plays a vital role in telemedicine applications. The authors propose a novel approach for design of substitution bytes (S-Box) using second-order reversible one-dimensional cellular automata (RCA(2)) as a replacement to the classical look-up-table (LUT) based S-Box used in AES algorithm. The performance of proposed RCA(2) based S-Box and conventional LUT based S-Box is evaluated in terms of security using the cryptographic properties such as the nonlinearity, correlation immunity bias, strict avalanche criteria and entropy. Moreover, it is also shown that RCA(2) based S-Boxes are dynamic in nature, invertible and provide high level of security. Further, it is also found that the RCA(2) based S-Box have comparatively better performance than that of conventional LUT based S-Box.
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.
Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin
2017-06-15
Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study-simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.
NASA Astrophysics Data System (ADS)
Nurhidayati, E.; Buchori, I.; Mussadun; Fariz, T. R.
2017-07-01
Pontianak waterfront city as water-based urban has the potential of water resources, socio-economic, cultural, tourism and riverine settlements. Settlements areas in the eastern district of Pontianak waterfront city is located in the triangle of Kapuas river and Landak river. This study uses quantitative-GIS methods that integrates binary logistic regression and Cellular Automata-Markov models. The data used in this study such as satellite imagery Quickbird 2003, Ikonos 2008 and elevation contour interval 1 meter. This study aims to discover the settlement land use changes in 2003-2014 and to predict the settlements areas in 2020. This study results the accuracy in predicting of changes in settlements areas shows overall accuracy (79.74%) and the highest kappa index (0.55). The prediction results show that settlement areas (481.98 Ha) in 2020 and the increasingly of settlement areas (6.80 Ha/year) in 2014-2020. The development of settlement areas in 2020 shows the highest land expansion in Parit Mayor Village. The results of regression coefficient value (0) of flooding variable, so flooding did not influence to the development of settlement areas in the eastern district of Pontianak because the building’s adaptation of rumah panggung’s settlements was very good which have adjusted to the height of tidal flood.
Tokunaga, Ken
2010-01-01
Dynamic behavior of signal transmission through metal complexes [L5M-BL-ML5]5+ (M=Fe, Ru, Os, BL=pyrazine (py), 4,4’-bipyridine (bpy), L=NH3), which are simplified models of the molecular quantum-dot cellular automata (molecular QCA), is discussed from the viewpoint of one-electron theory, density functional theory. It is found that for py complexes, the signal transmission time (tst) is Fe(0.6 fs) < Os(0.7 fs) < Ru(1.1 fs) and the signal amplitude (A) is Fe(0.05 e) < Os(0.06 e) < Ru(0.10 e). For bpy complexes, tst and A are Fe(1.4 fs) < Os(1.7 fs) < Ru(2.5 fs) and Os(0.11 e) < Ru(0.12 e) < Fe(0.13 e), respectively. Bpy complexes generally have stronger signal amplitude, but waste longer time for signal transmission than py complexes. Among all complexes, Fe complex with bpy BL shows the best result. These results are discussed from overlap integral and energy gap of molecular orbitals.
NASA Astrophysics Data System (ADS)
Heng, Fong Wan; Siang, Gan Yee; Sarmin, Nor Haniza; Turaev, Sherzod
2014-06-01
Recently, the relation of automata and groups has been studied. It was shown that properties of groups can be studied using state diagrams of modified automata and modified Watson-Crick automata. In this work, we investigate the relation of subgroups with the modified finite and Watson-Crick automata. We also establish the conditions for the recognition of subgroups by using the modified automata.
High-density equation of state for a lattice gas.
Ushcats, M V
2015-05-01
For the lattice gas models of arbitrary geometry and dimensions with absolute repulsion between particles at zero distance (a hard core identical to a single lattice site) and arbitrary repulsion or attraction at other distances, the "hole-particle" symmetry of the system potential energy has been stated and an equation of state has been derived on the basis of the classical Gibbs statistics. The equation is completely analogous to the well-known virial equation of state, except that it is more accurate at high-density states, while the virial equation has the low-density limitation. Both equations contain the common set of the so-called irreducible integrals, related to the corresponding virial coefficients, and can be used together to describe the behavior of a lattice gas in a wide range of densities.
Lattice gas simulations of dynamical geometry in one dimension.
Love, Peter J; Boghosian, Bruce M; Meyer, David A
2004-08-15
We present numerical results obtained using a lattice gas model with dynamical geometry. The (irreversible) macroscopic behaviour of the geometry (size) of the lattice is discussed in terms of a simple scaling theory and obtained numerically. The emergence of irreversible behaviour from the reversible microscopic lattice gas rules is discussed in terms of the constraint that the macroscopic evolution be reproducible. The average size of the lattice exhibits power-law growth with exponent at late times. The deviation of the macroscopic behaviour from reproducibility for particular initial conditions ('rogue states') is investigated as a function of system size. The number of such 'rogue states' is observed to decrease with increasing system size. Two mean-field analyses of the macroscopic behaviour are also presented. Copyright 2004 The Royal Society
Quantum lattice gas algorithm for the telegraph equation.
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.
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)
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
Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan
2016-12-14
Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits.
NASA Astrophysics Data System (ADS)
Iovine, G.; di Gregorio, S.; D'Ambrosio, D.; Lupiano, V.; Merenda, L.; Nardi, G.
