Simulation of deformations in magnetic media by the movable cellular automata method
NASA Astrophysics Data System (ADS)
Usachev, Victor V.; Andriushchenko, Petr D.; Afremov, Leonid L.
2015-09-01
A deformable model of the magnetic medium is considered in the research paper. Simulating algorithms of the impact of the external magnetic field on the deformation of the magnetic medium have been developed on the basis of the movable cellular automata (MCA) method.
Probabilistic cellular automata.
Agapie, Alexandru; Andreica, Anca; Giuclea, Marius
2014-09-01
Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case-connecting the probability of a configuration in the stationary distribution to its number of zero-one borders-the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata. PMID:24999557
Predictability in cellular automata.
Agapie, Alexandru; Andreica, Anca; Chira, Camelia; Giuclea, Marius
2014-01-01
Modelled as finite homogeneous Markov chains, probabilistic cellular automata with local transition probabilities in (0, 1) always posses a stationary distribution. This result alone is not very helpful when it comes to predicting the final configuration; one needs also a formula connecting the probabilities in the stationary distribution to some intrinsic feature of the lattice configuration. Previous results on the asynchronous cellular automata have showed that such feature really exists. It is the number of zero-one borders within the automaton's binary configuration. An exponential formula in the number of zero-one borders has been proved for the 1-D, 2-D and 3-D asynchronous automata with neighborhood three, five and seven, respectively. We perform computer experiments on a synchronous cellular automaton to check whether the empirical distribution obeys also that theoretical formula. The numerical results indicate a perfect fit for neighbourhood three and five, which opens the way for a rigorous proof of the formula in this new, synchronous case. PMID:25271778
NASA Astrophysics Data System (ADS)
Bagnoli, Franco; Rechtman, Raúl; El Yacoubi, Samira
2012-12-01
We study the problem of master-slave synchronization and control of totalistic cellular automata. The synchronization mechanism is that of setting a fraction of sites of the slave system equal to those of the master one (pinching synchronization). The synchronization observable is the distance between the two configurations. We present three control strategies that exploit local information (the number of nonzero first-order Boolean derivatives) in order to choose the sites to be synchronized. When no local information is used, we speak of simple pinching synchronization. We find the critical properties of control and discuss the best control strategy compared with simple synchronization.
NASA Astrophysics Data System (ADS)
Porod, Wolfgang; Lent, Craig S.; Bernstein, Gary H.
1994-06-01
The Notre Dame group has developed a new paradigm for ultra-dense and ultra-fast information processing in nanoelectronic systems. These Quantum Cellular Automata (QCA's) are the first concrete proposal for a technology based on arrays of coupled quantum dots. The basic building block of these cellular arrays is the Notre Dame Logic Cell, as it has been called in the literature. The phenomenon of Coulomb exclusion, which is a synergistic interplay of quantum confinement and Coulomb interaction, leads to a bistable behavior of each cell which makes possible their use in large-scale cellular arrays. The physical interaction between neighboring cells has been exploited to implement logic functions. New functionality may be achieved in this fashion, and the Notre Dame group invented a versatile majority logic gate. In a series of papers, the feasibility of QCA wires, wire crossing, inverters, and Boolean logic gates was demonstrated. A major finding is that all logic functions may be integrated in a hierarchial fashion which allows the design of complicated QCA structures. The most complicated system which was simulated to date is a one-bit full adder consisting of some 200 cells. In addition to exploring these new concepts, efforts are under way to physically realize such structures both in semiconductor and metal systems. Extensive modeling work of semiconductor quantum dot structures has helped identify optimum design parameters for QCA experimental implementations.
Global properties of cellular automata
Jen, E.
1986-04-01
Cellular automata are discrete mathematical systems that generate diverse, often complicated, behavior using simple deterministic rules. Analysis of the local structure of these rules makes possible a description of the global properties of the associated automata. A class of cellular automata that generate infinitely many aperoidic temporal sequences is defined,a s is the set of rules for which inverses exist. Necessary and sufficient conditions are derived characterizing the classes of ''nearest-neighbor'' rules for which arbitrary finite initial conditions (i) evolve to a homogeneous state; (ii) generate at least one constant temporal sequence.
Adaptive stochastic cellular automata: Applications
NASA Astrophysics Data System (ADS)
Qian, S.; Lee, Y. C.; Jones, R. D.; Barnes, C. W.; Flake, G. W.; O'Rourke, M. K.; Lee, K.; Chen, H. H.; Sun, G. Z.; Zhang, Y. Q.; Chen, D.; Giles, C. L.
1990-09-01
The stochastic learning cellular automata model has been applied to the problem of controlling unstable systems. Two example unstable systems studied are controlled by an adaptive stochastic cellular automata algorithm with an adaptive critic. The reinforcement learning algorithm and the architecture of the stochastic CA controller are presented. Learning to balance a single pole is discussed in detail. Balancing an inverted double pendulum highlights the power of the stochastic CA approach. The stochastic CA model is compared to conventional adaptive control and artificial neural network approaches.
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…
Quantum cellular automata without particles
NASA Astrophysics Data System (ADS)
Meyer, David A.; Shakeel, Asif
2016-01-01
Quantum cellular automata (QCA) constitute space and time homogeneous discrete models for quantum field theories (QFTs). Although QFTs are defined without reference to particles, computations are done in terms of Feynman diagrams, which are explicitly interpreted in terms of interacting particles. Similarly, the easiest QCA to construct are quantum lattice gas automata (QLGA). A natural question then is, which QCA are not QLGA? Here we construct a nontrivial example of such a QCA; it provides a simple model in 1 +1 dimensions with no particle interpretation at the scale where the QCA dynamics are homogeneous.
Xtoys: Cellular automata on xwindows
Creutz, M.
1995-08-15
Xtoys is a collection of xwindow programs for demonstrating simulations of various statistical models. Included are xising, for the two dimensional Ising model, xpotts, for the q-state Potts model, xautomalab, for a fairly general class of totalistic cellular automata, xsand, for the Bak-Tang-Wiesenfield model of self organized criticality, and xfires, a simple forest fire simulation. The programs should compile on any machine supporting xwindows.
Irregular Cellular Learning Automata.
Esnaashari, Mehdi; Meybodi, Mohammad Reza
2015-08-01
Cellular learning automaton (CLA) is a recently introduced model that combines cellular automaton (CA) and learning automaton (LA). The basic idea of CLA is to use LA to adjust the state transition probability of stochastic CA. This model has been used to solve problems in areas such as channel assignment in cellular networks, call admission control, image processing, and very large scale integration placement. In this paper, an extension of CLA called irregular CLA (ICLA) is introduced. This extension is obtained by removing the structure regularity assumption in CLA. Irregularity in the structure of ICLA is needed in some applications, such as computer networks, web mining, and grid computing. The concept of expediency has been introduced for ICLA and then, conditions under which an ICLA becomes expedient are analytically found. PMID:25291810
Universal map for cellular automata
NASA Astrophysics Data System (ADS)
García-Morales, V.
2012-08-01
A universal map is derived for all deterministic 1D cellular automata (CAs) containing no freely adjustable parameters and valid for any alphabet size and any neighborhood range (including non-symmetrical neighborhoods). The map can be extended to an arbitrary number of dimensions and topologies and to arbitrary order in time. Specific CA maps for the famous Conway's Game of Life and Wolfram's 256 elementary CAs are given. An induction method for CAs, based in the universal map, allows mathematical expressions for the orbits of a wide variety of elementary CAs to be systematically derived.
Symmetry analysis of cellular automata
NASA Astrophysics Data System (ADS)
García-Morales, V.
2013-01-01
By means of B-calculus [V. García-Morales, Phys. Lett. A 376 (2012) 2645] a universal map for deterministic cellular automata (CAs) has been derived. The latter is shown here to be invariant upon certain transformations (global complementation, reflection and shift). When constructing CA rules in terms of rules of lower range a new symmetry, “invariance under construction” is uncovered. Modular arithmetic is also reformulated within B-calculus and a new symmetry of certain totalistic CA rules, which calculate the Pascal simplices modulo an integer number p, is then also uncovered.
Aperiodicity in one-dimensional cellular automata
Jen, E.
1990-01-01
Cellular automata are a class of mathematical systems characterized by discreteness (in space, time, and state values), determinism, and local interaction. A certain class of one-dimensional, binary site-valued, nearest-neighbor automata is shown to generate infinitely many aperiodic temporal sequences from arbitrary finite initial conditions on an infinite lattice. The class of automaton rules that generate aperiodic temporal sequences are characterized by a particular form of injectivity in their interaction rules. Included are the nontrivial linear'' automaton rules (that is, rules for which the superposition principle holds); certain nonlinear automata that retain injectivity properties similar to those of linear automata; and a wider subset of nonlinear automata whose interaction rules satisfy a weaker form of injectivity together with certain symmetry conditions. A technique is outlined here that maps this last set of automata onto a linear automaton, and thereby establishes the aperiodicity of their temporal sequences. 12 refs., 3 figs.
Algorithmic crystal chemistry: A cellular automata approach
Krivovichev, S. V.
2012-01-15
Atomic-molecular mechanisms of crystal growth can be modeled based on crystallochemical information using cellular automata (a particular case of finite deterministic automata). In particular, the formation of heteropolyhedral layered complexes in uranyl selenates can be modeled applying a one-dimensional three-colored cellular automaton. The use of the theory of calculations (in particular, the theory of automata) in crystallography allows one to interpret crystal growth as a computational process (the realization of an algorithm or program with a finite number of steps).
Cellular automata to describe seismicity: A review
NASA Astrophysics Data System (ADS)
Jiménez, Abigail
2013-12-01
Cellular Automata have been used in the literature to describe seismicity. We first historically introduce Cellular Automata and provide some important definitions. Then we proceed to review the most important models, most of them being variations of the spring-block model proposed by Burridge and Knopoff, and describe the most important results obtained from them. We discuss the relation with criticality and also describe some models that try to reproduce real data.
Artificial life simulation of self-assembly in bacteriophage by movable finite automata.
Shirayama, Masatoshi; Koshino, Makoto; Hatakeyama, Toyomasa; Kimura, Haruhiko
2004-11-01
This paper presents a model which is based on biological research using the movable finite automata (MFA) on a self-assembly of T4 phage, and exhibits the results of artificial life simulation. In the previous work, Thompson and Goel [Artificial Life, Addison Weley, 1989, pp. 317-340; Biosystems 18 (1985) 23; J. Theor. Biol. 131 (1988) 351] presented the movable finite automata (MFA) which has a capability of moving on finite automata, and simulated on a computer. They were represented individual rectangular boxes, however, the results of simulation was different from real T4 phage. We propose the sphere model as a protein structure, and simulate the self-assembly of the entire structure of the T4 phage on a computer. PMID:15527954
Statistical Mechanics of Surjective Cellular Automata
NASA Astrophysics Data System (ADS)
Kari, Jarkko; Taati, Siamak
2015-09-01
Reversible cellular automata are seen as microscopic physical models, and their states of macroscopic equilibrium are described using invariant probability measures. We establish a connection between the invariance of Gibbs measures and the conservation of additive quantities in surjective cellular automata. Namely, we show that the simplex of shift-invariant Gibbs measures associated to a Hamiltonian is invariant under a surjective cellular automaton if and only if the cellular automaton conserves the Hamiltonian. A special case is the (well-known) invariance of the uniform Bernoulli measure under surjective cellular automata, which corresponds to the conservation of the trivial Hamiltonian. As an application, we obtain results indicating the lack of (non-trivial) Gibbs or Markov invariant measures for "sufficiently chaotic" cellular automata. We discuss the relevance of the randomization property of algebraic cellular automata to the problem of approach to macroscopic equilibrium, and pose several open questions. As an aside, a shift-invariant pre-image of a Gibbs measure under a pre-injective factor map between shifts of finite type turns out to be always a Gibbs measure. We provide a sufficient condition under which the image of a Gibbs measure under a pre-injective factor map is not a Gibbs measure. We point out a potential application of pre-injective factor maps as a tool in the study of phase transitions in statistical mechanical models.
Quantum features of natural cellular automata
NASA Astrophysics Data System (ADS)
Elze, Hans-Thomas
2016-03-01
Cellular automata can show well known features of quantum mechanics, such as a linear rule according to which they evolve and which resembles a discretized version of the Schrödinger equation. This includes corresponding conservation laws. The class of “natural” Hamiltonian cellular automata is based exclusively on integer-valued variables and couplings and their dynamics derives from an Action Principle. They can be mapped reversibly to continuum models by applying Sampling Theory. Thus, “deformed” quantum mechanical models with a finite discreteness scale l are obtained, which for l → 0 reproduce familiar continuum results. We have recently demonstrated that such automata can form “multipartite” systems consistently with the tensor product structures of nonrelativistic many-body quantum mechanics, while interacting and maintaining the linear evolution. Consequently, the Superposition Principle fully applies for such primitive discrete deterministic automata and their composites and can produce the essential quantum effects of interference and entanglement.
Cellular Automata Generalized To An Inferential System
NASA Astrophysics Data System (ADS)
Blower, David J.
2007-11-01
Stephen Wolfram popularized elementary one-dimensional cellular automata in his book, A New Kind of Science. Among many remarkable things, he proved that one of these cellular automata was a Universal Turing Machine. Such cellular automata can be interpreted in a different way by viewing them within the context of the formal manipulation rules from probability theory. Bayes's Theorem is the most famous of such formal rules. As a prelude, we recapitulate Jaynes's presentation of how probability theory generalizes classical logic using modus ponens as the canonical example. We emphasize the important conceptual standing of Boolean Algebra for the formal rules of probability manipulation and give an alternative demonstration augmenting and complementing Jaynes's derivation. We show the complementary roles played in arguments of this kind by Bayes's Theorem and joint probability tables. A good explanation for all of this is afforded by the expansion of any particular logic function via the disjunctive normal form (DNF). The DNF expansion is a useful heuristic emphasized in this exposition because such expansions point out where relevant 0s should be placed in the joint probability tables for logic functions involving any number of variables. It then becomes a straightforward exercise to rely on Boolean Algebra, Bayes's Theorem, and joint probability tables in extrapolating to Wolfram's cellular automata. Cellular automata are seen as purely deductive systems, just like classical logic, which probability theory is then able to generalize. Thus, any uncertainties which we might like to introduce into the discussion about cellular automata are handled with ease via the familiar inferential path. Most importantly, the difficult problem of predicting what cellular automata will do in the far future is treated like any inferential prediction problem.
Cellular automata modeling of weld solidification structure
Dress, W.B.; Zacharia, T.; Radhakrishnan, B.
1993-12-31
The authors explore the use of cellular automata in modeling arc-welding processes. A brief discussion of cellular automata and their previous use in micro-scale solidification simulations is presented. Macro-scale thermal calculations for arc-welding at a thin plate are shown to give good quantitative and qualitative results. Combining the two calculations in a single cellular array provides a realistic simulation of grain growth in a welding process. Results of simulating solidification in a moving melt pool in a poly-crystalline alloy sheet are presented.
Infrared image enhancement using Cellular Automata
NASA Astrophysics Data System (ADS)
Qi, Wei; Han, Jing; Zhang, Yi; Bai, Lian-fa
2016-05-01
Image enhancement is a crucial technique for infrared images. The clear image details are important for improving the quality of infrared images in computer vision. In this paper, we propose a new enhancement method based on two priors via Cellular Automata. First, we directly learn the gradient distribution prior from the images via Cellular Automata. Second, considering the importance of image details, we propose a new gradient distribution error to encode the structure information via Cellular Automata. Finally, an iterative method is applied to remap the original image based on two priors, further improving the quality of enhanced image. Our method is simple in implementation, easy to understand, extensible to accommodate other vision tasks, and produces more accurate results. Experiments show that the proposed method performs better than other methods using qualitative and quantitative measures.
Cellular-automata method for phase unwrapping
Ghiglia, D.C.; Mastin, G.A.; Romero, L.A.