On winter 1999, heavy rainfall severely stroke Campania region, triggering numerous debris flows on the slopes of the San Martino Valle Caudina-Cervinara area. Soil slips originated on the slopes, within the weathered volcaniclastic mantle of detrital cover overlying the carbonate skeleton of the massif. Debris slides soon turned into fast flow- ing mixtures of matrix and large blocks, downslope eroding the detrital mantle and increasing its original volume. At the base of the slopes, flows impacted on the urban areas, causing victims and severe destruction. Starting from a recent study on landslide risk conditions in Campania, carried out by the local Basin Authority, an evaluation of debris-flow susceptibility has been performed for n.8 selected areas ("red zones") of the above mentioned villages. According to that study, such red zones would be char- acterised by the highest risk levels (within the administrative boundaries of the same villages). Our susceptibility analysis has been performed by applying SCIDDICA-S3 - a Cellular Automata model, specifically developed, after the Sarno 1998 disaster, for simulating the spatial evolution of debris flows. Detailed topographic data and a map of the detrital coverage had to be given to the model, as input matrixes. A digi- tal "world" of hexagonal cells was adopted; type and amount of detrital mantle were collected through detailed field surveying. Real cases, selected among the landslides triggered on winter 1999, have been utilised for validating SCIDDICA and defining the best values for parameters: the validation has been carried out in a GIS environ- ment, by quantitatively comparing simulations with actual cases. Through geological evaluations, source locations of new phenomena have then been hypothesised within the red-zones. Initial volume for these new cases has been estimated by considering the actual statistics of the 1999 disaster. Finally, by merging the results of simulations, a deterministic
Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan
2016-01-01
Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits. PMID:27983633
NASA Astrophysics Data System (ADS)
Tanimoto, Jun; Hagishima, Aya; Tanaka, Yasukaka
2010-12-01
An improved cellular automaton model for pedestrian dynamics was established, where both static floor field and collision effect derived from game theory were considered. Several model parameters were carefully determined by previous studies. Results obtained through model-based simulation and analytical approach (derived from mean field approximation) proved that outflow rate from an evacuation exit, which is usually estimated using outflow coefficient in building codes in Japan, can be improved by placing an appropriate obstacle in front of the exit. This can reduce collision probability at the exit by increasing collisions around the obstacles ahead of the exit.
NASA Astrophysics Data System (ADS)
Wang, Yang; Chen, Yan-Yan
2016-12-01
The signalized traffic is considerably complex due to the fact that various driving behaviors have emerged to respond to traffic signals. However, the existing cellular automaton models take the signal-vehicle interactions into account inadequately, resulting in a potential risk that vehicular traffic flow dynamics may not be completely explored. To remedy this defect, this paper proposes a more realistic cellular automaton model by incorporating a number of the driving behaviors typically observed when the vehicles are approaching a traffic light. In particular, the anticipatory behavior proposed in this paper is realized with a perception factor designed by considering the vehicle speed implicitly and the gap to its preceding vehicle explicitly. Numerical simulations have been performed based on a signal controlled road which is partitioned into three sections according to the different reactions of drivers. The effects of microscopic driving behaviors on Kerner's time-delayed traffic breakdown at signal (Kerner 2011, 2013) have been investigated with the assistance of spatiotemporal pattern and trajectory analysis. Furthermore, the contributions of the driving behaviors on the traffic breakdown have been statistically examined. Finally, with the activation of the anticipatory behavior, the influences of the other driving behaviors on the formation of platoon have been investigated in terms of the number of platoons, the averaged platoon size, and the averaged flow rate.
NASA Astrophysics Data System (ADS)
Kokubo, Satoshi; Tanimoto, Jun; Hagishima, Aya
2011-02-01
Most of the conventional traffic Cellular Automaton (CA) models based on the Nagel-Schreckenberg model (NaSch model) have two problems: an unrealistic deceleration dynamics when a vehicle agent collides with a preceding vehicle in a stopping event, and the problem with reproducing the synchronized flow in Kerner's three-phase theory. In this paper, a revised stochastic Nishinari-Fukui-Schadschneider (S-NFS) model, belonging to the class of NaSch models, is presented. The proposed CA model, where a random braking effect is improved by considering the dependency on the velocity difference and heading distance with a preceding vehicle, is confirmed to overcome the two above-mentioned drawbacks.
NASA Astrophysics Data System (ADS)
Pazzona, Federico G.; Demontis, Pierfranco; Suffritti, Giuseppe B.
2009-12-01
In this second paper we exploit our thermodynamic partitioning cellular automaton (PCA) developed in Paper I [Pazzona et al., J. Chem. Phys. 131, 234703 (2009)] to study interacting molecules adsorbed in microporous materials. We present a mean-field theory of the single cell model at equilibrium followed by a detailed description of the procedure we propose to calculate the chemical potential in the canonical ensemble. Finally we use our approach to simulate transport properties starting from the parameterization devised by Ayappa [J. Chem. Phys. 111, 4736 (1999)] to reproduce the adsorption properties of xenon in zeolite NaA. We report how the correlations included in the PCA evolution rule affect the estimated self-diffusion coefficient.
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.
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.
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)
Dynamic lattice-gas model of underpotential deposition
NASA Astrophysics Data System (ADS)
Brown, Gregory; Rikvold, Per Arne; Novotny, M. A.; Wieckowski, Andrzej
1998-03-01
Underpotential deposition (UPD) is the process by which a monolayer or less of one metal is adsorbed onto the surface of another at electrode potentials more positive than those at which bulk deposition occurs. For particular combinations of metals, lattice-gas models have been formulated and studied using both analytical and numerical techniques. Dynamic Monte Carlo simulations of a lattice-gas model of UPD of copper onto Au(111) in the presence of sulfuric acid are presented. The simulations include adsorption, desorption, and lateral diffusion and span timescales from 10-9 to 10^1 s. The results reproduce the strong asymmetry seen in experimental current profiles that occur after a sudden potential change.(M. H. Hölzle, et al.), J. Electroanal. Chem. \\underbar371, 101 (1994). The simulation technique can also be used to understand features in cyclic-voltammetry profiles, where the applied potential is changed continuously.
NASA Astrophysics Data System (ADS)
Halder, Chandan; Karmakar, Anish; Hasan, Sk. Md.; Chakrabarti, Debalay; Pietrzyk, Maciej; Chakraborti, Nirupam
2016-12-01
The development of ferrite-martensite dual-phase microstructures by cold-rolling and intercritical annealing of 0.06 wt pct carbon steel was systematically studied using a dilatometer for two different heating rates (1 and 10 K/s). A step quenching treatment has been designed to develop dual-phase structures having a similar martensite fraction for two different heating rates. An increase in heating rate seemed to refine the ferrite grain size, but it increased the size and spacing of the martensitic regions. As a result, the strength of the steel increased with heating rate; however, the formability was affected. It has been concluded that the distribution of C during the annealing treatment of cold-rolled steel determines the size, distribution, and morphology of martensite, which ultimately influences the mechanical properties. Experimental detection of carbon distribution in austenite is difficult during annealing of the cold-rolled steel as the phase transformation occurs at a high temperature and C is an interstitial solute, which diffuses fast at that temperature. Therefore, a cellular automata (CA)-based phase transformation model is proposed in the present study for the prediction of C distribution in austenite during annealing of steel as the function of C content and heating rate. The CA model predicts that the carbon distribution in austenite becomes more inhomogeneous when the heating rate increases. In the CA model, the extent of carbon inhomogeneity is measured using a kernel averaging method for different orders of neighbors, which accounts for the different physical space during calculation. The obtained results reveal that the 10th order (covering 10- µm physical spaces around the cell of interest) is showing the maximum inhomogeneity of carbon and the same effect has been investigated and confirmed using auger electron spectroscopy (AES) for 0.06 wt pct carbon steel. Furthermore, the optimization of carbon homogeneity with respect to heating
NASA Astrophysics Data System (ADS)
D'Ambrosio, D.; Iovine, G.
2003-04-01
Cellular Automata (CA) offer a valid alternative to the classic approach, based on partial differential equation, in order to simulate complex phenomena, when these latter can be described in terms of local interactions among their constituent parts. SCIDDICA S3hex is a two-dimensional hexagonal CA model developed for simulating debris flows: it has recently been applied to several real cases of landslides occurred in Campania (Southern Italy). The release S3hex has been derived by progressively improving an initial simplified CA model, originally derived for simulating simple cases of flow-type landslides. The model requires information related to topography, thickness of erodable regolith overlying the bedrock, and location and extension of landslide sources. Performances depend on a set of global parameters which are utilised in the transition function of the model: their value affect the elementary processes of the transition function and thus the overall results. A fine calibration is therefore an essential phase, in order to evaluate the reliability of the model for successive applications to debris-flow susceptibility zonation. The complexity of both the model and the phenomena to be simulated suggested to employ an automated technique of evaluation, for the determination of the best set of global parameters. Genetic Algorithms (GA) are a powerful optimization tool inspired to natural selection. In the last decades, in spite of their intrinsic simplicity, they have largely been successfully applied on a wide number of highly complex problems. The calibration of the model could therefore be performed through such technique of optimisation, by considering several real cases of study. Owing to the large number of simulations generally needed for performing GA experiments on complex phenomena, which imply long lasting tests on sequential computational architectures, the adoption of a parallel computational environment seemed appropriate: the original source code
NASA Astrophysics Data System (ADS)
Iovine, G.; di Gregorio, S.; Lupiano, V.
On 15-16 December 1999, heavy rainfall severely stroke Campania region (southern Italy), triggering numerous debris flows on the slopes of the San Martino Valle Caudina-Cervinara area. Soil slips originated within the weathered volcaniclastic mantle of soil cover overlying the carbonate skeleton of the massif. Debris slides turned into fast flowing mixtures of matrix and large blocks, downslope eroding the soil cover and increasing their original volume. At the base of the slopes, debris flows impacted on the urban areas, causing victims and severe destruction (Vittori et al., 2000). Starting from a recent study on landslide risk conditions in Campania, carried out by the Regional Authority (PAI -Hydrogeological setting plan, in press), an evaluation of the debris-flow susceptibility has been performed for selected areas of the above mentioned villages. According to that study, such zones would be in fact characterised by the highest risk levels within the administrative boundaries of the same villages ("HR-zones"). Our susceptibility analysis has been performed by applying SCIDDICA S3-hex - a hexagonal Cellular Automata model (von Neumann, 1966), specifically developed for simulating the spatial evolution of debris flows (Iovine et al., 2002). In order to apply the model to a given study area, detailed topographic data and a map of the erodable soil cover overlying the bedrock of the massif must be provided (as input matrices); moreover, extent and location of landslide source must also be given. Real landslides, selected among those triggered on winter 1999, have first been utilised for calibrating SCIDDICA S3-hex and for defining "optimal" values for parameters. Calibration has been carried out with a GIS tool, by quantitatively comparing simulations with actual cases: optimal values correspond to best simulations. Through geological evaluations, source locations of new phenomena have then been hypothesised within the HR-zones. Initial volume for these new cases
Clemente-Juan, Juan Modesto; Palii, Andrew; Coronado, Eugenio; Tsukerblat, Boris
2016-08-09
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
Nava-Sedeño, J M; Hatzikirou, H; Peruani, F; Deutsch, A
2017-02-27
Cellular automata (CA) are discrete time, space, and state models which are extensively used for modeling biological phenomena. CA are "on-lattice" models with low computational demands. In particular, lattice-gas cellular automata (LGCA) have been introduced as models of single and collective cell migration. The interaction rule dictates the behavior of a cellular automaton model and is critical to the model's biological relevance. The LGCA model's interaction rule has been typically chosen phenomenologically. In this paper, we introduce a method to obtain lattice-gas cellular automaton interaction rules from physically-motivated "off-lattice" Langevin equation models for migrating cells. In particular, we consider Langevin equations related to single cell movement (movement of cells independent of each other) and collective cell migration (movement influenced by cell-cell interactions). As examples of collective cell migration, two different alignment mechanisms are studied: polar and nematic alignment. Both kinds of alignment have been observed in biological systems such as swarms of amoebae and myxobacteria. Polar alignment causes cells to align their velocities parallel to each other, whereas nematic alignment drives cells to align either parallel or antiparallel to each other. Under appropriate assumptions, we have derived the LGCA transition probability rule from the steady-state distribution of the off-lattice Fokker-Planck equation. Comparing alignment order parameters between the original Langevin model and the derived LGCA for both mechanisms, we found different areas of agreement in the parameter space. Finally, we discuss potential reasons for model disagreement and propose extensions to the CA rule derivation methodology.