1987-01-01
Research into two-dimensional phase unwrapping has uncovered interesting and troublesome inconsistencies that cause path-dependent results. Cellular automata, which are simple, discrete mathematical systems, offered promise of computation in nondirectional, parallel manner. A cellular automaton was discovered that can unwrap consistent phase data in n dimensions in a path-independent manner and can automatically accommodate noise-induced (pointlike) inconsistencies and arbitrary boundary conditions (region partitioning). For data with regional (nonpointlike) inconsistencies, no phase-unwrapping algorithm will converge, including the cellular-automata approach. However, the automata method permits more simple visualization of the regional inconsistencies. Examples of its behavior on one- and two-dimensional data are presented.
Fuzzy cellular automata models in immunology
NASA Astrophysics Data System (ADS)
Ahmed, E.
1996-10-01
The self-nonself character of antigens is considered to be fuzzy. The Chowdhury et al. cellular automata model is generalized accordingly. New steady states are found. The first corresponds to a below-normal help and suppression and is proposed to be related to autoimmune diseases. The second corresponds to a below-normal B-cell level.
Dynamical Systems Perspective of Wolfram's Cellular Automata
NASA Astrophysics Data System (ADS)
Courbage, M.; Kamiński, B.
2013-01-01
Leon Chua, following Wolfram, devoted a big effort to understand deeply the wealth of complexity of the rules of all elementary one-dimensional cellular automata from the point of view of the nonlinear dynamicist. Here we complete this point of view by a dynamical system perspective, extending them to the limit of infinite number of sites.
Self-reproduction in small cellular automata
NASA Astrophysics Data System (ADS)
Byl, John
1989-01-01
Self-reproduction in cellular automata is discussed with reference to Langton's criteria as to what constitutes genuine self-reproduction. It is found that it is possible to construct self-reproducing structures that are substantially less complex than that presented by Langton.
Benchmark study between FIDAP and a cellular automata code
Akau, R.L.; Stockman, H.W.
1991-01-01
A fluid flow benchmark exercise was conducted to compare results between a cellular automata code and FIDAP. Cellular automata codes are free from gridding constraints, and are generally used to model slow (Reynolds number {approx} 1) flows around complex solid obstacles. However, the accuracy of cellular automata codes at higher Reynolds numbers, where inertial terms are significant, is not well-documented. In order to validate the cellular automata code, two fluids problems were investigated. For both problems, flow was assumed to be laminar, two-dimensional, isothermal, incompressible and periodic. Results showed that the cellular automata code simulated the overall behavior of the flow field. 7 refs., 12 figs.
Additive Cellular Automata and Volume Growth
NASA Astrophysics Data System (ADS)
Ward, Thomas B.
2000-09-01
A class of dynamical systems associated to rings of S-integers in rational function fields is described. General results about these systems give a rather complete description of the well-known dynamics in one-dimensional additive cellular automata with prime alphabet, including simple formulæ for the topological entropy and the number of periodic configurations. For these systems the periodic points are uniformly distributed along some subsequence with respect to the maximal measure, and in particular are dense. Periodic points may be constructed arbitrarily close to a given configuration, and rationality of the dynamical zeta function is characterized. Throughout the emphasis is to place this particular family of cellular automata into the wider context of S-integer dynamical systems, and to show how the arithmetic of rational function fields determines their behaviour. Using a covering space the dynamics of additive cellular automata are related to a form of hyperbolicity in completions of rational function fields. This expresses the topological entropy of the automata directly in terms of volume growth in the covering space.
Cellular automata model for citrus variegated chlorosis.
Martins, M L; Ceotto, G; Alves, S G; Bufon, C C; Silva, J M; Laranjeira, F F
2000-11-01
A cellular automata model is proposed to analyze the progress of citrus variegated chlorosis epidemics in São Paulo orange plantations. In this model epidemiological and environmental features, such as motility of sharpshooter vectors that perform Lévy flights, level of plant hydric and nutritional stress, and seasonal climatic effects, are included. The observed epidemic data were quantitatively reproduced by the proposed model on varying the parameters controlling vector motility, plant stress, and initial population of diseased plants. PMID:11102058
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.
Configurable Cellular Automata for Pseudorandom Number Generation
NASA Astrophysics Data System (ADS)
Quieta, Marie Therese; Guan, Sheng-Uei
This paper proposes a generalized structure of cellular automata (CA) — the configurable cellular automata (CoCA). With selected properties from programmable CA (PCA) and controllable CA (CCA), a new approach to cellular automata is developed. In CoCA, the cells are dynamically reconfigured at run-time via a control CA. Reconfiguration of a cell simply means varying the properties of that cell with time. Some examples of properties to be reconfigured are rule selection, boundary condition, and radius. While the objective of this paper is to propose CoCA as a new CA method, the main focus is to design a CoCA that can function as a good pseudorandom number generator (PRNG). As a PRNG, CoCA can be a suitable candidate as it can pass 17 out of 18 Diehard tests with 31 cells. CoCA PRNG's performance based on Diehard test is considered superior over other CA PRNG works. Moreover, CoCA opens new rooms for research not only in the field of random number generation, but in modeling complex systems as well.
Astrobiological complexity with probabilistic cellular automata.
Vukotić, Branislav; Ćirković, Milan M
2012-08-01
The search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling the astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous space of the input parameters. We perform a simple clustering analysis of typical astrobiological histories with "Copernican" choice of input parameters and discuss the relevant boundary conditions of practical importance for planning and guiding empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches. PMID:22832998
Astrobiological Complexity with Probabilistic Cellular Automata
NASA Astrophysics Data System (ADS)
Vukotić, Branislav; Ćirković, Milan M.
2012-08-01
The search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling the astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous space of the input parameters. We perform a simple clustering analysis of typical astrobiological histories with "Copernican" choice of input parameters and discuss the relevant boundary conditions of practical importance for planning and guiding empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.
Nonsynchronous updating in the multiverse of cellular automata.
Reia, Sandro M; Kinouchi, Osame
2015-04-01
In this paper we study updating effects on cellular automata rule space. We consider a subset of 6144 order-3 automata from the space of 262144 bidimensional outer-totalistic rules. We compare synchronous to asynchronous and sequential updatings. Focusing on two automata, we discuss how update changes destroy typical structures of these rules. Besides, we show that the first-order phase transition in the multiverse of synchronous cellular automata, revealed with the use of a recently introduced control parameter, seems to be robust not only to changes in update schema but also to different initial densities. PMID:25974442
Nonsynchronous updating in the multiverse of cellular automata
NASA Astrophysics Data System (ADS)
Reia, Sandro M.; Kinouchi, Osame
2015-04-01
In this paper we study updating effects on cellular automata rule space. We consider a subset of 6144 order-3 automata from the space of 262144 bidimensional outer-totalistic rules. We compare synchronous to asynchronous and sequential updatings. Focusing on two automata, we discuss how update changes destroy typical structures of these rules. Besides, we show that the first-order phase transition in the multiverse of synchronous cellular automata, revealed with the use of a recently introduced control parameter, seems to be robust not only to changes in update schema but also to different initial densities.
SELF-ORGANIZED CRITICALITY AND CELLULAR AUTOMATA
CREUTZ,M.
2007-01-01
Cellular automata provide a fascinating class of dynamical systems based on very simple rules of evolution yet capable of displaying highly complex behavior. These include simplified models for many phenomena seen in nature. Among other things, they provide insight into self-organized criticality, wherein dissipative systems naturally drive themselves to a critical state with important phenomena occurring over a wide range of length and the scales. This article begins with an overview of self-organized criticality. This is followed by a discussion of a few examples of simple cellular automaton systems, some of which may exhibit critical behavior. Finally, some of the fascinating exact mathematical properties of the Bak-Tang-Wiesenfeld sand-pile model [1] are discussed.
Weyl, Dirac and Maxwell Quantum Cellular Automata
NASA Astrophysics Data System (ADS)
Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo; Tosini, Alessandro
2015-10-01
Recent advances on quantum foundations achieved the derivation of free quantum field theory from general principles, without referring to mechanical notions and relativistic invariance. From the aforementioned principles a quantum cellular automata (QCA) theory follows, whose relativistic limit of small wave-vector provides the free dynamics of quantum field theory. The QCA theory can be regarded as an extended quantum field theory that describes in a unified way all scales ranging from an hypothetical discrete Planck scale up to the usual Fermi scale. The present paper reviews the automaton theory for the Weyl field, and the composite automata for Dirac and Maxwell fields. We then give a simple analysis of the dynamics in the momentum space in terms of a dispersive differential equation for narrowband wave-packets. We then review the phenomenology of the free-field automaton and consider possible visible effects arising from the discreteness of the framework. We conclude introducing the consequences of the automaton dispersion relation, leading to a deformed Lorentz covariance and to possible effects on the thermodynamics of ideal gases.
Complex dynamics of cellular automata rule 119
NASA Astrophysics Data System (ADS)
Chen, Fang-Fang; Chen, Fang-Yue
2009-03-01
In this paper, the dynamical behaviors of cellular automata rule 119 are studied from the viewpoint of symbolic dynamics in the bi-infinite symbolic sequence space Σ2. It is shown that there exists one Bernoulli-measure global attractor of rule 119, which is also the nonwandering set of the rule. Moreover, it is demonstrated that rule 119 is topologically mixing on the global attractor and possesses the positive topological entropy. Therefore, rule 119 is chaotic in the sense of both Li-Yorke and Devaney on the global attractor. It is interesting that rule 119, a member of Wolfram’s class II which was said to be simple as periodic before, actually possesses a chaotic global attractor in Σ2. Finally, it is noted that the method presented in this work is also applicable to studying the dynamics of other rules, especially the 112 Bernoulli-shift rules therein.
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.
Cellular automata based byte error correcting codes over finite fields
NASA Astrophysics Data System (ADS)
Köroğlu, Mehmet E.; Şiap, İrfan; Akın, Hasan
2012-08-01
Reed-Solomon codes are very convenient for burst error correction which occurs frequently in applications, but as the number of errors increase, the circuit structure of implementing Reed-Solomon codes becomes very complex. An alternative solution to this problem is the modular and regular structure of cellular automata which can be constructed with VLSI economically. Therefore, in recent years, cellular automata have became an important tool for error correcting codes. For the first time, cellular automata based byte error correcting codes analogous to extended Reed-Solomon codes over binary fields was studied by Chowdhury et al. [1] and Bhaumik et al. [2] improved the coding-decoding scheme. In this study cellular automata based double-byte error correcting codes are generalized from binary fields to primitive finite fields Zp.
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.
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.
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).
Cellular automata modelling of biomolecular networks dynamics.
Bonchev, D; Thomas, S; Apte, A; Kier, L B
2010-01-01
The modelling of biological systems dynamics is traditionally performed by ordinary differential equations (ODEs). When dealing with intracellular networks of genes, proteins and metabolites, however, this approach is hindered by network complexity and the lack of experimental kinetic parameters. This opened the field for other modelling techniques, such as cellular automata (CA) and agent-based modelling (ABM). This article reviews this emerging field of studies on network dynamics in molecular biology. The basics of the CA technique are discussed along with an extensive list of related software and websites. The application of CA to networks of biochemical reactions is exemplified in detail by the case studies of the mitogen-activated protein kinase (MAPK) signalling pathway, the FAS-ligand (FASL)-induced and Bcl-2-related apoptosis. The potential of the CA method to model basic pathways patterns, to identify ways to control pathway dynamics and to help in generating strategies to fight with cancer is demonstrated. The different line of CA applications presented includes the search for the best-performing network motifs, an analysis of importance for effective intracellular signalling and pathway cross-talk. PMID:20373215
On the Reversibility of 150 Wolfram Cellular Automata
NASA Astrophysics Data System (ADS)
Del Rey, A. Martín; Sánchez, G. Rodríguez
In this paper, the reversibility problem for 150 Wolfram cellular automata is tackled for null boundary conditions. It is explicitly shown that the reversibility depends on the number of cells of the cellular automaton. The inverse cellular automaton for each case is also computed.
Cellular Automata Ideas in Digital Circuits and Switching Theory.
ERIC Educational Resources Information Center
Siwak, Pawel P.
1985-01-01
Presents two examples which illustrate the usefulness of ideas from cellular automata. First, Lee's algorithm is recalled and its cellular nature shown. Then a problem from digraphs, which has arisen from analyzing predecessing configurations in the famous Conway's "game of life," is considered. (Author/JN)
Lempel-Ziv complexity analysis of one dimensional cellular automata.
Estevez-Rams, E; Lora-Serrano, R; Nunes, C A J; Aragón-Fernández, B
2015-12-01
Lempel-Ziv complexity measure has been used to estimate the entropy density of a string. It is defined as the number of factors in a production factorization of a string. In this contribution, we show that its use can be extended, by using the normalized information distance, to study the spatiotemporal evolution of random initial configurations under cellular automata rules. In particular, the transfer information from time consecutive configurations is studied, as well as the sensitivity to perturbed initial conditions. The behavior of the cellular automata rules can be grouped in different classes, but no single grouping captures the whole nature of the involved rules. The analysis carried out is particularly appropriate for studying the computational processing capabilities of cellular automata rules. PMID:26723145
Lempel-Ziv complexity analysis of one dimensional cellular automata
NASA Astrophysics Data System (ADS)
Estevez-Rams, E.; Lora-Serrano, R.; Nunes, C. A. J.; Aragón-Fernández, B.
2015-12-01
Lempel-Ziv complexity measure has been used to estimate the entropy density of a string. It is defined as the number of factors in a production factorization of a string. In this contribution, we show that its use can be extended, by using the normalized information distance, to study the spatiotemporal evolution of random initial configurations under cellular automata rules. In particular, the transfer information from time consecutive configurations is studied, as well as the sensitivity to perturbed initial conditions. The behavior of the cellular automata rules can be grouped in different classes, but no single grouping captures the whole nature of the involved rules. The analysis carried out is particularly appropriate for studying the computational processing capabilities of cellular automata rules.
The 3-dimensional cellular automata for HIV infection
NASA Astrophysics Data System (ADS)
Mo, Youbin; Ren, Bin; Yang, Wencao; Shuai, Jianwei
2014-04-01
The HIV infection dynamics is discussed in detail with a 3-dimensional cellular automata model in this paper. The model can reproduce the three-phase development, i.e., the acute period, the asymptotic period and the AIDS period, observed in the HIV-infected patients in a clinic. We show that the 3D HIV model performs a better robustness on the model parameters than the 2D cellular automata. Furthermore, we reveal that the occurrence of a perpetual source to successively generate infectious waves to spread to the whole system drives the model from the asymptotic state to the AIDS state.
From quantum cellular automata to quantum lattice gases
Meyer, D.A.
1996-12-01
A natural architecture for nanoscale quantum computation is that of a quantum cellular automaton. Motivated by this observation, we begin an investigation of exactly unitary cellular automata. After proving that there can be no nontrivial, homogeneous, local, unitary, scalar cellular automaton in one dimension, we weaken the homogeneity condition and show that there are nontrivial, exactly unitary, partitioning cellular automata. We find a one-parameter family of evolution rules which are best interpreted as those for a one-particle quantum automaton. This model is naturally reformulated as a two component cellular automaton which we demonstrate to limit to the Dirac equation. We describe two generalizations of this automaton, the second of which, to multiple interacting particles, is the correct definition of a quantum lattice gas.
Synchronization of One-Dimensional Stochastically Coupled Cellular Automata
NASA Astrophysics Data System (ADS)
Mrowinski, Maciej J.; Kosinski, Robert A.
In this work the authors study synchronization resulting from the asymmetric stochastic coupling between two one-dimensional chaotic cellular automata and provide a simple analytical model to explain this phenomenon. The authors also study synchronization in a more general case, using sets of rules with a different number of states and different values of Langton's parameter λ.
Return of the Quantum Cellular Automata: Episode VI
NASA Astrophysics Data System (ADS)
Carr, Lincoln D.; Hillberry, Logan E.; Rall, Patrick; Halpern, Nicole Yunger; Bao, Ning; Montangero, Simone
2016-05-01
There are now over 150 quantum simulators or analog quantum computers worldwide. Although exploring quantum phase transitions, many-body localization, and the generalized Gibbs ensemble are exciting and worthwhile endeavors, there are totally untapped directions we have not yet pursued. One of these is quantum cellular automata. In the past a principal goal of quantum cellular automata was to reproduce continuum single particle quantum physics such as the Schrodinger or Dirac equation from simple rule sets. Now that we begin to really understand entanglement and many-body quantum physics at a deeper level, quantum cellular automata present new possibilities. We explore several time evolution schemes on simple spin chains leading to high degrees of quantum complexity and nontrivial quantum dynamics. We explain how the 256 known classical elementary cellular automata reduce to just a few exciting quantum cases. Our analysis tools include mutual information based complex networks as well as more familiar quantifiers like sound speed and diffusion rate. Funded by NSF and AFOSR.
Boolean linear differential operators on elementary cellular automata
NASA Astrophysics Data System (ADS)
Martín Del Rey, Ángel
2014-12-01
In this paper, the notion of boolean linear differential operator (BLDO) on elementary cellular automata (ECA) is introduced and some of their more important properties are studied. Special attention is paid to those differential operators whose coefficients are the ECA with rule numbers 90 and 150.
Quantum dot spin cellular automata for realizing a quantum processor
NASA Astrophysics Data System (ADS)
Bayat, Abolfazl; Creffield, Charles E.; Jefferson, John H.; Pepper, Michael; Bose, Sougato
2015-10-01
We show how single quantum dots, each hosting a singlet-triplet qubit, can be placed in arrays to build a spin quantum cellular automaton. A fast (˜10 ns) deterministic coherent singlet-triplet filtering, as opposed to current incoherent tunneling/slow-adiabatic based quantum gates (operation time ˜300 ns), can be employed to produce a two-qubit gate through capacitive (electrostatic) couplings that can operate over significant distances. This is the coherent version of the widely discussed charge and nano-magnet cellular automata, and would increase speed, reduce dissipation, and perform quantum computation while interfacing smoothly with its classical counterpart. This combines the best of two worlds—the coherence of spin pairs known from quantum technologies, and the strength and range of electrostatic couplings from the charge-based classical cellular automata. Significantly our system has zero electric dipole moment during the whole operation process, thereby increasing its charge dephasing time.
Extended Self Organised Criticality in Asynchronously Tuned Cellular Automata
NASA Astrophysics Data System (ADS)
Gunji, Yukio-Pegio
2014-12-01
Systems at a critical point in phase transitions can be regarded as being relevant to biological complex behaviour. Such a perspective can only result, in a mathematical consistent manner, from a recursive structure. We implement a recursive structure based on updating by asynchronously tuned elementary cellular automata (AT ECA), and show that a large class of elementary cellular automata (ECA) can reveal critical behavior due to the asynchronous updating and tuning.We show that the obtained criticality coincides with the criticality in phase transitions of asynchronous ECA with respect to density decay, and that multiple distributed ECAs, synchronously updated, can emulate critical behavior in AT ECA. Our approach draws on concepts and tools from category and set theory, in particular on "adjunction dualities" of pairs of adjoint functors.
Construction of living cellular automata using the Physarum plasmodium
NASA Astrophysics Data System (ADS)
Shirakawa, Tomohiro; Sato, Hiroshi; Ishiguro, Shinji
2015-04-01
The plasmodium of Physarum polycephalum is a unicellular and multinuclear giant amoeba that has an amorphous cell body. To clearly observe how the plasmodium makes decisions in its motile and exploratory behaviours, we developed a new experimental system to pseudo-discretize the motility of the organism. In our experimental space that has agar surfaces arranged in a two-dimensional lattice, the continuous and omnidirectional movement of the plasmodium was limited to the stepwise one, and the direction of the locomotion was also limited to four neighbours. In such an experimental system, a cellular automata-like system was constructed using the living cell. We further analysed the exploratory behaviours of the plasmodium by duplicating the experimental results in the simulation models of cellular automata. As a result, it was revealed that the behaviours of the plasmodium are not reproduced by only local state transition rules; and for the reproduction, a kind of historical rule setting is needed.
Identifying patterns from one-rule-firing cellular automata.
Shin, Jae Kyun
2011-01-01
A new firing scheme for cellular automata in which only one rule is fired at a time produces myriad patterns. In addition to geometric patterns, natural patterns such as flowers and snow crystals were also generated. This study proposes an efficient method identifying the patterns using a minimal number of digits. Complexity of the generated patterns is discussed in terms of the shapes and colors of the patterns. PMID:21087150
A full computation-relevant topological dynamics classification of elementary cellular automata
NASA Astrophysics Data System (ADS)
Schüle, Martin; Stoop, Ruedi
2012-12-01
Cellular automata are both computational and dynamical systems. We give a complete classification of the dynamic behaviour of elementary cellular automata (ECA) in terms of fundamental dynamic system notions such as sensitivity and chaoticity. The "complex" ECA emerge to be sensitive, but not chaotic and not eventually weakly periodic. Based on this classification, we conjecture that elementary cellular automata capable of carrying out complex computations, such as needed for Turing-universality, are at the "edge of chaos."
Cellular automata method for phase unwrapping
Ghiglia, D.C.; Mastin, G.A.
1985-10-01
Research into phase unwrapping has led to the discovery of a cellular automaton that can unwrap phase in one- and two-dimensions. The extremely interesting behavior of the automaton and the aesthetically pleasing structure that evolves from repeated iterates will be presented.
Analytical Solution of Traffic Cellular Automata Model
NASA Astrophysics Data System (ADS)
Lo, Shih-Ching; Hsu, Chia-Hung
2009-08-01
Complex traffic system seems to be simulated successfully by cellular automaton (CA) models. Various models are developed to understand single-lane traffic, multilane traffic, lane-changing behavior and network traffic situations. However, the result of CA simulation can only be obtained after massive microscopic computation. Although, the mean field theory (MFT) has been studied to be the approximation of CA model, the MFT can only applied to the simple CA rules or small value of parameters. In this study, we simulate traffic flow by the NaSch model under different combination of parameters, which are maximal speed, dawdling probability and density. After that, the position of critical density, the slope of free-flow and congested regime are observed and modeled due to the simulated data. Finally, the coefficients of the model will be calibrated by the simulated data and the analytical solution of traffic CA is obtained.
Cellular Automata with network incubation in information technology diffusion
NASA Astrophysics Data System (ADS)
Guseo, Renato; Guidolin, Mariangela
2010-06-01
Innovation diffusion of network goods determines direct network externalities that depress sales for long periods and delay full benefits. We model this effect through a multiplicative dynamic market potential driven by a latent individual threshold embedded in a special Cellular Automata representation. The corresponding mean field approximation of its aggregate version is a Riccati equation with a closed form solution. This allows the detection of a change-point time separating an incubation period from a subsequent take-off due to a collective threshold (critical mass). Weighted nonlinear least squares are the main inferential methodology. An application is analysed with reference to USA fax machine diffusion.
From deterministic cellular automata to coupled map lattices
NASA Astrophysics Data System (ADS)
García-Morales, Vladimir
2016-07-01
A general mathematical method is presented for the systematic construction of coupled map lattices (CMLs) out of deterministic cellular automata (CAs). The entire CA rule space is addressed by means of a universal map for CAs that we have recently derived and that is not dependent on any freely adjustable parameters. The CMLs thus constructed are termed real-valued deterministic cellular automata (RDCA) and encompass all deterministic CAs in rule space in the asymptotic limit κ \\to 0 of a continuous parameter κ. Thus, RDCAs generalize CAs in such a way that they constitute CMLs when κ is finite and nonvanishing. In the limit κ \\to ∞ all RDCAs are shown to exhibit a global homogeneous fixed-point that attracts all initial conditions. A new bifurcation is discovered for RDCAs and its location is exactly determined from the linear stability analysis of the global quiescent state. In this bifurcation, fuzziness gradually begins to intrude in a purely deterministic CA-like dynamics. The mathematical method presented allows to get insight in some highly nontrivial behavior found after the bifurcation.
A Programmable Cellular-Automata Polarized Dirac Vacuum
NASA Astrophysics Data System (ADS)
Osoroma, Drahcir S.
2013-09-01
We explore properties of a `Least Cosmological Unit' (LCU) as an inherent spacetime raster tiling or tessellating the unique backcloth of Holographic Anthropic Multiverse (HAM) cosmology as an array of programmable cellular automata. The HAM vacuum is a scale-invariant HD extension of a covariant polarized Dirac vacuum with `bumps' and `holes' typically described by extended electromagnetic theory corresponding to an Einstein energy-dependent spacetime metric admitting a periodic photon mass. The new cosmology incorporates a unique form of M-Theoretic Calabi-Yau-Poincaré Dodecadedral-AdS5-DS5space (PDS) with mirror symmetry best described by an HD extension of Cramer's Transactional Interpretation when integrated also with an HD extension of the de Broglie-Bohm-Vigier causal interpretation of quantum theory. We incorporate a unique form of large-scale additional dimensionality (LSXD) bearing some similarity to that conceived by Randall and Sundrum; and extend the fundamental basis of our model to the Unified Field, UF. A Sagnac Effect rf-pulsed incursive resonance hierarchy is utilized to manipulate and ballistically program the geometric-topological properties of this putative LSXD space-spacetime network. The model is empirically testable; and it is proposed that a variety of new technologies will arise from ballistic programming of tessellated LCU vacuum cellular automata.
Simulation of root forms using cellular automata model
NASA Astrophysics Data System (ADS)
Winarno, Nanang; Prima, Eka Cahya; Afifah, Ratih Mega Ayu
2016-02-01
This research aims to produce a simulation program for root forms using cellular automata model. Stephen Wolfram in his book entitled "A New Kind of Science" discusses the formation rules based on the statistical analysis. In accordance with Stephen Wolfram's investigation, the research will develop a basic idea of computer program using Delphi 7 programming language. To best of our knowledge, there is no previous research developing a simulation describing root forms using the cellular automata model compared to the natural root form with the presence of stone addition as the disturbance. The result shows that (1) the simulation used four rules comparing results of the program towards the natural photographs and each rule had shown different root forms; (2) the stone disturbances prevent the root growth and the multiplication of root forms had been successfully modeled. Therefore, this research had added some stones, which have size of 120 cells placed randomly in the soil. Like in nature, stones cannot be penetrated by plant roots. The result showed that it is very likely to further develop the program of simulating root forms by 50 variations.
Cellular automata and complex dynamics of driven elastic media
Coppersmith, S.N.; Littlewodd, P.B.; Sibani, P.
1995-12-01
Several systems of importance in condensed matter physics can be modelled as an elastic medium in a disordered environment and driven by an external force. In the simplest cases, the equation of motion involves competition between a local non-linear potential (fluctuating in space) and elastic coupling, as well as relaxational (inertialess) dynamics. Despite a simple mathematical description, the interactions between many degrees of freedom lead to the emergence of time and length scales much longer than those set by the microscopic dynamics. Extensive computations have improved the understanding of the behavior of such models, but full solutions of the equations of motion for very large systems are time-consuming and may obscure important physical principles in a massive volume of output. The development of cellular automata models has been crucial, both in conceptual simplification and in allowing the collection of data on many replicas of very large systems. We will discuss how the marriage of cellular automata models and parallel computation on a MasPar MP-1216 computer has helped to elucidate the dynamical properties of these many-degree-of-freedom systems.
Critical Probabilities and Convergence Time of Percolation Probabilistic Cellular Automata
NASA Astrophysics Data System (ADS)
Taggi, Lorenzo
2015-05-01
This paper considers a class of probabilistic cellular automata undergoing a phase transition with an absorbing state. Denoting by the neighbourhood of site , the transition probability is if or otherwise, . For any there exists a non-trivial critical probability that separates a phase with an absorbing state from a fluctuating phase. This paper studies how the neighbourhood affects the value of and provides lower bounds for . Furthermore, by using dynamic renormalization techniques, we prove that the expected convergence time of the processes on a finite space with periodic boundaries grows exponentially (resp. logarithmically) with the system size if (resp. ). This provides a partial answer to an open problem in Toom et al. (Stochastic Cellular Systems: Ergodicity, Memory, Morphogenesis, pp. 1-182. Manchester University Press, Manchester, 1990; Topics in Contemporary Probability and its Applications, pp. 117-157. CRC Press, Boca Raton, 1995).
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.
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.
Cellular automata simulation of medication-induced autoimmune diseases
NASA Astrophysics Data System (ADS)
Stauffer, Dietrich; Proykova, Ana
2004-01-01
We implement the cellular automata model proposed by Stauffer and Weisbuch in 1992 to describe the response of the immune system to antigens in the presence of medications. The model contains two thresholds, θ1 and θ2, suggested by de Boer, Segel, and Perelson to present the minimum field needed to stimulate the proliferation of the receptors and to suppress it, respectively. The influence of the drug is mimicked by increasing the second threshold, thus enhancing the immune response. If this increase is too strong, the immune response is triggered in the whole immune repertoire, causing it to attack the own body. This effect is seen in our simulations to depend both on the ratio of the thresholds and on their absolute values.
Dynamics of HIV infection on 2D cellular automata
NASA Astrophysics Data System (ADS)
Benyoussef, A.; HafidAllah, N. El; ElKenz, A.; Ez-Zahraouy, H.; Loulidi, M.
2003-05-01
We use a cellular automata approach to describe the interactions of the immune system with the human immunodeficiency virus (HIV). We study the evolution of HIV infection, particularly in the clinical latency period. The results we have obtained show the existence of four different behaviours in the plane of death rate of virus-death rate of infected T cell. These regions meet at a critical point, where the virus density and the infected T cell density remain invariant during the evolution of disease. We have introduced two kinds of treatments, the protease inhibitors and the RT inhibitors, in order to study their effects on the evolution of HIV infection. These treatments are powerful in decreasing the density of the virus in the blood and the delay of the AIDS onset.
An image encryption based on elementary cellular automata
NASA Astrophysics Data System (ADS)
Jin, Jun
2012-12-01
This paper presents a new image encryption/decryption scheme. The behavior of a number of elementary cellular automata (ECA) of length 8 with periodic boundary conditions is investigated. It is found in the state-transition diagram that some ECA rules result in state attractors which satisfies basic requirement of the encryption scheme that can perform encrypting function to transform the pixel values. The generation of these attractors depending only on the rule and initial state of the CA, without any additional hardware cost for the implementation, and requires minimized computational resources. Simulation results on some grayscale and color images show that the proposed image encryption method satisfies the properties of confusion and diffusion, execution speed and has perfect information concealing.
Mosquito population dynamics from cellular automata-based simulation
NASA Astrophysics Data System (ADS)
Syafarina, Inna; Sadikin, Rifki; Nuraini, Nuning
2016-02-01
In this paper we present an innovative model for simulating mosquito-vector population dynamics. The simulation consist of two stages: demography and dispersal dynamics. For demography simulation, we follow the existing model for modeling a mosquito life cycles. Moreover, we use cellular automata-based model for simulating dispersal of the vector. In simulation, each individual vector is able to move to other grid based on a random walk. Our model is also capable to represent immunity factor for each grid. We simulate the model to evaluate its correctness. Based on the simulations, we can conclude that our model is correct. However, our model need to be improved to find a realistic parameters to match real data.
An Asynchronous Cellular Automata-Based Adaptive Illumination Facility
NASA Astrophysics Data System (ADS)
Bandini, Stefania; Bonomi, Andrea; Vizzari, Giuseppe; Acconci, Vito
The term Ambient Intelligence refers to electronic environments that are sensitive and responsive to the presence of people; in the described scenario the environment itself is endowed with a set of sensors (to perceive humans or other physical entities such as dogs, bicycles, etc.), interacting with a set of actuators (lights) that choose their actions (i.e. state of illumination) in an attempt improve the overall experience of these users. The model for the interaction and action of sensors and actuators is an asynchronous Cellular Automata (CA) with memory, supporting a self-organization of the system as a response to the presence and movements of people inside it. The paper will introduce the model, as well as an ad hoc user interface for the specification of the relevant parameters of the CA transition rule that determines the overall system behaviour.