Iterons, fractals and computations of automata
NASA Astrophysics Data System (ADS)
Siwak, Paweł
1999-03-01
Processing of strings by some automata, when viewed on space-time (ST) diagrams, reveals characteristic soliton-like coherent periodic objects. They are inherently associated with iterations of automata mappings thus we call them the iterons. In the paper we present two classes of one-dimensional iterons: particles and filtrons. The particles are typical for parallel (cellular) processing, while filtrons, introduced in (32) are specific for serial processing of strings. In general, the images of iterated automata mappings exhibit not only coherent entities but also the fractals, and quasi-periodic and chaotic dynamics. We show typical images of such computations: fractals, multiplication by a number, and addition of binary numbers defined by a Turing machine. Then, the particles are presented as iterons generated by cellular automata in three computations: B/U code conversion (13, 29), majority classification (9), and in discrete version of the FPU (Fermi-Pasta-Ulam) dynamics (7, 23). We disclose particles by a technique of combinational recoding of ST diagrams (as opposed to sequential recoding). Subsequently, we recall the recursive filters based on FCA (filter cellular automata) window operators, and considered by Park (26), Ablowitz (1), Fokas (11), Fuchssteiner (12), Bruschi (5) and Jiang (20). We present the automata equivalents to these filters (33). Some of them belong to the class of filter automata introduced in (30). We also define and illustrate some properties of filtrons. Contrary to particles, the filtrons interact nonlocally in the sense that distant symbols may influence one another. Thus their interactions are very unusual. Some examples have been given in (32). Here we show new examples of filtron phenomena: multifiltron solitonic collisions, attracting and repelling filtrons, trapped bouncing filtrons (which behave like a resonance cavity) and quasi filtrons.
A (reactive) lattice-gas approach to economic cycles
NASA Astrophysics Data System (ADS)
Ausloos, Marcel; Clippe, Paulette; Miśkiewicz, Janusz; Peķalski, Andrzej
2004-12-01
A microscopic approach to macroeconomic features is intended. A model for macroeconomic behavior under heterogeneous spatial economic conditions is reviewed. A birth-death lattice gas model taking into account the influence of an economic environment on the fitness and concentration evolution of economic entities is numerically and analytically examined. The reaction-diffusion model can also be mapped onto a high-order logistic map. The role of the selection pressure along various dynamics with entity diffusion on a square symmetry lattice has been studied by Monte-Carlo simulation. The model leads to a sort of phase transition for the fitness gap as a function of the selection pressure and to cycles. The control parameter is a (scalar) “business plan”. The business plan(s) allows for spin-offs or merging and enterprise survival evolution law(s), whence bifurcations, cycles and chaotic behavior.
Measurement-Induced Localization of an Ultracold Lattice Gas
NASA Astrophysics Data System (ADS)
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.
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.
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.
Lattice gas simulation of experimentally studied evacuation dynamics.
Helbing, Dirk; Isobe, Motonari; Nagatani, Takashi; Takimoto, Kouhei
2003-06-01
We study the evacuation process from a classroom by means of experiments and simulations. The evacuation of students from a classroom is observed by video cameras, and the escape time of each student is measured. Our experimental results are compared with simulations based on a lattice gas model of pedestrian flows. We find that the empirically identified inefficiencies of the evacuation process can be well reproduced. Our particular focus is on the spatial dependence of the escape times on the initial positions, which is highly significant. The escape time distribution turns out to be rather broad due to a jamming (queuing) of the students at the exit, which determines not only the saturation flow (capacity) but also the temporal characteristics of the evacuation dynamics.
A lattice-gas model for amyloid fibril aggregation
Hong, Liu; Qi, Xianghong; Zhang, Yang
2012-01-01
A simple lattice-gas model, with two fundamental energy terms —elongation and nucleation effects, is proposed for understanding the mechanisms of amyloid fibril formation. Based on the analytical solution and Monte Carlo simulation of 1D system, we have thoroughly explored the dependence of mass concentration, number concentration of amyloid filaments and the lag-time on the initial protein concentration, the critical nucleus size, the strengths of nucleation and elongation effects, respectively. We also found that thickening process (self-association of filaments into multi-strand fibrils) is not essential for the modeling of amyloid filaments through simulations on 2D lattice. Compared with the kinetic model recently proposed by Knowles et al., highly quantitative consistency of two models in the calculation of mass fraction of filaments is found. Moreover our model can generate a better prediction on the number fraction, which is closer to experimental values when the elongation strength gets stronger. PMID:23275684
Dynamics of a lattice gas system of three species
NASA Astrophysics Data System (ADS)
Wang, Yuanshi; Wu, Hong; Liang, Junhao
2016-10-01
This paper considers a mutualism system of three species in which each species provides resource for the next one in a one-directional loop, while there exists spatial competition among them. The system is characterized by a lattice gas model and the cases of obligate mutualisms, obligate-facultative mutualisms and facultative mutualisms are considered. Using dynamical systems theory, it is shown that (i) the mutualisms can lead to coexistence of species; (ii) A weak mutualism or an extremely strong mutualism will result in extinction of species, while even the superior facultative species will be driven into extinction by its over-strong mutualism on the next one; (iii) Initial population density plays a role in the coexistence of species. It is also shown that when there exists weak mutualism, an obligate species can survive by providing more benefit to the next one, and the inferior facultative species will not be driven into extinction if it can strengthen its mutualism on the next species. Moreover, Hopf bifurcation, saddle-node bifurcation and bifurcation of heteroclinic cycles are shown in the system. Projection method is extended to exhibit bistability in the three-dimensional model: when saddle-node bifurcation occurs, stable manifold of the saddle-node point divides intR+3 into two basins of attraction of two equilibria. Furthermore, Lyapunov method is applied to exhibit unstability of heteroclinic cycles. Numerical simulations confirm and extend our results.
Overview: Understanding nucleation phenomena from simulations of lattice gas models
NASA Astrophysics Data System (ADS)
Binder, Kurt; Virnau, Peter
2016-12-01
Monte Carlo simulations of homogeneous and heterogeneous nucleation in Ising/lattice gas models are reviewed with an emphasis on the general insight gained on the mechanisms by which metastable states decay. Attention is paid to the proper distinction of particles that belong to a cluster (droplet), that may trigger a nucleation event, from particles in its environment, a problem crucial near the critical point. Well below the critical point, the lattice structure causes an anisotropy of the interface tension, and hence nonspherical droplet shapes result, making the treatment nontrivial even within the conventional classical theory of homogeneous nucleation. For temperatures below the roughening transition temperature facetted crystals rather than spherical droplets result. The possibility to find nucleation barriers from a thermodynamic analysis avoiding a cluster identification on the particle level is discussed, as well as the question of curvature corrections to the interfacial tension. For the interpretation of heterogeneous nucleation at planar walls, knowledge of contact angles and line tensions is desirable, and methods to extract these quantities from simulations will be mentioned. Finally, also the problem of nucleation near the stability limit of metastable states and the significance of the spinodal curve will be discussed, in the light of simulations of Ising models with medium range interactions.