Game level layout generation using evolved cellular automata
NASA Astrophysics Data System (ADS)
Pech, Andrew; Masek, Martin; Lam, Chiou-Peng; Hingston, Philip
2016-01-01
Design of level layouts typically involves the production of a set of levels which are different, yet display a consistent style based on the purpose of a particular level. In this paper, a new approach to the generation of unique level layouts, based on a target set of attributes, is presented. These attributes, which are learned automatically from an example layout, are used for the off-line evolution of a set of cellular automata rules. These rules can then be used for the real-time generation of level layouts that meet the target parameters. The approach is demonstrated on a set of maze-like level layouts. Results are presented to show the effect of various CA parameters and rule representation.
Narrow-band oscillations in probabilistic cellular automata.
Puljic, Marko; Kozma, Robert
2008-08-01
Dynamical properties of neural populations are studied using probabilistic cellular automata. Previous work demonstrated the emergence of critical behavior as the function of system noise and density of long-range axonal connections. Finite-size scaling theory identified critical properties, which were consistent with properties of a weak Ising universality class. The present work extends the studies to neural populations with excitatory and inhibitory interactions. It is shown that the populations can exhibit narrow-band oscillations when confined to a range of inhibition levels, with clear boundaries marking the parameter region of prominent oscillations. Phase diagrams have been constructed to characterize unimodal, bimodal, and quadromodal oscillatory states. The significance of these findings is discussed in the context of large-scale narrow-band oscillations in neural tissues, as observed in electroencephalographic and magnetoencephalographic measurements. PMID:18850928
Are nonlinear discrete cellular automata compatible with quantum mechanics?
NASA Astrophysics Data System (ADS)
Elze, Hans-Thomas
2015-07-01
We consider discrete and integer-valued cellular automata (CA). A particular class of which comprises “Hamiltonian CA” with equations of motion that bear similarities to Hamilton's equations, while they present discrete updating rules. The dynamics is linear, quite similar to unitary evolution described by the Schrödinger equation. This has been essential in our construction of an invertible map between such CA and continuous quantum mechanical models, which incorporate a fundamental discreteness scale. Based on Shannon's sampling theory, it leads, for example, to a one-to-one relation between quantum mechanical and CA conservation laws. The important issue of linearity of the theory is examined here by incorporating higher-order nonlinearities into the underlying action. These produce inconsistent nonlocal (in time) effects when trying to describe continuously such nonlinear CA. Therefore, in the present framework, only linear CA and local quantum mechanical dynamics are compatible.
Renormalisation of 2D Cellular Automata with an Absorbing State
NASA Astrophysics Data System (ADS)
Weaver, Iain S.; Prügel-Bennett, Adam
2015-04-01
We describe a real-space renormalisation scheme for non-equilibrium probabilistic cellular automata (PCA) models, and apply it to a two-dimensional binary PCA. An exact renormalisation scheme is rare, and therefore we provide a method for computing the stationary probability distribution of states for such models with which to weight the renormalisation, effectively minimising the error in the scale transformation. While a mean-field approximation is trivial, we use the principle of maximum entropy to incorporate nearest-neighbour spin-correlations in the steady-state probability distribution. In doing so we find the fixed point of the renormalisation is modified by the steady-state approximation order.
Density Effects in Cellular Automata Models of Granular Materials
NASA Astrophysics Data System (ADS)
Baxter, G. W.; Behringer, R. P.
1996-11-01
We have studied density waves in a two dimensional cellular automata model of the gravity-driven flow of ellipsoidal particles through a wedge-shaped hopper(G. W. Baxter and R. P. Behringer, PRA 42), 1017 (1990).. The density variations form above the apex of the hopper and move upward, opposite the grain motion, with a well defined velocity. The waves become more pronounced as they travel. Density waves and alignment of particles are competing effects. Nearest-neighbor interactions which lead to alignment of neighboring grains can destroy the density waves. The relationship of these results to previous studies of density waves in real granular materials will be discussed(G. W. Baxter, R. P. Behringer, T. Fagert, and G. A. Johnson, PRL 62), 2825 (1989)..
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.
Modeling the Sinoatrial Node by Cellular Automata with Irregular Topology
NASA Astrophysics Data System (ADS)
Makowiec, Danuta
The role of irregularity in intercellular connections is studied in the first natural human pacemaker called the sinoatrial node by modeling with the Greenberg-Hastings cellular automata. Facts from modern physiology about the sinoatrial node drive modeling. Heterogeneity between cell connections is reproduced by a rewiring procedure applied to a square lattice. The Greenberg-Hastings rule, representing the intrinsic cellular dynamics, is modified to imitate self-excitation of each pacemaker cell. Moreover, interactions with nearest neighbors are changed to heterogeneous ones by enhancing horizontal connections. Stationary states of the modeled system emerge as self-organized robust oscillatory states. Since the sinoatrial node role relies on a single cell cyclic activity, properties of single cells are studied. It appears that the strength and diversity of cellular oscillations depend directly on properties of intrinsic cellular dynamics. But these oscillations also depend on the underlying topology. Moderate nonuniformity of intercellular connections are found vital for proper function of the sinoatrial node, namely, for producing robust oscillatory states that are able to respond effectively to the autonomic system control.
Evolving cellular automata to perform computations. Final technical report
Crutchfield, J.P.; Mitchell, M.
1998-04-01
The overall goals of the project are to determine the usefulness of genetic algorithms (GAs) in designing spatially extended parallel systems to perform computational tasks and to develop theoretical frameworks both for understanding the computation in the systems evolved by the GA and for understanding the evolutionary process which successful systems are designed. In the original proposal the authors scheduled the first year of the project to be devoted to experimental grounding. During the first year they developed the simulation and graphics software necessary for doing experiments and analysis on one dimensional cellular automata (CAs), and they performed extensive experiments and analysis concerning two computational tasks--density classification and synchronization. Details of these experiments and results, and a list of resulting publications, were given in the 1994--1995 report. The authors scheduled the second year to be devoted to theoretical development. (A third year, to be funded by the National Science Foundation, will be devoted to applications.) Accordingly, most of the effort during the second year was spent on theory, both of GAs and of the CAs that they evolve. A central notion is that of the computational strategy of a CA, which they formalize in terms of domains, particles, and particle interactions. This formalization builds on the computational mechanics framework developed by Crutchfield and Hanson for understanding intrinsic computation in spatially extended dynamical systems. They have made significant progress in the following areas: (1) statistical dynamics of GAs; (2) formalizing particle based computation in cellular automata; and (3) computation in two-dimensional CAs.
Quantum-cellular-automata quantum computing with endohedral fullerenes
NASA Astrophysics Data System (ADS)
Twamley, J.
2003-05-01
We present a scheme to perform universal quantum computation using global addressing techniques as applied to a physical system of endohedrally doped fullerenes. The system consists of an ABAB linear array of group-V endohedrally doped fullerenes. Each molecule spin site consists of a nuclear spin coupled via a hyperfine interaction to an electron spin. The electron spin of each molecule is in a quartet ground state S=3/2. Neighboring molecular electron spins are coupled via a magnetic dipole interaction. We find that an all-electron construction of a quantum cellular automaton is frustrated due to the degeneracy of the electronic transitions. However, we can construct a quantum-cellular-automata quantum computing architecture using these molecules by encoding the quantum information on the nuclear spins while using the electron spins as a local bus. We deduce the NMR and ESR pulses required to execute the basic cellular automaton operation and obtain a rough figure of merit for the number of gate operations per decoherence time. We find that this figure of merit compares well with other physical quantum computer proposals. We argue that the proposed architecture meets well the first four DiVincenzo criteria and we outline various routes toward meeting the fifth criterion: qubit readout.
Rule matrices, degree vectors, and preimages for cellular automata
Jen, E.
1989-01-01
Cellular automata are mathematical systems characterized by discreteness (in space, time, and state values), determinism, and local interaction. Few analytical techniques exist for such systems. The rule matrix and degree vectors of a cellular automaton -- both of which are determined a priori from the function defining the automaton, rather than a posteriori from simulations of its evolution -- are introduced here as tools for understanding certain qualitative features of automaton behavior. The rule matrix represents in convenient form the information contained in an automaton's rule table; the degree vectors are computed from the rule matrix, and reflect the extent to which the system is one-to-one'' versus many-to-one'' on restricted subspaces of the mapping. The rule matrix and degree vectors determine, for example, several aspects of the enumeration and prediction'' of preimages for spatial sequences evolving under the rule, where the preimages of a sequence S are defined to be the set of sequences mapped by the automaton rule onto S. 2 figs., 2 tabs.
1/ fα spectra in elementary cellular automata and fractal signals
NASA Astrophysics Data System (ADS)
Nagler, Jan; Claussen, Jens Christian
2005-06-01
We systematically compute the power spectra of the one-dimensional elementary cellular automata introduced by Wolfram. On the one hand our analysis reveals that one automaton displays 1/f spectra though considered as trivial, and on the other hand that various automata classified as chaotic or complex display no 1/f spectra. We model the results generalizing the recently investigated Sierpinski signal to a class of fractal signals that are tailored to produce 1/fα spectra. From the widespread occurrence of (elementary) cellular automata patterns in chemistry, physics, and computer sciences, there are various candidates to show spectra similar to our results.
Study of hotspot repair using cellular automata method
NASA Astrophysics Data System (ADS)
Nagase, Norimasa; Takeuchi, Kanji; Sakurai, Mitsuo; Itoh, Takahisa; Okada, Tomoyuki
2014-07-01
In advanced semiconductor manufacturing, model-based optical proximity correction is commonly used to compensate for image errors. The final pattern is generated using correction values determined by lithography simulation. Image errors such as patterns with insufficient correction or patterns with excessive correction can be generated. These patterns with errors are called hotspots. Such errors are conventionally detected by lithography simulation of OPC patterns. When a hotspot is detected by lithography simulation, it has to be repaired manually or by repeated use of OPC tool. However, it is difficult to obtain correct pattern for a complicated shape, and the correction procedure may require a significant amount of additional processing. In order to solve this issue, we examine application of cellular automata (CA) method for hotspot correction. It is known that CA method can be used for weather or traffic analysis and prediction. In this report, we studied the CA method for deriving simple hotspot repair rule based on lattice cell-like models for light intensity distribution and OPC patterns. We will report on the results of hotspot correction technique with the OPC pattern using CA method.
A Study on Sequence Generation Powers of Small Cellular Automata
NASA Astrophysics Data System (ADS)
Kamikawa, Naoki; Umeo, Hiroshi
A model of cellular automata (CA) is considered to be a well-studied non-linear model of complex systems in which an infinite one-dimensional array of finite state machines (cells) updates itself in a synchronous manner according to a uniform local rule. A sequence generation problem on the CAs has been studied and many scholars proposed several real-time sequence generation algorithms for a variety of non-regular sequences such as prime, Fibonacci, and {2n|n=1,2,3,...} sequences etc. The paper describes the sequence generation powers of CAs having a small number of states, focusing on the CAs with one, two, and three internal states, respectively. The authors enumerate all of the sequences generated by two-state CAs and present several non-regular sequences that can be generated in real-time by three-state CAs, but not generated by any two-state CA. It is shown that there exists a sequence generation gap among the powers of those small CAs.
Modeling Second-Order Chemical Reactions using Cellular Automata
NASA Astrophysics Data System (ADS)
Hunter, N. E.; Barton, C. C.; Seybold, P. G.; Rizki, M. M.
2012-12-01
Cellular automata (CA) are discrete, agent-based, dynamic, iterated, mathematical computational models used to describe complex physical, biological, and chemical systems. Unlike the more computationally demanding molecular dynamics and Monte Carlo approaches, which use "force fields" to model molecular interactions, CA models employ a set of local rules. The traditional approach for modeling chemical reactions is to solve a set of simultaneous differential rate equations to give deterministic outcomes. CA models yield statistical outcomes for a finite number of ingredients. The deterministic solutions appear as limiting cases for conditions such as a large number of ingredients or a finite number of ingredients and many trials. Here we present a 2-dimensional, probabilistic CA model of a second-order gas phase reaction A + B → C, using a MATLAB basis. Beginning with a random distribution of ingredients A and B, formation of C emerges as the system evolves. The reaction rate can be varied based on the probability of favorable collisions of the reagents A and B. The model permits visualization of the conversion of reagents to products, and allows one to plot concentration vs. time for A, B and C. We test hypothetical reaction conditions such as: limiting reagents, the effects of reaction probabilities, and reagent concentrations on the reaction kinetics. The deterministic solutions of the reactions emerge as statistical averages in the limit of the large number of cells in the array. Modeling results for dynamic processes in the atmosphere will be presented.
A Cellular Automata occupant evacuation model considering gathering behavior
NASA Astrophysics Data System (ADS)
Zhao, Daoliang; Wang, Jinhui; Zhang, Xiaoliang; Wang, Xiaoqun
2015-01-01
A two-dimensional (2D) Cellular Automata (CA) random model is developed to simulate occupant evacuation considering gathering behavior. The movement process from random distribution to gathering state can be simulated based on the map of the position repulsive force. Evacuations with random distribution and gathering distribution are compared. Visual field means object area coverage considered by the individual in the current cell, representing by the radius of visual field, VR. The simulation results with VR = 1 and 2 have little difference while the simulation with VR = 3 can reasonably represent gathering process. When the occupant density is less than 0.64 people/m2, the time of gathering process increases very fast with the increase of density; when the density is larger than 1.28 people/m2, the time of gathering decreases with the increase of density. When the initial density is less than 1.44 people/m2, the evacuation times with random distribution are always less than those with gathering distribution. When the initial density is larger than 1.44 people/m2, the evacuation times with gathering or random distribution are almost the same. Our model can simulate the gathering and evacuation process with more than two rally points. The number and distribution of rally points can deeply affect the evacuation time.
Critical Behavior in Cellular Automata Animal Disease Transmission Model
NASA Astrophysics Data System (ADS)
Morley, P. D.; Chang, Julius
Using cellular automata model, we simulate the British Government Policy (BGP) in the 2001 foot and mouth epidemic in Great Britain. When clinical symptoms of the disease appeared in a farm, there is mandatory slaughter (culling) of all livestock in an infected premise (IP). Those farms in the neighboring of an IP (contiguous premise, CP), are also culled, aka nearest neighbor interaction. Farms where the disease may be prevalent from animal, human, vehicle or airborne transmission (dangerous contact, DC), are additionally culled, aka next-to-nearest neighbor interactions and lightning factor. The resulting mathematical model possesses a phase transition, whereupon if the physical disease transmission kernel exceeds a critical value, catastrophic loss of animals ensues. The nonlocal disease transport probability can be as low as 0.01% per day and the disease can still be in the high mortality phase. We show that the fundamental equation for sustainable disease transport is the criticality equation for neutron fission cascade. Finally, we calculate that the percentage of culled animals that are actually healthy is ≈30%.
Using Cellular Automata for Parking Recommendations in Smart Environments
Horng, Gwo-Jiun
2014-01-01
In this work, we propose an innovative adaptive recommendation mechanism for smart parking. The cognitive RF module will transmit the vehicle location information and the parking space requirements to the parking congestion computing center (PCCC) when the driver must find a parking space. Moreover, for the parking spaces, we use a cellular automata (CA) model mechanism that can adjust to full and not full parking lot situations. Here, the PCCC can compute the nearest parking lot, the parking lot status and the current or opposite driving direction with the vehicle location information. By considering the driving direction, we can determine when the vehicles must turn around and thus reduce road congestion and speed up finding a parking space. The recommendation will be sent to the drivers through a wireless communication cognitive radio (CR) model after the computation and analysis by the PCCC. The current study evaluates the performance of this approach by conducting computer simulations. The simulation results show the strengths of the proposed smart parking mechanism in terms of avoiding increased congestion and decreasing the time to find a parking space. PMID:25153671
Using cellular automata for parking recommendations in smart environments.
Horng, Gwo-Jiun
2014-01-01
In this work, we propose an innovative adaptive recommendation mechanism for smart parking. The cognitive RF module will transmit the vehicle location information and the parking space requirements to the parking congestion computing center (PCCC) when the driver must find a parking space. Moreover, for the parking spaces, we use a cellular automata (CA) model mechanism that can adjust to full and not full parking lot situations. Here, the PCCC can compute the nearest parking lot, the parking lot status and the current or opposite driving direction with the vehicle location information. By considering the driving direction, we can determine when the vehicles must turn around and thus reduce road congestion and speed up finding a parking space. The recommendation will be sent to the drivers through a wireless communication cognitive radio (CR) model after the computation and analysis by the PCCC. The current study evaluates the performance of this approach by conducting computer simulations. The simulation results show the strengths of the proposed smart parking mechanism in terms of avoiding increased congestion and decreasing the time to find a parking space. PMID:25153671
Cellular automata for traffic flow modeling. Final report
Benjaafar, S.; Dooley, K.; Setyawan, W.
1997-12-01
In this paper, the authors explore the usefulness of cellular automata to traffic flow modeling. The authors extend some of the existing CA models to capture characteristics of traffic flow that have not been possible to model using either conventional analytical models or existing simulation techniques. In particular, the authors examine higher moments of traffic flow and evaluate their effect on overall traffic performance. The behavior of these higher moments is found to be surprising, somewhat counter-intuitive, and to have important implications for design and control of traffic systems. For example, the authors show that the density of maximum throughput is near the density of maximum speed variance. Contrary to current practice, traffic should, therefore, be steered away from this density region. For deterministic systems the authors found traffic flow to possess a finite period which is highly sensitive to density in a non-monotonic fashion. The authors show that knowledge of this periodic behavior to be very useful in designing and controlling automated systems. These results are obtained for both single and two lane systems. For two lane systems, the authors also examine the relationship between lane changing behavior and flow performance. The authors show that the density of maximum land changing frequency occurs past the density of maximum throughput. Therefore, traffic should also be steered away from this density region.
Correlation velocities in heterogeneous bidirectional cellular automata traffic flow
NASA Astrophysics Data System (ADS)
Lakouari, N.; Bentaleb, K.; Ez-Zahraouy, H.; Benyoussef, A.
2015-12-01
Traffic flow behavior and velocity correlation in a bidirectional two lanes road are studied using Cellular Automata (CA) model within a mixture of fast and slow vehicles. The behaviors of the Inter-lane and Intra-lane Velocity Correlation Coefficients (V.C.C.) due to the interactions between vehicles in the same lane and the opposite lane as a function of the density are investigated. It is shown that high densities in one lane lead to large cluster in the second one, which decreases the Intra-lane velocity correlations and thereby form clusters in the opposite lane. Moreover, we have found that there is a critical density over which the Inter-lane V.C.C. occurs, but below which no Inter-lane V.C.C. happens. The spatiotemporal diagrams correspond to those regions are derived numerically. Furthermore, the effect of the overtaking probability in one lane on the Intra-lane V.C.C. in the other lane is also investigated. It is shown that the decrease of the overtaking probability in one lane decreases slightly the Intra-lane V.C.C. at intermediate density regimes in the other lane, which improves the current, as well as the Inter-lane V.C.C. decreases.
Robustness of a cellular automata model for the HIV infection
NASA Astrophysics Data System (ADS)
Figueirêdo, P. H.; Coutinho, S.; Zorzenon dos Santos, R. M.
2008-11-01
An investigation was conducted to study the robustness of the results obtained from the cellular automata model which describes the spread of the HIV infection within lymphoid tissues [R.M. Zorzenon dos Santos, S. Coutinho, Phys. Rev. Lett. 87 (2001) 168102]. The analysis focused on the dynamic behavior of the model when defined in lattices with different symmetries and dimensionalities. The results illustrated that the three-phase dynamics of the planar models suffered minor changes in relation to lattice symmetry variations and, while differences were observed regarding dimensionality changes, qualitative behavior was preserved. A further investigation was conducted into primary infection and sensitiveness of the latency period to variations of the model’s stochastic parameters over wide ranging values. The variables characterizing primary infection and the latency period exhibited power-law behavior when the stochastic parameters varied over a few orders of magnitude. The power-law exponents were approximately the same when lattice symmetry varied, but there was a significant variation when dimensionality changed from two to three. The dynamics of the three-dimensional model was also shown to be insensitive to variations of the deterministic parameters related to cell resistance to the infection, and the necessary time lag to mount the specific immune response to HIV variants. The robustness of the model demonstrated in this work reinforce that its basic hypothesis are consistent with the three-stage dynamic of the HIV infection observed in patients.
Some properties of the floor field cellular automata evacuation model
NASA Astrophysics Data System (ADS)
Gwizdałła, Tomasz M.
2015-02-01
We study the process of evacuation of pedestrians from the room with the given arrangement of doors and obstacles by using the cellular automata technique. The technique which became quite popular is characterized by the discretization of time as well as space. For such a discretized space we use so-called floor field model which generally corresponds to the description of every cell by some monotonic function of distance between this cell and the closest exit. We study several types of effects. We start from some general features of model like the kind of a neighborhood or the factors disrupting the motion. Then we analyze the influence of asymmetry and size on the evacuation time. Finally we show characteristics concerning different arrangements of exits and include a particular approach to the proxemics effects. The scaling analyses help us to distinguish these cases which just reflect the geometry of the system and those which depend also on the simulation properties. All calculations are performed for a wide range of initial densities corresponding to different occupation rates as described by the typical crowd counting techniques.
Cellular automata model for traffic flow with safe driving conditions
NASA Astrophysics Data System (ADS)
María, Elena Lárraga; Luis, Alvarez-Icaza
2014-05-01
In this paper, a recently introduced cellular automata (CA) model is used for a statistical analysis of the inner microscopic structure of synchronized traffic flow. The analysis focuses on the formation and dissolution of clusters or platoons of vehicles, as the mechanism that causes the presence of this synchronized traffic state with a high flow. This platoon formation is one of the most interesting phenomena observed in traffic flows and plays an important role both in manual and automated highway systems (AHS). Simulation results, obtained from a single-lane system under periodic boundary conditions indicate that in the density region where the synchronized state is observed, most vehicles travel together in platoons with approximately the same speed and small spatial distances. The examination of velocity variations and individual vehicle gaps shows that the flow corresponding to the synchronized state is stable, safe and highly correlated. Moreover, results indicate that the observed platoon formation in real traffic is reproduced in simulations by the relation between vehicle headway and velocity that is embedded in the dynamics definition of the CA model.
Stochastic cellular automata model for wildland fire spread dynamics
NASA Astrophysics Data System (ADS)
Maduro Almeida, Rodolfo; Macau, Elbert E. N.
2011-03-01
A stochastic cellular automata model for wildland fire spread under flat terrain and no-wind conditions is proposed and its dynamics is characterized and analyzed. One of three possible states characterizes each cell: vegetation cell, burning cell and burnt cell. The dynamics of fire spread is modeled as a stochastic event with an effective fire spread probability S which is a function of three probabilities that characterize: the proportion of vegetation cells across the lattice, the probability of a burning cell becomes burnt, and the probability of the fire spread from a burning cell to a neighboring vegetation cell. A set of simulation experiments is performed to analyze the effects of different values of the three probabilities in the fire pattern. Monte-Carlo simulations indicate that there is a critical line in the model parameter space that separates the set of parameters which a fire can propagate from those for which it cannot propagate. Finally, the relevance of the model is discussed under the light of computational experiments that illustrate the capability of the model catches both the dynamical and static qualitative properties of fire propagation.
Gutowitz, H.A.
1988-11-17
In this lecture the map from a cellular automaton to a sequence of analytical approximations called the local structure theory is described. Connections are drawn between cellular automata and neural network models. It is suggested that the process by which a cellular automaton holds particular probability measures invariant is an appropriate model for biological memory. 20 figs.
A stochastic parameterization for deep convection using cellular automata
NASA Astrophysics Data System (ADS)
Bengtsson, L.; Steinheimer, M.; Bechtold, P.; Geleyn, J.
2012-12-01
Cumulus parameterizations used in most operational weather and climate models today are based on the mass-flux concept which took form in the early 1970's. In such schemes it is assumed that a unique relationship exists between the ensemble-average of the sub-grid convection, and the instantaneous state of the atmosphere in a vertical grid box column. However, such a relationship is unlikely to be described by a simple deterministic function (Palmer, 2011). Thus, because of the statistical nature of the parameterization challenge, it has been recognized by the community that it is important to introduce stochastic elements to the parameterizations (for instance: Plant and Craig, 2008, Khouider et al. 2010, Frenkel et al. 2011, Bentsson et al. 2011, but the list is far from exhaustive). There are undoubtedly many ways in which stochastisity can enter new developments. In this study we use a two-way interacting cellular automata (CA), as its intrinsic nature possesses many qualities interesting for deep convection parameterization. In the one-dimensional entraining plume approach, there is no parameterization of horizontal transport of heat, moisture or momentum due to cumulus convection. In reality, mass transport due to gravity waves that propagate in the horizontal can trigger new convection, important for the organization of deep convection (Huang, 1988). The self-organizational characteristics of the CA allows for lateral communication between adjacent NWP model grid-boxes, and temporal memory. Thus the CA scheme used in this study contain three interesting components for representation of cumulus convection, which are not present in the traditional one-dimensional bulk entraining plume method: horizontal communication, memory and stochastisity. The scheme is implemented in the high resolution regional NWP model ALARO, and simulations show enhanced organization of convective activity along squall-lines. Probabilistic evaluation demonstrate an enhanced spread in
Modeling pedestrian behaviors under attracting incidents using cellular automata
NASA Astrophysics Data System (ADS)
Chen, Yanyan; Chen, Ning; Wang, Yang; Wang, Zhenbao; Feng, Guochen
2015-08-01
Compared to vehicular flow, pedestrian flow is more complicated as it is free from the restriction of the lane and more flexible. Due to the lack of modeling pedestrian behaviors under attracting incidents (incidents which attract pedestrians around to gather), this paper proposes a new cellular automata model aiming to reproduce the behaviors induced by such attracting incidents. When attracting incidents occur, the proposed model will classify pedestrians around the incidents into three groups: the "unaffected" type, the "stopped" type and the "onlooking" type. The "unaffected" type represents the pedestrians who are not interested in the attracting incidents and its dynamics are the same as that under normal circumstances which are the main target in the previous works. The "stopped" type represents the pedestrians are somewhat interested in the attracting incidents, but unwilling to move close to the venues. Its dynamics are determined by "stopped" utility which can make the pedestrians stop for a while. The "onlooking" type represents the pedestrians who show strong interest in the attracting incidents and intend to move close to the venues to gain more information. The "onlooking" pedestrians will take a series of reactions to attracting incidents, such as approaching to the venues, stopping and watching the attracting incidents, leaving the venues, which have all been considered in the proposed model. The simulation results demonstrate that the proposed model can capture the macro-characteristics of pedestrian traffic flow under normal circumstances and possesses the fundamental characteristics of the pedestrian behaviors under attracting incidents around which a torus-shaped crowd is typically formed.
Validating Cellular Automata Lava Flow Emplacement Algorithms with Standard Benchmarks
NASA Astrophysics Data System (ADS)
Richardson, J. A.; Connor, L.; Charbonnier, S. J.; Connor, C.; Gallant, E.
2015-12-01
A major existing need in assessing lava flow simulators is a common set of validation benchmark tests. We propose three levels of benchmarks which test model output against increasingly complex standards. First, imulated lava flows should be morphologically identical, given changes in parameter space that should be inconsequential, such as slope direction. Second, lava flows simulated in simple parameter spaces can be tested against analytical solutions or empirical relationships seen in Bingham fluids. For instance, a lava flow simulated on a flat surface should produce a circular outline. Third, lava flows simulated over real world topography can be compared to recent real world lava flows, such as those at Tolbachik, Russia, and Fogo, Cape Verde. Success or failure of emplacement algorithms in these validation benchmarks can be determined using a Bayesian approach, which directly tests the ability of an emplacement algorithm to correctly forecast lava inundation. Here we focus on two posterior metrics, P(A|B) and P(¬A|¬B), which describe the positive and negative predictive value of flow algorithms. This is an improvement on less direct statistics such as model sensitivity and the Jaccard fitness coefficient. We have performed these validation benchmarks on a new, modular lava flow emplacement simulator that we have developed. This simulator, which we call MOLASSES, follows a Cellular Automata (CA) method. The code is developed in several interchangeable modules, which enables quick modification of the distribution algorithm from cell locations to their neighbors. By assessing several different distribution schemes with the benchmark tests, we have improved the performance of MOLASSES to correctly match early stages of the 2012-3 Tolbachik Flow, Kamchakta Russia, to 80%. We also can evaluate model performance given uncertain input parameters using a Monte Carlo setup. This illuminates sensitivity to model uncertainty.
Generic framework for mining cellular automata models on protein-folding simulations.
Diaz, N; Tischer, I
2016-01-01
Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined. PMID:27323045
A novel image encryption algorithm using chaos and reversible cellular automata
NASA Astrophysics Data System (ADS)
Wang, Xingyuan; Luan, Dapeng
2013-11-01
In this paper, a novel image encryption scheme is proposed based on reversible cellular automata (RCA) combining chaos. In this algorithm, an intertwining logistic map with complex behavior and periodic boundary reversible cellular automata are used. We split each pixel of image into units of 4 bits, then adopt pseudorandom key stream generated by the intertwining logistic map to permute these units in confusion stage. And in diffusion stage, two-dimensional reversible cellular automata which are discrete dynamical systems are applied to iterate many rounds to achieve diffusion on bit-level, in which we only consider the higher 4 bits in a pixel because the higher 4 bits carry almost the information of an image. Theoretical analysis and experimental results demonstrate the proposed algorithm achieves a high security level and processes good performance against common attacks like differential attack and statistical attack. This algorithm belongs to the class of symmetric systems.
Is there a sharp phase transition for deterministic cellular automata
Wootters, W.K. Los Alamos National Lab., NM Williams Coll., Williamstown, MA . Dept. of Physics); Langton, C.G. )
1990-01-01
Previous work has suggested that there is a kind of phase transition between deterministic automata exhibiting periodic behavior and those exhibiting chaotic behavior. However, unlike the usual phase transitions of physics, this transition takes place over a range of values of the parameter rather than at a specific value. The present paper asks whether the transition can be made sharp, either by taking the limit of an infinitely large rule table, or by changing the parameter in terms of which the space of automata is explored. We find strong evidence that, for the class of automata we consider, the transition does become sharp in the limit of an infinite number of symbols, the size of the neighborhood being held fixed. Our work also suggests an alternative parameter in terms of which it is likely that the transition will become fairly sharp even if one does not increase the number of symbols. In the course of our analysis, we find that mean field theory, which is our main tool, gives surprisingly good predictions of the statistical properties of the class of automata we consider. 18 refs., 6 figs.