Enantiomeric phase separation in a lattice gas model: Guggenheim approximation
NASA Astrophysics Data System (ADS)
Huckaby, Dale A.; Shinmi, Masato; Ausloos, Marcel; Clippe, Paulette
1986-05-01
We consider a lattice gas in which the two enantiomeric forms of a tetrahedral molecule, consisting of a central carbon atom bonded to four different groups A, B, G, and H, are adsorbed onto a triangular lattice, such that the carbon atom is above a lattice site, the three bonds to A, B, and G point toward neighboring lattice sites, and the bond to H points perpendicular to and away from the plane of the lattice. For a certain choice of intermolecular interactions, such as may exist between the zwitterion forms of an amino acid, the phase diagram was investigated using a Guggenheim approximation with two order parameters. Enantiomeric phase separation into two symmetric condensed phases occurs at low temperatures. These condensed phases become a single racemic condensed phase at a critical line, and they are in equilibrium with a racemic gas phase along a line of triple points. These two lines coincide at a critical endpoint. The racemic condensed and gas phases are in equilibrium along a two phase coexistence line which begins at the critical endpoint and ends at a critical point. No tricritical point was found in the model for the special choice of interactions studied.
Overview: Understanding nucleation phenomena from simulations of lattice gas models.
Binder, Kurt; Virnau, Peter
2016-12-07
Monte Carlo simulations of homogeneous and heterogeneous nucleation in Ising/lattice gas models are reviewed with an emphasis on the general insight gained on the mechanisms by which metastable states decay. Attention is paid to the proper distinction of particles that belong to a cluster (droplet), that may trigger a nucleation event, from particles in its environment, a problem crucial near the critical point. Well below the critical point, the lattice structure causes an anisotropy of the interface tension, and hence nonspherical droplet shapes result, making the treatment nontrivial even within the conventional classical theory of homogeneous nucleation. For temperatures below the roughening transition temperature facetted crystals rather than spherical droplets result. The possibility to find nucleation barriers from a thermodynamic analysis avoiding a cluster identification on the particle level is discussed, as well as the question of curvature corrections to the interfacial tension. For the interpretation of heterogeneous nucleation at planar walls, knowledge of contact angles and line tensions is desirable, and methods to extract these quantities from simulations will be mentioned. Finally, also the problem of nucleation near the stability limit of metastable states and the significance of the spinodal curve will be discussed, in the light of simulations of Ising models with medium range interactions.
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.
Automata representation for Abelian groups
NASA Astrophysics Data System (ADS)
Fong, Wan Heng; Gan, Yee Siang; Sarmin, Nor Haniza; Turaev, Sherzod
2013-04-01
A finite automaton is one of the classic models of recognition devices, which is used to determine the type of language a string belongs to. A string is said to be recognized by a finite automaton if the automaton "reads" the string from the left to the right starting from the initial state and finishing at a final state. Another type of automata which is a counterpart of sticker systems, namely Watson-Crick automata, is finite automata which can scan the double-stranded tapes of DNA strings using the complimentary relation. The properties of groups have been extended for the recognition of finite automata over groups. In this paper, two variants of automata, modified deterministic finite automata and modified deterministic Watson-Crick automata are used in the study of Abelian groups. Moreover, the relation between finite automata diagram over Abelian groups and the Cayley table is introduced. In addition, some properties of Abelian groups are presented in terms of automata.
Lattice-gas model for active vesicle transport by molecular motors with opposite polarities
NASA Astrophysics Data System (ADS)
Muhuri, Sudipto; Pagonabarraga, Ignacio
2010-08-01
We introduce a multispecies lattice-gas model for motor protein driven collective cargo transport on cellular filaments. We use this model to describe and analyze the collective motion of interacting vesicle cargos being carried by oppositely directed molecular motors, moving on a single biofilament. Building on a totally asymmetric exclusion process to characterize the motion of the interacting cargos, we allow for mass exchange with the environment, input, and output at filament boundaries and focus on the role of interconversion rates and how they affect the directionality of the net cargo transport. We quantify the effect of the various different competing processes in terms of nonequilibrium phase diagrams. The interplay of interconversion rates, which allow for flux reversal and evaporation-deposition processes, introduces qualitatively unique features in the phase diagrams. We observe regimes of three-phase coexistence, the possibility of phase re-entrance, and a significant flexibility in how the different phase boundaries shift in response to changes in control parameters. The moving steady-state solutions of this model allows for different possibilities for the spatial distribution of cargo vesicles, ranging from homogeneous distribution of vesicles to polarized distributions, characterized by inhomogeneities or shocks. Current reversals due to internal regulation emerge naturally within the framework of this model. We believe that this minimal model will clarify the understanding of many features of collective vesicle transport, apart from serving as the basis for building more exact quantitative models for vesicle transport relevant to various in vivo situations.
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.
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.
Actin Automata: Phenomenology and Localizations
NASA Astrophysics Data System (ADS)
Adamatzky, Andrew; Mayne, Richard
Actin is a globular protein which forms long filaments in the eukaryotic cytoskeleton, whose roles in cell function include structural support, contractile activity to intracellular signaling. We model actin filaments as two chains of one-dimensional binary-state semi-totalistic automaton arrays to describe hypothetical signaling events therein. Each node of the actin automaton takes state "0" (resting) or "1" (excited) and updates its state in discrete time depending on its neighbor's states. We analyze the complete rule space of actin automata using integral characteristics of space-time configurations generated by these rules and compute state transition rules that support traveling and mobile localizations. Approaches towards selection of the localization supporting rules using the global characteristics are outlined. We find that some properties of actin automata rules may be predicted using Shannon entropy, activity and incoherence of excitation between the polymer chains. We also show that it is possible to infer whether a given rule supports traveling or stationary localizations by looking at ratios of excited neighbors that are essential for generations of the localizations. We conclude by applying biomolecular hypotheses to this model and discuss the significance of our findings in context with cell signaling and emergent behavior in cellular computation.
High-performance multiprocessor architecture for a 3-D lattice gas model
NASA Technical Reports Server (NTRS)
Lee, F.; Flynn, M.; Morf, M.