A Cellular Automata Model for the Study of Landslides
NASA Astrophysics Data System (ADS)
Liucci, Luisa; Suteanu, Cristian; Melelli, Laura
2016-04-01
Power-law scaling has been observed in the frequency distribution of landslide sizes in many regions of the world, for landslides triggered by different factors, and in both multi-temporal and post-event datasets, thus indicating the universal character of this property of landslides and suggesting that the same mechanisms drive the dynamics of mass wasting processes. The reasons for the scaling behavior of landslide sizes are widely debated, since their understanding would improve our knowledge of the spatial and temporal evolution of this phenomenon. Self-Organized Critical (SOC) dynamics and the key role of topography have been suggested as possible explanations. The scaling exponent of the landslide size-frequency distribution defines the probability of landslide magnitudes and it thus represents an important parameter for hazard assessment. Therefore, another - still unanswered - important question concerns the factors on which its value depends. This paper investigates these issues using a Cellular Automata (CA) model. The CA uses a real topographic surface acquired from a Digital Elevation Model to represent the initial state of the system, where the states of cells are defined in terms of altitude. The stability criterion is based on the slope gradient. The system is driven to instability through a temporal decrease of the stability condition of cells, which may be thought of as representing the temporal weakening of soil caused by factors like rainfall. A transition rule defines the way in which instabilities lead to discharge from unstable cells to the neighboring cells, deciding upon the landslide direction and the quantity of mass involved. Both the direction and the transferred mass depend on the local topographic features. The scaling properties of the area-frequency distributions of the resulting landslide series are investigated for several rates of weakening and for different time windows, in order to explore the response of the system to model
Free Quantum Field Theory from Quantum Cellular Automata
NASA Astrophysics Data System (ADS)
Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo; Tosini, Alessandro
2015-10-01
After leading to a new axiomatic derivation of quantum theory (see D'Ariano et al. in Found Phys, 2015), the new informational paradigm is entering the domain of quantum field theory, suggesting a quantum automata framework that can be regarded as an extension of quantum field theory to including an hypothetical Planck scale, and with the usual quantum field theory recovered in the relativistic limit of small wave-vectors. Being derived from simple principles (linearity, unitarity, locality, homogeneity, isotropy, and minimality of dimension), the automata theory is quantum ab-initio, and does not assume Lorentz covariance and mechanical notions. Being discrete it can describe localized states and measurements (unmanageable by quantum field theory), solving all the issues plaguing field theory originated from the continuum. These features make the theory an ideal framework for quantum gravity, with relativistic covariance and space-time emergent solely from the interactions, and not assumed a priori. The paper presents a synthetic derivation of the automata theory, showing how the principles lead to a description in terms of a quantum automaton over a Cayley graph of a group. Restricting to Abelian groups we show how the automata recover the Weyl, Dirac and Maxwell dynamics in the relativistic limit. We conclude with some new routes about the more general scenario of non-Abelian Cayley graphs. The phenomenology arising from the automata theory in the ultra-relativistic domain and the analysis of corresponding distorted Lorentz covariance is reviewed in Bisio et al. (Found Phys 2015, in this same issue).
A comparative analysis of electronic and molecular quantum dot cellular automata
Umamahesvari, H. E-mail: ajithavijay1@gmail.com; Ajitha, D. E-mail: ajithavijay1@gmail.com
2015-06-24
This paper presents a comparative analysis of electronic quantum-dot cellular automata (EQCA) and Magnetic quantum dot Cellular Automata (MQCA). QCA is a computing paradigm that encodes and processes information by the position of individual electrons. To enhance the high dense and ultra-low power devices, various researches have been actively carried out to find an alternative way to continue and follow Moore’s law, so called “beyond CMOS technology”. There have been several proposals for physically implementing QCA, EQCA and MQCA are the two important QCAs reported so far. This paper provides a comparative study on these two QCAs.
Ecological risk assessment of genetically modified crops based on cellular automata modeling.
Yang, Jun; Wang, Zhi-Rui; Yang, De-Li; Yang, Qing; Yan, Jun; He, Ming-Feng
2009-01-01
The assessment of ecological risk in genetically modified (GM) biological systems is critically important for decision-making and public acceptance. Cellular automata (CA) provide a potential modeling and simulation framework for representing relationships and interspecies interactions both temporally and spatially. In this paper, a simple subsystem contains only four species: crop, target pest, non-target pest and enemy insect, and a three layer arrangement of LxL stochastic cellular automata with a periodic boundary were established. The simulation of this simplified system showed abundant and sufficient complexity in population assembly and densities, suggesting a prospective application in ecological risk assessment of GM crops. PMID:19477260
A comparative analysis of electronic and molecular quantum dot cellular automata
NASA Astrophysics Data System (ADS)
Umamahesvari, H.; Ajitha, D.
2015-06-01
This paper presents a comparative analysis of electronic quantum-dot cellular automata (EQCA) and Magnetic quantum dot Cellular Automata (MQCA). QCA is a computing paradigm that encodes and processes information by the position of individual electrons. To enhance the high dense and ultra-low power devices, various researches have been actively carried out to find an alternative way to continue and follow Moore's law, so called "beyond CMOS technology". There have been several proposals for physically implementing QCA, EQCA and MQCA are the two important QCAs reported so far. This paper provides a comparative study on these two QCAs
Cellular Automata Models Applied to the Study of Landslide Dynamics
NASA Astrophysics Data System (ADS)
Liucci, Luisa; Melelli, Laura; Suteanu, Cristian
2015-04-01
Landslides are caused by complex processes controlled by the interaction of numerous factors. Increasing efforts are being made to understand the spatial and temporal evolution of this phenomenon, and the use of remote sensing data is making significant contributions in improving forecast. This paper studies landslides seen as complex dynamic systems, in order to investigate their potential Self Organized Critical (SOC) behavior, and in particular, scale-invariant aspects of processes governing the spatial development of landslides and their temporal evolution, as well as the mechanisms involved in driving the system and keeping it in a critical state. For this purpose, we build Cellular Automata Models, which have been shown to be capable of reproducing the complexity of real world features using a small number of variables and simple rules, thus allowing for the reduction of the number of input parameters commonly used in the study of processes governing landslide evolution, such as those linked to the geomechanical properties of soils. This type of models has already been successfully applied in studying the dynamics of other natural hazards, such as earthquakes and forest fires. The basic structure of the model is composed of three modules: (i) An initialization module, which defines the topographic surface at time zero as a grid of square cells, each described by an altitude value; the surface is acquired from real Digital Elevation Models (DEMs). (ii) A transition function, which defines the rules used by the model to update the state of the system at each iteration. The rules use a stability criterion based on the slope angle and introduce a variable describing the weakening of the material over time, caused for example by rainfall. The weakening brings some sites of the system out of equilibrium thus causing the triggering of landslides, which propagate within the system through local interactions between neighboring cells. By using different rates of
The preservation of riparian zones and other environmentally sensitive areas has long been recognized as one of the most cost-effective methods of managing stormwater and providing a broad range of ecosystem services. In this research, a cellular automata (CA)—Markov chain model ...
Simulating the immune response to the HIV-1 virus with cellular automata
NASA Astrophysics Data System (ADS)
Kougias, Ch. F.; Schulte, J.
1990-07-01
Two cellular automata models are presented which simulate the immune response to the HIV-1 virus at the early stage of the infection. The simple model A is based on the generalized nearest neighbor interaction, and the complex model B on the explicitly defined local interactions between the neighboring sites. These two models are discussed in the context of related work by Pandey.
Cellular automata with object-oriented features for parallel molecular network modeling.
Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan
2005-06-01
Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented. PMID:16117022
Order of the transition versus space dimension in a family of cellular automata
NASA Astrophysics Data System (ADS)
Bidaux, Roger; Boccara, Nini; Chaté, Hugues
1989-03-01
A mean-field theory of (probabilistic) cellular automata is developed and used to select a typical local rule whose mean-field analysis predicts first-order phase transitions. The corresponding automaton is then studied numerically on regular lattices for space dimensions d between 1 and 4. At odds with usual beliefs on two-state automata with one absorbing phase, first-order transitions are indeed exhibited as soon as d>1, with closer quantitative agreement with mean-field predictions for high space dimensions. For d=1, the transition is continuous, but with critical exponents different from those of directed percolation.
Simulation of the 1992 Tessina landslide by a cellular automata model and future hazard scenarios
NASA Astrophysics Data System (ADS)
Avolio, MV; Di Gregorio, Salvatore; Mantovani, Franco; Pasuto, Alessandro; Rongo, Rocco; Silvano, Sandro; Spataro, William
Cellular Automata are a powerful tool for modelling natural and artificial systems, which can be described in terms of local interactions of their constituent parts. Some types of landslides, such as debris/mud flows, match these requirements. The 1992 Tessina landslide has characteristics (slow mud flows) which make it appropriate for modelling by means of Cellular Automata, except for the initial phase of detachment, which is caused by a rotational movement that has no effect on the mud flow path. This paper presents the Cellular Automata approach for modelling slow mud/debris flows, the results of simulation of the 1992 Tessina landslide and future hazard scenarios based on the volumes of masses that could be mobilised in the future. They were obtained by adapting the Cellular Automata Model called SCIDDICA, which has been validated for very fast landslides. SCIDDICA was applied by modifying the general model to the peculiarities of the Tessina landslide. The simulations obtained by this initial model were satisfactory for forecasting the surface covered by mud. Calibration of the model, which was obtained from simulation of the 1992 event, was used for forecasting flow expansion during possible future reactivation. For this purpose two simulations concerning the collapse of about 1 million m 3 of material were tested. In one of these, the presence of a containment wall built in 1992 for the protection of the Tarcogna hamlet was inserted. The results obtained identified the conditions of high risk affecting the villages of Funes and Lamosano and show that this Cellular Automata approach can have a wide range of applications for different types of mud/debris flows.
Modeling Pseudorandom Sequence Generators using Cellular Automata: The Alternating Step Generator
NASA Astrophysics Data System (ADS)
Pazo-Robles, María Eugenia; Fúster-Sabater, Amparo
2007-12-01
Stream ciphers are pseudorandom bit generators whose output sequences are combined with the sensitive information by means of a mathematical function currently an addition module 2. The Alternating Step Generator is a pseudorandom sequence generator with good cryptographic properties and non-linear structure. In this work, we propose two different ways to model such a generator by using linear and discrete mathematical functions e.g. Cellular Automata. One of these ways deals with the realization of a linear model from a pair of basic automata provided by the Catell and Muzio algorithm. The other way is a new approach based on automata's addition consisting in the realization of a new automaton with non-primitive polynomial and short length. Both methods provide linear models able to generate the output sequence of the Alternating Step Generator.
Phase transitions in coupled map lattices and in associated probabilistic cellular automata.
Just, Wolfram
2006-10-01
Analytical tools are applied to investigate piecewise linear coupled map lattices in terms of probabilistic cellular automata. The so-called disorder condition of probabilistic cellular automata is closely related with attracting sets in coupled map lattices. The importance of this condition for the suppression of phase transitions is illustrated by spatially one-dimensional systems. Invariant densities and temporal correlations are calculated explicitly. Ising type phase transitions are found for one-dimensional coupled map lattices acting on repelling sets and for a spatially two-dimensional Miller-Huse-like system with stable long time dynamics. Critical exponents are calculated within a finite size scaling approach. The relevance of detailed balance of the resulting probabilistic cellular automaton for the critical behavior is pointed out. PMID:17155155
Stability of Cellular Automata Trajectories Revisited: Branching Walks and Lyapunov Profiles
NASA Astrophysics Data System (ADS)
Baetens, Jan M.; Gravner, Janko
2016-05-01
We study non-equilibrium defect accumulation dynamics on a cellular automaton trajectory: a branching walk process in which a defect creates a successor on any neighborhood site whose update it affects. On an infinite lattice, defects accumulate at different exponential rates in different directions, giving rise to the Lyapunov profile. This profile quantifies instability of a cellular automaton evolution and is connected to the theory of large deviations. We rigorously and empirically study Lyapunov profiles generated from random initial states. We also introduce explicit and computationally feasible variational methods to compute the Lyapunov profiles for periodic configurations, thus developing an analog of Floquet theory for cellular automata.
Topology regulates pattern formation capacity of binary cellular automata on graphs
NASA Astrophysics Data System (ADS)
Marr, Carsten; Hütt, Marc-Thorsten
2005-08-01
We study the effect of topology variation on the dynamic behavior of a system with local update rules. We implement one-dimensional binary cellular automata on graphs with various topologies by formulating two sets of degree-dependent rules, each containing a single parameter. We observe that changes in graph topology induce transitions between different dynamic domains (Wolfram classes) without a formal change in the update rule. Along with topological variations, we study the pattern formation capacities of regular, random, small-world and scale-free graphs. Pattern formation capacity is quantified in terms of two entropy measures, which for standard cellular automata allow a qualitative distinction between the four Wolfram classes. A mean-field model explains the dynamic behavior of random graphs. Implications for our understanding of information transport through complex, network-based systems are discussed.
Chaos of elementary cellular automata rule 42 of Wolfram's class II
NASA Astrophysics Data System (ADS)
Chen, Fang-Yue; Jin, Wei-Feng; Chen, Guan-Rong; Chen, Fang-Fang; Chen, Lin
2009-03-01
In this paper, the dynamics of elementary cellular automata rule 42 is investigated in the bi-infinite symbolic sequence space. Rule 42, a member of Wolfram's class II which was said to be simply as periodic before, actually defines a chaotic global attractor; that is, rule 42 is topologically mixing on its global attractor and possesses the positive topological entropy. Therefore, rule 42 is chaotic in the sense of both Li-Yorke and Devaney. Meanwhile, the characteristic function and the basin tree diagram of rule 42 are explored for some finite length of binary strings, which reveal its Bernoulli characteristics. The method presented in this work is also applicable to studying the dynamics of other rules, especially the 112 Bernoulli-shift rules of the elementary cellular automata.
A cellular automata model of traffic flow with variable probability of randomization
NASA Astrophysics Data System (ADS)
Zheng, Wei-Fan; Zhang, Ji-Ye
2015-05-01
Research on the stochastic behavior of traffic flow is important to understand the intrinsic evolution rules of a traffic system. By introducing an interactional potential of vehicles into the randomization step, an improved cellular automata traffic flow model with variable probability of randomization is proposed in this paper. In the proposed model, the driver is affected by the interactional potential of vehicles before him, and his decision-making process is related to the interactional potential. Compared with the traditional cellular automata model, the modeling is more suitable for the driver’s random decision-making process based on the vehicle and traffic situations in front of him in actual traffic. From the improved model, the fundamental diagram (flow-density relationship) is obtained, and the detailed high-density traffic phenomenon is reproduced through numerical simulation. Project supported by the National Natural Science Foundation of China (Grant Nos. 11172247, 61273021, 61373009, and 61100118).
Chaos of elementary cellular automata rule 42 of Wolfram's class II.
Chen, Fang-Yue; Jin, Wei-Feng; Chen, Guan-Rong; Chen, Fang-Fang; Chen, Lin
2009-03-01
In this paper, the dynamics of elementary cellular automata rule 42 is investigated in the bi-infinite symbolic sequence space. Rule 42, a member of Wolfram's class II which was said to be simply as periodic before, actually defines a chaotic global attractor; that is, rule 42 is topologically mixing on its global attractor and possesses the positive topological entropy. Therefore, rule 42 is chaotic in the sense of both Li-Yorke and Devaney. Meanwhile, the characteristic function and the basin tree diagram of rule 42 are explored for some finite length of binary strings, which reveal its Bernoulli characteristics. The method presented in this work is also applicable to studying the dynamics of other rules, especially the 112 Bernoulli-shift rules of the elementary cellular automata. PMID:19335004
From QCA (Quantum Cellular Automata) to Organocatalytic Reactions with Stabilized Carbenium Ions.
Gualandi, Andrea; Mengozzi, Luca; Manoni, Elisabetta; Giorgio Cozzi, Pier
2016-06-01
What do quantum cellular automata (QCA), "on water" reactions, and SN 1-type organocatalytic transformations have in common? The link between these distant arguments is the practical access to useful intermediates and key products through the use of stabilized carbenium ions. Over 10 years, starting with a carbenium ion bearing a ferrocenyl group, to the 1,3-benzodithiolylium carbenium ion, our group has exploited the use of these intermediates in useful and practical synthetic transformations. In particular, we have applied the use of carbenium ions to stereoselective organocatalytic alkylation reactions, showing a possible solution for the "holy grail of organocatalysis". Examples of the use of these quite stabilized intermediates are now also considered in organometallic chemistry. On the other hand, the stable carbenium ions are also applied to tailored molecules adapted to quantum cellular automata, a new possible paradigm for computation. Carbenium ions are not a problem, they can be a/the solution! PMID:27062088
Coulomb coupling and the role of symmetries in quantum-dot arrays for cellular automata
Ramirez, F.; Cota, E.; Ulloa, S. E.