1991-01-01
The lattice gas method has recently emerged as a promising discrete particle simulation method in areas such as fluid dynamics. We present a very high-performance scalable multiprocessor architecture, called ALGE, proposed for the simulation of a realistic 3-D lattice gas model, Henon's 24-bit FCHC isometric model. Each of these VLSI processors is as powerful as a CRAY-2 for this application. ALGE is scalable in the sense that it achieves linear speedup for both fixed and increasing problem sizes with more processors. The core computation of a lattice gas model consists of many repetitions of two alternating phases: particle collision and propagation. Functional decomposition by symmetry group and virtual move are the respective keys to efficient implementation of collision and propagation.
Synchronization of Regular Automata
NASA Astrophysics Data System (ADS)
Caucal, Didier
Functional graph grammars are finite devices which generate the class of regular automata. We recall the notion of synchronization by grammars, and for any given grammar we consider the class of languages recognized by automata generated by all its synchronized grammars. The synchronization is an automaton-related notion: all grammars generating the same automaton synchronize the same languages. When the synchronizing automaton is unambiguous, the class of its synchronized languages forms an effective boolean algebra lying between the classes of regular languages and unambiguous context-free languages. We additionally provide sufficient conditions for such classes to be closed under concatenation and its iteration.
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 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.
Implementation and Performance of a Binary Lattice Gas Algorithm on Parallel Processor Systems
NASA Astrophysics Data System (ADS)
Hayot, F.; Mandal, M.; Sadayappan, P.
1989-02-01
We study the performance of a lattice gas binary algorithm on a "real arithmetic" machine, a 32 processor INTEL iPSC hypercube. The implementation is based on so-called multi-spin coding techniques. From the measured performance we extrapolate to larger and more powerful parallel systems. Comparisons are made with "bit" machines, such as the parallel Connection Machine.
Lattice gas dynamics: application to driven vortices in two dimensional superconductors.
Gotcheva, Violeta; Wang, Albert T J; Teitel, S
2004-06-18
A continuous time Monte Carlo lattice gas dynamics is developed to model driven steady states of vortices in two dimensional superconducting networks. Dramatic differences are found when compared to a simpler Metropolis dynamics. Subtle finite size effects are found at low temperature, with a moving smectic that becomes unstable to an anisotropic liquid on sufficiently large length scales.
Weighted Automata and Weighted Logics
NASA Astrophysics Data System (ADS)
Droste, Manfred; Gastin, Paul
In automata theory, a fundamental result of Büchi and Elgot states that the recognizable languages are precisely the ones definable by sentences of monadic second order logic. We will present a generalization of this result to the context of weighted automata. We develop syntax and semantics of a quantitative logic; like the behaviors of weighted automata, the semantics of sentences of our logic are formal power series describing ‘how often’ the sentence is true for a given word. Our main result shows that if the weights are taken in an arbitrary semiring, then the behaviors of weighted automata are precisely the series definable by sentences of our quantitative logic. We achieve a similar characterization for weighted Büchi automata acting on infinite words, if the underlying semiring satisfies suitable completeness assumptions. Moreover, if the semiring is additively locally finite or locally finite, then natural extensions of our weighted logic still have the same expressive power as weighted automata.
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.
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.
A lattice-gas model for alkali-metal fullerides: body-centred-cubic structure
NASA Astrophysics Data System (ADS)
Szabó, György; Udvardi, László
1998-05-01
A Coulomb lattice-gas model with a host-lattice screening mechanism is adapted to describe the ordering phenomena in alkali-metal fullerides of body-centred-cubic structure. It is assumed that the electric charge of an alkali ion residing at a tetrahedral interstitial site is completely screened by its first-neighbour 0953-8984/10/19/009/img5 molecules. The electronic energy of the 0953-8984/10/19/009/img6 ion is also taken into consideration as a charged spherical shell. By means of these assumptions an effective (short-range) pair interaction between two alkali ions is obtained. The resultant lattice-gas model is analysed by using two- and six-sublattice mean-field approximations. The thermodynamic properties are summarized in phase diagrams for different shell radii.
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.
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
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
Uniform and Multi-Grid Modeling of Acoustic Wave Propagation With Cellular Automaton Techniques
2013-03-01
J. Acoustique, vol. 43, no. 30, pp. 223–287, 1992. [8] B. A., “Von Neumann’s self-reproducing automata ,” In Essays on Cellular Automata , pp. 3–64...1970. [9] A. Ilachinski, “ Cellular automata ,” in Cellular Automata A Discrete Universe, New Jersey, World Scientific Publishing Co. Pte. Ltd...2001, p. 5. [10] L. Villar and A. Souza, “ Cellular automata models for general traffic conditions on a line,” Physica A, vol. 211, pp. 84–92, 1994
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.
Multipebble Simulations for Alternating Automata
NASA Astrophysics Data System (ADS)
Clemente, Lorenzo; Mayr, Richard
We study generalized simulation relations for alternating Büchi automata (ABA), as well as alternating finite automata. Having multiple pebbles allows the Duplicator to "hedge her bets" and delay decisions in the simulation game, thus yielding a coarser simulation relation. We define (k 1,k 2)-simulations, with k 1/k 2 pebbles on the left/right, respectively. This generalizes previous work on ordinary simulation (i.e., (1,1)-simulation) for nondeterministic Büchi automata (NBA)[4] in and ABA in [5], and (1,k)-simulation for NBA in [3].
Cellular Automata Models of Ring Dynamics
NASA Astrophysics Data System (ADS)
Gravner, Janko
This paper describes three models arising from the theory of excitable media, whose primary visual feature are expanding rings of excitation. Rigorous mathematical results and experimental/computational issues are both addressed. We start with the much-studied Greenberg-Hastings model (GHM) in which the rings are very short-lived, but they do have a transient percolation property. By contrast, in the model we call annihilating nested rings (ANR), excitation centers only gradually lose strength, i.e., each time they become inactive (and then stay so forever) with a fixed probability; we show how the long-term global connectivity properties of the set of excited sites undergo a phase transition. Second part of the paper is devoted to digital boiling (DB) in which new rings spontaneously appear at rested sites with a positive probability. We focus on such (related) issues as convergence to equilibrium, equilibrium excitation level and success of the basic coupling.