2000-07-15
Using a group-theoretical analysis of the symmetries of a quantum dot array, we investigate the role of defects on the energetics of the system and the resulting charge configurations (or polarization of the cell). We find that for the typical four- or five-element geometries proposed, even small asymmetries introduced by defects in the system, or variations in the local electrostatic environment, can give rise to large effects on the polarization of the ground state and the corresponding low-energy excitations. These shifts are likely to produce important effects in the operation of the cellular automata proposed using these quantum dots. In particular, we find that the sensitivity to polarization changes induced by a driver cell decreases dramatically, and the polarization values are no longer fully defined. These effects would both force the use of stronger driving fields, and may also complicate the dynamical behavior of the cellular automata. (c) 2000 The American Physical Society.
Spatial organization and evolution period of the epidemic model using cellular automata.
Liu, Quan-Xing; Jin, Zhen; Liu, Mao-Xing
2006-09-01
We investigate epidemic models with spatial structure based on the cellular automata method. The construction of the cellular automata is from the study by Weimar and Boon about the reaction-diffusion equations [Phys. Rev. E 49, 1749 (1994)]. Our results show that the spatial epidemic models exhibit the spontaneous formation of irregular spiral waves at large scales within the domain of chaos. Moreover, the irregular spiral waves grow stably. The system also shows a spatial period-2 structure at one dimension outside the domain of chaos. It is interesting that the spatial period-2 structure will break and transform into a spatial synchronous configuration in the domain of chaos. Our results confirm that populations embed and disperse more stably in space than they do in nonspatial counterparts. PMID:17025597
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.
Nishawala, Vinesh V.; Ostoja-Starzewski, Martin; Leamy, Michael J.; Demmie, Paul N.
2015-09-10
Peridynamics is a non-local continuum mechanics formulation that can handle spatial discontinuities as the governing equations are integro-differential equations which do not involve gradients such as strains and deformation rates. This paper employs bond-based peridynamics. Cellular Automata is a local computational method which, in its rectangular variant on interior domains, is mathematically equivalent to the central difference finite difference method. However, cellular automata does not require the derivation of the governing partial differential equations and provides for common boundary conditions based on physical reasoning. Both methodologies are used to solve a half-space subjected to a normal load, known as Lamb’smore » Problem. The results are compared with theoretical solution from classical elasticity and experimental results. Furthermore, this paper is used to validate our implementation of these methods.« less
Efficient process development for bulk silicon etching using cellular automata simulation techniques
NASA Astrophysics Data System (ADS)
Marchetti, James; He, Yie; Than, Olaf; Akkaraju, Sandeep
1998-09-01
This paper describes cellular automata simulation techniques used to predict the anisotropic etching of single-crystal silicon. In particular, this paper will focus on the application of wet etching of silicon wafers using typical anisotropic etchants such as KOH, TMAH, and EDP. Achieving a desired final 3D geometry of etch silicon wafers often is difficult without requiring a number of fabrication design iterations. The result is wasted time and resources. AnisE, a tool to simulate anisotropic etching of silicon wafers using cellular automata simulation, was developed in order to efficiently prototype and manufacture MEMS devices. AnisE has been shown to effectively decrease device development time and costs by up to 50% and 60%, respectively.
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.
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.
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.
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.
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.
Supervised nuclear track detection of CR-39 detectors by cellular automata
NASA Astrophysics Data System (ADS)
Chahkandi Nejad, Hadi; Khayat, Omid; Mohammadi, Kheirollah; Tavakoli, Saeed
2014-05-01
In this paper, cellular automata are used to detect the nuclear tracks in the track images captured from the surface of CR-39 detectors. Parameters of the automaton as the states, neighborhood, rules and quality parameters are defined optimally for the track image data set under analysis. The presented method is a supervised computational algorithm which comprises a rule definition phase as the learning procedure. Parameter optimization is also performed to adapt the algorithm to the data set used.
a Predator-Prey Model Based on the Fully Parallel Cellular Automata
NASA Astrophysics Data System (ADS)
He, Mingfeng; Ruan, Hongbo; Yu, Changliang
We presented a predator-prey lattice model containing moveable wolves and sheep, which are characterized by Penna double bit strings. Sexual reproduction and child-care strategies are considered. To implement this model in an efficient way, we build a fully parallel Cellular Automata based on a new definition of the neighborhood. We show the roles played by the initial densities of the populations, the mutation rate and the linear size of the lattice in the evolution of this model.
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.
NASA Astrophysics Data System (ADS)
Vanag, Vladimir K.
1999-05-01
Spatially extended dynamical systems are ubiquitous and include such things as insect and animal populations; complex chemical, technological, and geochemical processes; humanity itself, and much more. It is clearly desirable to have a certain universal tool with which the highly complex behaviour of nonlinear dynamical systems can be analyzed and modelled. For this purpose, cellular automata seem to be good candidates. In the present review, emphasis is placed on the possibilities that various types of probabilistic cellular automata (PCA), such as DSMC (direct simulation Monte Carlo) and LGCA (lattice-gas cellular automata), offer. The methods are primarily designed for modelling spatially extended dynamical systems with inner fluctuations accounted for. For the Willamowskii-Roessler and Oregonator models, PCA applications to the following problems are illustrated: the effect of fluctuations on the dynamics of nonlinear systems; Turing structure formation; the effect of hydrodynamic modes on the behaviour of nonlinear chemical systems (stirring effects); bifurcation changes in the dynamical regimes of complex systems with restricted geometry or low spatial dimension; and the description of chemical systems in microemulsions.
Incremental Learning of Cellular Automata for Parallel Recognition of Formal Languages
NASA Astrophysics Data System (ADS)
Nakamura, Katsuhiko; Imada, Keita
Parallel language recognition by cellular automata (CAs) is currently an important subject in computation theory. This paper describes incremental learning of one-dimensional, bounded, one-way, cellular automata (OCAs) that recognize formal languages from positive and negative sample strings. The objectives of this work are to develop automatic synthesis of parallel systems and to contribute to the theory of real-time recognition by cellular automata. We implemented methods to learn the rules of OCAs in the Occam system, which is based on grammatical inference of context-free grammars (CFGs) implemented in Synapse. An important feature of Occam is incremental learning by a rule generation mechanism called bridging and the search for rule sets. The bridging looks for and fills gaps in incomplete space-time transition diagrams for positive samples. Another feature of our approach is that the system synthesizes minimal or semi-minimal rule sets of CAs. This paper reports experimental results on learning several OCAs for fundamental formal languages including sets of balanced parentheses and palindromes as well as the set {a n b n c n | n ≥ 1}.
Synchronization, TIGoRS, and Information Flow in Complex Systems: Dispositional Cellular Automata.
Sulis, William H
2016-04-01
Synchronization has a long history in physics where it refers to the phase matching of two identical oscillators. This notion has been extensively studied in physics as well as in biology, where it has been applied to such widely varying phenomena as the flashing of fireflies and firing of neurons in the brain. Human behavior, however, may be recurrent but it is not oscillatory even though many physiological systems do exhibit oscillatory tendencies. Moreover, much of human behaviour is collaborative and cooperative, where the individual behaviours may be distinct yet contemporaneous (if not simultaneous) and taken collectively express some functionality. In the context of behaviour, the important aspect is the repeated co-occurrence in time of behaviours that facilitate the propagation of information or of functionality, regardless of whether or not these behaviours are similar or identical. An example of this weaker notion of synchronization is transient induced global response synchronization (TIGoRS). Previous work has shown that TIGoRS is a ubiquitous phenomenon among complex systems, enabling them to stably parse environmental transients into salient units to which they stably respond. This leads to the notion of Sulis machines, which emergently generate a primitive linguistic structure through their dynamics. This article reviews the notion of TIGoRS and its expression in several complex systems models including tempered neural networks, driven cellular automata and cocktail party automata. The emergent linguistics of Sulis machines are discussed. A new class of complex systems model, the dispositional cellular automaton is introduced. A new metric for TIGoRS, the excess synchronization, is introduced and applied to the study of TIGoRS in dispositional cellular automata. It is shown that these automata exhibit a nonlinear synchronization response to certain perturbing transients. PMID:27033136
NASA Astrophysics Data System (ADS)
Javaheri Javid, Mohammad Ali; Blackwell, Tim; Zimmer, Robert; Majid al-Rifaie, Mohammad
2016-04-01
Shannon entropy fails to discriminate structurally different patterns in two-dimensional images. We have adapted information gain measure and Kolmogorov complexity to overcome the shortcomings of entropy as a measure of image structure. The measures are customised to robustly quantify the complexity of images resulting from multi-state cellular automata (CA). Experiments with a two-dimensional multi-state cellular automaton demonstrate that these measures are able to predict some of the structural characteristics, symmetry and orientation of CA generated patterns.
Noise-enhanced performance of ratchet cellular automata.
Babic, Dusan; Bechinger, Clemens
2005-04-15
We present the first experimental realization of a ratchet cellular automaton (RCA) which has recently been suggested as an alternative approach for performing logical operations with interacting (quasi)particles. Our study was performed with interacting colloidal particles which serve as a model system for other dissipative systems, i.e., magnetic vortices on a superconductor or ions in dissipative optical arrays. We demonstrate that noise can enhance the efficiency of information transport in RCA and consequently enables their optimal operation at finite temperatures. PMID:15904122
A cellular automata model of Ebola virus dynamics
NASA Astrophysics Data System (ADS)
Burkhead, Emily; Hawkins, Jane
2015-11-01
We construct a stochastic cellular automaton (SCA) model for the spread of the Ebola virus (EBOV). We make substantial modifications to an existing SCA model used for HIV, introduced by others and studied by the authors. We give a rigorous analysis of the similarities between models due to the spread of virus and the typical immune response to it, and the differences which reflect the drastically different timing of the course of EBOV. We demonstrate output from the model and compare it with clinical data.
A new small-world network created by Cellular Automata
NASA Astrophysics Data System (ADS)
Ruan, Yuhong; Li, Anwei
2016-08-01
In this paper, we generate small-world networks by the Cellular Automaton based on starting with one-dimensional regular networks. Besides the common properties of small-world networks with small average shortest path length and large clustering coefficient, the small-world networks generated in this way have other properties: (i) The edges which are cut in the regular network can be controlled that whether the edges are reconnected or not, and (ii) the number of the edges of the small-world network model equals the number of the edges of the original regular network. In other words, the average degree of the small-world network model equals to the average degree of the original regular network.
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.
Fluctuation in option pricing using cellular automata based market models
NASA Astrophysics Data System (ADS)
Gao, Yuying; Beni, Gerardo
2005-05-01
A new agent-based Cellular Automaton (CA) computational algorithm for option pricing is proposed. CAs have been extensively used in modeling complex dynamical systems but not in modeling option prices. Compared with traditional tools, which rely on guessing volatilities to calculate option prices, the CA model is directly addressing market mechanisms and simulates price fluctuation from aggregation of actions made by interacting individual market makers in a large population. This paper explores whether CA models can provide reasonable good answers to pricing European options. The Black-Scholes model and the Binomial Tree model are used for comparison. Comparison reveals that CA models perform reasonably well in pricing options, reproducing overall characteristics of random walk based model, while at the same time providing plausible results for the 'fat-tail' phenomenon observed in many markets. We also show that the binomial tree model can be obtained from a CA rule. Thus, CA models are suitable tools to generalize the standard theories of option pricing.
An evaluation of cellular automata applied to ganglia dissolution
NASA Astrophysics Data System (ADS)
Johns, M. L.; Gladden, L. F.
2002-12-01
The ability of a three-dimensional (3-D) cellular automaton (CA) approach to describe or mimic the dissolution of entrapped octanol ganglia, trapped in a porous media, into a mobile aqueous phase has been directly assessed using detailed 3-D visualizations of the dissolution process, as provided by magnetic resonance imaging (MRI). In the 3-D CA, both time and space are made discrete with the state of each geometric site being updated after each time increment according to the state of all neighboring sites. Good agreement is produced by a direct 3-D comparison of the CA results with the corresponding images of the dissolving ganglia. These experimental images are also supplemented by 3-D velocity maps of the mobile aqueous phase produced using either MRI or by a lattice-Boltzmann simulation. The velocity maps are used to validate the assumption that a consideration of the local velocity field is essential for an accurate description of the ganglia dissolution process. Based on this analysis, an appropriate length scale is proposed for the region, required to be considered in the respective vicinity of each ganglion, when describing their dissolution using a CA approach.
Symbolic Computation Using Cellular Automata-Based Hyperdimensional Computing.
Yilmaz, Ozgur
2015-12-01
This letter introduces a novel framework of reservoir computing that is capable of both connectionist machine intelligence and symbolic computation. A cellular automaton is used as the reservoir of dynamical systems. Input is randomly projected onto the initial conditions of automaton cells, and nonlinear computation is performed on the input via application of a rule in the automaton for a period of time. The evolution of the automaton creates a space-time volume of the automaton state space, and it is used as the reservoir. The proposed framework is shown to be capable of long-term memory, and it requires orders of magnitude less computation compared to echo state networks. As the focus of the letter, we suggest that binary reservoir feature vectors can be combined using Boolean operations as in hyperdimensional computing, paving a direct way for concept building and symbolic processing. To demonstrate the capability of the proposed system, we make analogies directly on image data by asking, What is the automobile of air? PMID:26496041
Calculation of impulse responses with a cellular automata algorithm
NASA Astrophysics Data System (ADS)
Barjau, Ana
2001-05-01
The air columns in musical instruments usually have a predominant dimension and thus are very often modeled as 1D systems where uniparametric waves propagate. Different algorithms can be found in the literature to simulate this propagation. The more widely used are finite difference schemes and delay lines. A finite difference scheme (FD) is a numerical integration of a differential formulation (the wave equation), while delay lines (DL) use analytical exact solutions of the wave equation over finite lengths. A new and different approach is that of a cellular automaton (CA) scheme. The underlying philosophy is opposite those of FD and DL, as the starting point is not the wave equation. In a CA approach, the phenomenon to be studied is reduced to a few simple physical laws that are applied to a set of cells representing the physical system (in the present case, the propagation medium). In this paper, a CA will be proposed to obtain the impulse response of different bore geometries. The results will be compared to those obtained with other algorithms.
The Effect of Mixed Vehicles on Traffic Flow in Two Lane Cellular Automata Model
NASA Astrophysics Data System (ADS)
Jia, Bin; Jiang, Rui; Gao, Zi-You; Zhao, Xiao-Mei
In real traffic, the traffic system is usually composed of different types of vehicles, which have different parameters. How these parameters, especially the lengths of the vehicles, influence the traffic behaviors and transportation capability has seldom been investigated. In this paper, we study the mixed traffic system using the cellular automata traffic flow model. The simulation results show that when the road occupancy rate is large, increasing the fraction of long vehicles can apparently, improve the transportation capability. The influence of slow vehicles fraction on the average velocity of vehicles has been discussed, and it is found that the influences are very different when the difference of vehicle length is considered or not.
NASA Astrophysics Data System (ADS)
Enayatifar, Rasul; Sadaei, Hossein Javedani; Abdullah, Abdul Hanan; Lee, Malrey; Isnin, Ismail Fauzi
2015-08-01
Currently, there are many studies have conducted on developing security of the digital image in order to protect such data while they are sending on the internet. This work aims to propose a new approach based on a hybrid model of the Tinkerbell chaotic map, deoxyribonucleic acid (DNA) and cellular automata (CA). DNA rules, DNA sequence XOR operator and CA rules are used simultaneously to encrypt the plain-image pixels. To determine rule number in DNA sequence and also CA, a 2-dimension Tinkerbell chaotic map is employed. Experimental results and computer simulations, both confirm that the proposed scheme not only demonstrates outstanding encryption, but also resists various typical attacks.
The Design of Fault Tolerant Quantum Dot Cellular Automata Based Logic
NASA Technical Reports Server (NTRS)
Armstrong, C. Duane; Humphreys, William M.; Fijany, Amir
2002-01-01
As transistor geometries are reduced, quantum effects begin to dominate device performance. At some point, transistors cease to have the properties that make them useful computational components. New computing elements must be developed in order to keep pace with Moore s Law. Quantum dot cellular automata (QCA) represent an alternative paradigm to transistor-based logic. QCA architectures that are robust to manufacturing tolerances and defects must be developed. We are developing software that allows the exploration of fault tolerant QCA gate architectures by automating the specification, simulation, analysis and documentation processes.