Cellular automata models of ring dynamics
Gravner, J.
1996-12-01
This paper describes three models arising from the theory of excitable media, whose primary visual feature are expanding rings of excitation. Rigorous mathematical results and experimental/computational issues are both addressed. We start with the much-studied Greenberg-Hastings model (GHM) in which the rings are very short-lived, but they do have a transient percolation property. By contrast, in the model we call annihilating nested rings (ANR), excitation centers only gradually lose strength, i.e., each time they become inactive (and then stay so forever) with a fixed probability; we show how the long-term global connectivity properties of the set of excited sites undergo a phase transition. Second part of the paper is devoted to digital boiling (DB) in which new rings spontaneously appear at rested sites with a positive probability. We focus on such (related) issues as convergence to equilibrium, equilibrium excitation level and success of the basic coupling.
Spontaneous formation of large clusters in a lattice gas above the critical point.
Khain, Evgeniy; Khasin, Michael; Sander, Leonard M
2014-12-01
We consider clustering of particles in the lattice gas model above the critical point. We find the probability for large density fluctuations over scales much larger than the correlation length. This fundamental problem is of interest in various biological contexts such as quorum sensing and clustering of motile, adhesive, cancer cells. In the latter case, it may give a clue to the problem of growth of recurrent tumors. We develop a formalism for the analysis of this rare event employing a phenomenological master equation and measuring the transition rates in numerical simulations. The spontaneous clustering is treated in the framework of the eikonal approximation to the master equation.
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.
Spontaneous formation of large clusters in a lattice gas above the critical point
NASA Astrophysics Data System (ADS)
Khain, Evgeniy; Khasin, Michael; Sander, Leonard M.
2014-12-01
We consider clustering of particles in the lattice gas model above the critical point. We find the probability for large density fluctuations over scales much larger than the correlation length. This fundamental problem is of interest in various biological contexts such as quorum sensing and clustering of motile, adhesive, cancer cells. In the latter case, it may give a clue to the problem of growth of recurrent tumors. We develop a formalism for the analysis of this rare event employing a phenomenological master equation and measuring the transition rates in numerical simulations. The spontaneous clustering is treated in the framework of the eikonal approximation to the master equation.
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.
Critical dynamics of the jamming transition in one-dimensional nonequilibrium lattice-gas models.
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.
Efficient Algorithms for Handling Nondeterministic Automata
NASA Astrophysics Data System (ADS)
Vojnar, Tomáš
Finite (word, tree, or omega) automata play an important role in different areas of computer science, including, for instance, formal verification. Often, deterministic automata are used for which traditional algorithms for important operations such as minimisation and inclusion checking are available. However, the use of deterministic automata implies a need to determinise nondeterministic automata that often arise during various computations even when the computations start with deterministic automata. Unfortunately, determinisation is a very expensive step since deterministic automata may be exponentially bigger than the original nondeterministic automata. That is why, it appears advantageous to avoid determinisation and work directly with nondeterministic automata. This, however, brings a need to be able to implement operations traditionally done on deterministic automata on nondeterministic automata instead. In particular, this is the case of inclusion checking and minimisation (or rather reduction of the size of automata). In the talk, we review several recently proposed techniques for inclusion checking on nondeterministic finite word and tree automata as well as Büchi automata. These techniques are based on using the so called antichains, possibly combined with a use of suitable simulation relations (and, in the case of Büchi automata, the so called Ramsey-based or rank-based approaches). Further, we discuss techniques for reducing the size of nondeterministic word and tree automata using quotienting based on the recently proposed notion of mediated equivalences. The talk is based on several common works with Parosh Aziz Abdulla, Ahmed Bouajjani, Yu-Fang Chen, Peter Habermehl, Lisa Kaati, Richard Mayr, Tayssir Touili, Lorenzo Clemente, Lukáš Holík, and Chih-Duo Hong.
Catalytic formation of ammonia: a lattice gas non-thermal Langmuir Hinshelwood mechanism
NASA Astrophysics Data System (ADS)
Khan, K. M.; Ahmad, N.; Albano, E. V.
2001-11-01
The catalytic formation of ammonia synthesis through dimers N 2 and H 2 has been studied through Monte-Carlo simulation via a model based on lattice gas non-thermal Langmuir-Hinshelwood mechanism, which involves the precursor motion of H 2 molecule. The most interesting feature of this model is it yields a steady reactive window, which is separated by continuous and discontinuous irreversible phase transitions. The phase diagram is qualitatively similar to well-known ZGB model. The width of the window depends upon the mobility of precursors. The continuous transition disappears when mobility of precursors is extended to third nearest neighbourhood. The dependence of production rate on partial pressure of hydrogen is predicted by simple mathematical equations in our model. Some more interesting results are observed when reaction between precursors and chemisorbed hydrogen atoms is considered.
A lattice-gas model for alkali-metal fullerides: face-centred-cubic structure
NASA Astrophysics Data System (ADS)
Udvardi, László; Szabó, György
1996-12-01
A lattice-gas model is suggested for describing the ordering phenomena in alkali-metal fullerides of face-centred-cubic structure assuming that the electric charge of alkali ions residing in either octahedral or tetrahedral sites is completely screened by the first-neighbour 0953-8984/8/50/022/img5 molecules. This approximation allows us to derive an effective ion - ion interaction. The van der Waals interaction between the ion and 0953-8984/8/50/022/img5 molecule is characterized by introducing an additional site energy at the tetrahedral sites. This model is investigated by using a three-sublattice mean-field approximation and a simple cluster-variation method. The analysis shows a large variety of phase diagrams as the site energy parameter is changed.
Two-dimensional crystals of Rydberg excitations in a resonantly driven lattice gas
NASA Astrophysics Data System (ADS)
Petrosyan, David
2013-10-01
The competition between resonant optical excitation of Rydberg states of atoms and their strong, long-range van der Waals interaction results in spatial ordering of Rydberg excitations in a two-dimensional lattice gas, as observed in a recent experiment of Schauß [Nature (London)NATUAS0028-083610.1038/nature11596 491, 87 (2012)]. Here we use semiclassical Monte Carlo simulations to obtain stationary states for hundreds of atoms in finite-size lattices. We show the formation of regular spatial structures of Rydberg excitations in a system of increasing size, and find highly sub-Poissonian distribution of the number of Rydberg excitations characterized by a large negative value of the Mandel Q parameter which is nearly independent of the system size.
Effect of disorder on condensation in the lattice gas model on a random graph
NASA Astrophysics Data System (ADS)
Handford, Thomas P.; Dear, Alexander; Pérez-Reche, Francisco J.; Taraskin, Sergei N.
2014-07-01
The lattice gas model of condensation in a heterogeneous pore system, represented by a random graph of cells, is studied using an exact analytical solution. A binary mixture of pore cells with different coordination numbers is shown to exhibit two phase transitions as a function of chemical potential in a certain temperature range. Heterogeneity in interaction strengths is demonstrated to reduce the critical temperature and, for large-enough degreeS of disorder, divides the cells into ones which are either on average occupied or unoccupied. Despite treating the pore space loops in a simplified manner, the random-graph model provides a good description of condensation in porous structures containing loops. This is illustrated by considering capillary condensation in a structural model of mesoporous silica SBA-15.
Nucleation near the eutectic point in a Potts-lattice gas model.
Agarwal, Vishal; Peters, Baron
2014-02-28
We use the Potts-lattice gas model to study nucleation at and near the eutectic composition. We use rare-event methods to compute the free energy landscape for the competing nucleation products, and short trajectories at the barrier top to obtain prefactors. We introduce a procedure to tune the frequency of semigrand Monte Carlo moves so that the dynamics of a small closed system roughly resemble those of an infinite system. The non-dimensionalized nucleation rates follow trends as predicted by the classical nucleation theory. Finally, we develop corrections that convert free energy surfaces from closed (canonical) simulations into free energy surfaces from open (semigrand) simulations. The new corrections extend earlier corrections to now address situations like nucleation at the eutectic point where two products nucleate competitively.
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.
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.
Study of the critical behavior of the driven lattice gas model with limited nonequilibrium dynamics
NASA Astrophysics Data System (ADS)
Saracco, Gustavo P.; Rubio Puzzo, M. Leticia; Bab, Marisa A.
2017-02-01
In this paper the nonequilibrium critical behavior is investigated using a variant of the well-known two-dimensional driven lattice gas (DLG) model, called modified driven lattice gas (MDLG). In this model, the application of the external field is regulated by a parameter p ɛ [ 0 , 1 ] in such a way that if p = 0, the field is not applied, and it becomes the Ising model, while if p = 1, the DLG model is recovered. The behavior of the model is investigated for several values of p by studying the dynamic evolution of the system within the short-time regime in the neighborhood of a phase transition. It is found that the system experiences second-order phase transitions in all the interval of p for the density of particles ρ = 0.5. The determined critical temperatures Tc(p) are greater than the critical temperature of the Ising model TcI, and increase with p up to the critical temperature of the DLG model in the limit of infinite driving fields. The dependence of Tc(p) on p is compatible with a power-law behavior whose exponent is ψ = 0.27(3) . Furthermore, the complete set of the critical and the anisotropic exponents is estimated. For the smallest value of p, the dynamics and β exponents are close to that calculated for the Ising model, and the anisotropic exponent Δ is near zero. As p is increased, the exponents and Δ change, meaning that the anisotropy effects increase. For the largest value investigated, the set of exponents approaches to that reported by the most recent theoretical framework developed for the DLG model.
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.
DTIC Information for AFOSR Task 2304CP Lattice-Gas Theory and Computation for Complex Fluid Dynamics
1997-11-06
by ANSI Std Z39-18 ifested sound waves, surprising fluid-like behavior given the model’s simplicity and severe spacetime discretization. The transport...the integer lattice-gas: (1) is exactly computed on a discrete spacetime lattice (all the additive con- served quantities, e.g. mass and momentum, are
Algebraic Systems and Pushdown Automata
NASA Astrophysics Data System (ADS)
Petre, Ion; Salomaa, Arto
We concentrate in this chapter on the core aspects of algebraic series, pushdown automata, and their relation to formal languages. We choose to follow here a presentation of their theory based on the concept of properness. We introduce in Sect. 2 some auxiliary notions and results needed throughout the chapter, in particular the notions of discrete convergence in semirings and C-cycle free infinite matrices. In Sect. 3 we introduce the algebraic power series in terms of algebraic systems of equations. We focus on interconnections with context-free grammars and on normal forms. We then conclude the section with a presentation of the theorems of Shamir and Chomsky-Schützenberger. We discuss in Sect. 4 the algebraic and the regulated rational transductions, as well as some representation results related to them. Section 5 is dedicated to pushdown automata and focuses on the interconnections with classical (non-weighted) pushdown automata and on the interconnections with algebraic systems. We then conclude the chapter with a brief discussion of some of the other topics related to algebraic systems and pushdown automata.
Solution of an associating lattice-gas model with density anomaly on a Husimi lattice.
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.
``SAFFMAN-TAYLOR'' Finger in 2d Parallel Viscous: BGK Lattice Gas Simulations
NASA Astrophysics Data System (ADS)
Salin, Dominique; Rakotomalala, Nicole; Watzky, Philippe
1996-11-01
We study the displacement of miscible fluids between two parallel plates for different values of the Peclet number Pe and of the viscosity ratio M. The full Navier-Stokes problem is addressed. We use the BGK lattice gas method, which is well suited for miscible fluids and allows to introduce molecular diffusion at the microscopic scale of the lattice. This numerical experiment leads to a symmetric concentration profile about the middle of the gap between the plates. At Pe numbers of the order of 1, mixing involves diffusion and advection in the flow direction. At large Pe, the fluids do not mix and an interface between them can be defined. Moreover, above M ~ 10, the interface becomes a well defined finger, the reduced width of which tends to λ_∞=0.56 at large values of M. Assuming that miscible fluids at high Pe numbers are similar to immiscible fluids at high capillary numbers, we find the analytical shape of the finger, using an extrapolation of the Reinelt-Saffman calculations for a Stokes immiscible flow. Surprisingly, the result is that our finger can be deduced from the celebrated Saffman-Taylor' s one, obtained in a potential flow, by a streching in the flow direction by a numerical factor of 2.125.