The Development of Design Tools for Fault Tolerant Quantum Dot Cellular Automata Based Logic
NASA Technical Reports Server (NTRS)
Armstrong, Curtis D.; Humphreys, William M.
2003-01-01
We are developing software to explore the fault tolerance of quantum dot cellular automata gate architectures in the presence of manufacturing variations and device defects. The Topology Optimization Methodology using Applied Statistics (TOMAS) framework extends the capabilities of the A Quantum Interconnected Network Array Simulator (AQUINAS) by adding front-end and back-end software and creating an environment that integrates all of these components. The front-end tools establish all simulation parameters, configure the simulation system, automate the Monte Carlo generation of simulation files, and execute the simulation of these files. The back-end tools perform automated data parsing, statistical analysis and report generation.
Simple and Flexible Self-Reproducing Structures in Asynchronous Cellular Automata and Their Dynamics
NASA Astrophysics Data System (ADS)
Huang, Xin; Lee, Jia; Yang, Rui-Long; Zhu, Qing-Sheng
2013-03-01
Self-reproduction on asynchronous cellular automata (ACAs) has attracted wide attention due to the evident artifacts induced by synchronous updating. Asynchronous updating, which allows cells to undergo transitions independently at random times, might be more compatible with the natural processes occurring at micro-scale, but the dark side of the coin is the increment in the complexity of an ACA in order to accomplish stable self-reproduction. This paper proposes a novel model of self-timed cellular automata (STCAs), a special type of ACAs, where unsheathed loops are able to duplicate themselves reliably in parallel. The removal of sheath cannot only allow various loops with more flexible and compact structures to replicate themselves, but also reduce the number of cell states of the STCA as compared to the previous model adopting sheathed loops [Y. Takada, T. Isokawa, F. Peper and N. Matsui, Physica D227, 26 (2007)]. The lack of sheath, on the other hand, often tends to cause much more complicated interactions among loops, when all of them struggle independently to stretch out their constructing arms at the same time. In particular, such intense collisions may even cause the emergence of a mess of twisted constructing arms in the cellular space. By using a simple and natural method, our self-reproducing loops (SRLs) are able to retract their arms successively, thereby disentangling from the mess successfully.
Nakajima, Kohei; Haruna, Taichi
2011-09-01
In this paper, we propose a new class of cellular automata based on the modification of its state space. It is introduced to model a computation which is exposed to an environment. We formalized the computation as extension and projection processes of its state space and resulting misidentifications of the state. This is motivated to embed the role of an environment into the system itself, which naturally induces self-organized internal perturbations rather than the usual external perturbations. Implementing this structure into the elementary cellular automata, we characterized its effect by means of input entropy and power spectral analysis. As a result, the cellular automata with this structure showed robust class IV behavior and a 1/f power spectrum in a wide range of rule space comparative to the notion of the edge of chaos. PMID:21600265
Stair evacuation simulation based on cellular automata considering evacuees’ walk preferences
NASA Astrophysics Data System (ADS)
Ding, Ning; Zhang, Hui; Chen, Tao; Peter, B. Luh
2015-06-01
As a physical model, the cellular automata (CA) model is widely used in many areas, such as stair evacuation. However, existing CA models do not consider evacuees’ walk preferences nor psychological status, and the structure of the basic model is unapplicable for the stair structure. This paper is to improve the stair evacuation simulation by addressing these issues, and a new cellular automata model is established. Several evacuees’ walk preference and how evacuee’s psychology influences their behaviors are introduced into this model. Evacuees’ speeds will be influenced by these features. To validate this simulation, two fire drills held in two high-rise buildings are video-recorded. It is found that the simulation results are similar to the fire drill results. The structure of this model is simple, and it is easy to further develop and utilize in different buildings with various kinds of occupants. Project supported by the National Basic Research Program of China (Grant No. 2012CB719705) and the National Natural Science Foundation of China (Grant Nos. 91224008, 91024032, and 71373139).
Calibrating Cellular Automata of Land Use/cover Change Models Using a Genetic Algorithm
NASA Astrophysics Data System (ADS)
Mas, J. F.; Soares-Filho, B.; Rodrigues, H.
2015-08-01
Spatially explicit land use / land cover (LUCC) models aim at simulating the patterns of change on the landscape. In order to simulate landscape structure, the simulation procedures of most computational LUCC models use a cellular automata to replicate the land use / cover patches. Generally, model evaluation is based on assessing the location of the simulated changes in comparison to the true locations but landscapes metrics can also be used to assess landscape structure. As model complexity increases, the need to improve calibration and assessment techniques also increases. In this study, we applied a genetic algorithm tool to optimize cellular automata's parameters to simulate deforestation in a region of the Brazilian Amazon. We found that the genetic algorithm was able to calibrate the model to simulate more realistic landscape in term of connectivity. Results show also that more realistic simulated landscapes are often obtained at the expense of the location coincidence. However, when considering processes such as the fragmentation impacts on biodiversity, the simulation of more realistic landscape structure should be preferred to spatial coincidence performance.
NASA Astrophysics Data System (ADS)
Xue, Yuan; Qian, Yong-Sheng; Guang, Xiao-Ping; Zeng, Jun-Wei; Jia, Zhi-Long; Wang, Xin
2013-05-01
With the application of the dynamic control system, Cellular Automata model has become a valued tool for the simulation of human behavior and traffic flow. As an integrated kind of railway signal-control pattern, the four-aspect color light automatic block signaling has accounted for 50% in the signal-control system in China. Thus, it is extremely important to calculate correctly its carrying capacity under the automatic block signaling. Based on this fact the paper proposes a new kind of "cellular automata model" for the four-aspect color light automatic block signaling under different speed states. It also presents rational rules for the express trains with higher speed overtaking trains with lower speed in a same or adjacent section and the departing rules in some intermediate stations. In it, the state of mixed-speed trains running in the section composed of many stations is simulated with CA model, and the train-running diagram is acquired accordingly. After analyzing the relevant simulation results, the needed data are achieved herewith for the variation of section carrying capacity, the average train delay, the train speed with the change of mixed proportion, as well as the distance between the adjacent stations.
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.
Konovalenko, Igor S. Smolin, Alexey Yu. Konovalenko, Ivan S.; Promakhov, Vladimir V.; Psakhie, Sergey G.
2014-11-14
Movable cellular automaton method was used for investigating the mechanical behavior of ceramic composites under uniaxial compression. A 2D numerical model of ceramic composites based on oxides of zirconium and aluminum with different structural parameters was developed using the SEM images of micro-sections of a real composite. The influence of such structural parameters as the geometrical dimensions of layers, inclusions, and their spatial distribution in the sample, the volume content of the composite components and their mechanical properties (as well as the amount of zirconium dioxide that underwent the phase transformation) on the fracture, strength, deformation and dissipative properties was investigated.
Temperature Effects on Olive Fruit Fly Infestation in the FlySim Cellular Automata Model
NASA Astrophysics Data System (ADS)
Bruno, Vincenzo; Baldacchini, Valerio; di Gregorio, Salvatore
FlySim is a Cellular Automata model developed for simulating infestation of olive fruit flies (Bactrocera Oleae) on olive (Olea europaea) groves. The flies move into the groves looking for mature olives where eggs are spawn. This serious agricultural problem is mainly tackled by using chemical agents at the first signs of the infestation, but organic productions with no or few chemicals are strongly requested by the market. Oil made with infested olives is poor in quality, nor olives are suitable for selling in stores. The FlySim model simulates the diffusion of flies looking for mature olives and the growing of flies due to atmospheric conditions. Foreseeing an infestation is the best way to prevent it and to reduce the need of chemicals in agriculture. In this work we investigated the effects of temperature on olive fruit flies and resulting infestation during late spring and summer.
Ca-Pri a Cellular Automata Phenomenological Research Investigation: Simulation Results
NASA Astrophysics Data System (ADS)
Iannone, G.; Troisi, A.
2013-05-01
Following the introduction of a phenomenological cellular automata (CA) model capable to reproduce city growth and urban sprawl, we develop a toy model simulation considering a realistic framework. The main characteristic of our approach is an evolution algorithm based on inhabitants preferences. The control of grown cells is obtained by means of suitable functions which depend on the initial condition of the simulation. New born urban settlements are achieved by means of a logistic evolution of the urban pattern while urban sprawl is controlled by means of the population evolution function. In order to compare model results with a realistic urban framework we have considered, as the area of study, the island of Capri (Italy) in the Mediterranean Sea. Two different phases of the urban evolution on the island have been taken into account: a new born initial growth as induced by geographic suitability and the simulation of urban spread after 1943 induced by the population evolution after this date.
Hologram authentication based on a secure watermarking algorithm using cellular automata.
Hwang, Wen-Jyi; Chan, Hao-Tang; Cheng, Chau-Jern
2014-09-20
A secure watermarking algorithm for hologram authentication is presented in this paper. The algorithm exploits the noise-like feature of holograms to randomly embed a watermark in the domain of the discrete cosine transform with marginal degradation in transparency. The pseudo random number (PRN) generators based on a cellular automata algorithm with asymmetrical and nonlocal connections are used for the random hiding. Each client has its own unique PRN generators for enhancing the watermark security. In the proposed algorithm, watermarks are also randomly generated to eliminate the requirements of prestoring watermarks in the clients and servers. An authentication scheme is then proposed for the algorithm with random watermark generation and hiding. PMID:25322138
NASA Astrophysics Data System (ADS)
Adabi, Sepideh; Adabi, Sahar; Rezaee, Ali
According to the traditional definition of Wireless Sensor Networks (WSNs), static sensors have limited the feasibility of WSNs in some kind of approaches, so the mobility was introduced in WSN. Mobile nodes in a WSN come equipped with battery and from the point of deployment, this battery reserve becomes a valuable resource since it cannot be replenished. Hence, maximizing the network lifetime by minimizing the energy is an important challenge in Mobile WSN. Energy conservation can be accomplished by different approaches. In this paper, we presented an energy conservation solution based on Cellular Automata. The main objective of this solution is based on dynamically adjusting the transmission range and switching between operational states of the sensor nodes.
NASA Astrophysics Data System (ADS)
Kohring, G. A.; Stauffer, D.
Geometric parallelization was tested on the Intel Hypercube with 32 MIMD processors of 1860 type, each with 16 Mbytes of distributed memory. We applied it to Ising models in two and three dimensions as well as to neural networks and two-dimensional hydrodynamic cellular automata. For system sizes suited to this machine, up to 60960*60960 and 1410*1410*1408 Ising spins, we found nearly hundred percent parallel efficiency in spite of the needed inter-processor communications. For small systems, the observed deviations from full efficiency were compared with the scaling concepts of Heermann and Burkitt and of Jakobs and Gerling. For Ising models, we determined the Glauber kinetic exponent z≃2.18 in two dimensions and confirmed the stretched exponential relaxation of the magnetization towards the spontaneous magnetization below Tc. For three dimensions we found z≃2.09 and simple exponential relaxation.
NASA Astrophysics Data System (ADS)
Ren, Gang; Jiang, Hang; Chen, Jingxu; Huang, Zhengfeng; Lu, Lili
2016-06-01
This paper presents a cellular automata (CA) model to elucidate the straight-through movements of the heterogeneous bicycle traffic at signalized intersection. The CA model, via simulation, particularly exposits the dispersion phenomenon existing in the straight-through bicycle traffic. The nonlane-based cycling behavior and diverse bicycle properties are also incorporated in the CA model. A series of simulations are conducted to reveal the travel process, bicycles interaction and influence of the dispersion phenomenon. The simulation results show that the dispersion phenomenon significantly results in more bicycles interactions in terms of spilling maneuvers and overtaking maneuvers during the straight-through movements. Meanwhile, the dispersion phenomenon could contribute to the efficiency of the bicycle traffic, and straight-through bicycles need less time to depart the intersection under the circumstance of dispersion phenomenon. The simulation results are able to provide specific guideline for reasonably utilizing the dispersion phenomenon to improve the operational efficiency of straight-through bicycle traffic.
Emergence of density dynamics by surface interpolation in elementary cellular automata
NASA Astrophysics Data System (ADS)
Seck-Tuoh-Mora, Juan Carlos; Medina-Marin, Joselito; Martínez, Genaro J.; Hernández-Romero, Norberto
2014-04-01
A classic problem in elementary cellular automata (ECAs) is the specification of numerical tools to represent and study their dynamical behaviour. Mean field theory and basins of attraction have been commonly used; however, although the first case gives the long term estimation of density, frequently it does not show an adequate approximation for the step-by-step temporal behaviour; mainly for non-trivial behaviour. In the second case, basins of attraction display a complete representation of the evolution of an ECA, but they are limited up to configurations of 32 cells; and for the same ECA, one can obtain tens of basins to analyse. This paper is devoted to represent the dynamics of density in ECAs for hundreds of cells using only two surfaces calculated by the nearest-neighbour interpolation. A diversity of surfaces emerges in this analysis. Consequently, we propose a surface and histogram based classification for periodic, chaotic and complex ECA.
Conflict game in evacuation process: A study combining Cellular Automata model
NASA Astrophysics Data System (ADS)
Zheng, Xiaoping; Cheng, Yuan
2011-03-01
The game-theoretic approach is an essential tool in the research of conflicts of human behaviors. The aim of this study is to research crowd dynamic conflicts during evacuation processes. By combining a conflict game with a Cellular Automata model, the following factors such as rationality, herding effect and conflict cost are taken into the research on frequency of each strategy of evacuees, and evacuation time. Results from Monte Carlo simulations show that (i) in an emergency condition, rationality leads to “vying” behaviors and inhibited “polite” behavior; (ii) high herding causes a crowd of high rationality (especially in normal circumstances) to become more “vying” in behavior; (iii) the high-rationality crowd is shown to spend more evacuation time than a low-rationality crowd in emergency situations. This study provides a new perspective to understand conflicts in evacuation processes as well as the rationality of evacuees.
Occupants’ behavior of going with the crowd based on cellular automata occupant evacuation model
NASA Astrophysics Data System (ADS)
Zhao, Daoliang; Yang, Lizhong; Li, Jian
2008-06-01
Occupant behavior which is very complex affects evacuation efficiency and route choice a lot. The psychology and behavior of going with the crowd is very common in daily life and also in occupant evacuation. In this paper, a two-dimensional Cellular Automata model is applied to simulate the process of evacuation considering the psychology of going with the crowd with different room structure or occupant density. The psychology of going with the crowd (the abbreviation is GWC) is classified into directional GWC ( DGWC) and spatial GWC ( SGWC). The influence of two such kinds of psychology on occupant evacuation is discussed in order to provide some useful guidance on the emergency management of evacuation.
Fault-tolerance and thermal characteristics of quantum-dot cellular automata devices
NASA Astrophysics Data System (ADS)
Anduwan, G. A.; Padgett, B. D.; Kuntzman, M.; Hendrichsen, M. K.; Sturzu, I.; Khatun, M.; Tougaw, P. D.
2010-06-01
We present fault tolerant properties of various quantum-dot cellular automata (QCA) devices. Effects of temperatures and dot displacements on the operation of the fundamental devices such as a binary wire, logical gates, a crossover, and an exclusive OR (XOR) have been investigated. A Hubbard-type Hamiltonian and intercellular Hartree approximation have been used for modeling, and a uniform random distribution has been implemented for the defect simulations. The breakdown characteristics of all the devices are almost the same except the crossover. Results show that the success of any device is significantly dependent on both the fabrication defects and temperatures. We have observed unique characteristic features of the crossover. It is highly sensitive to defects of any magnitude. Results show that the presence of a crossover in a XOR design is a major factor for its failure. The effects of temperature and defects in the crossover device are pronounced and have significant impact on larger and complicated QCA devices.
Design of Efficient Full Adder in Quantum-Dot Cellular Automata
Sen, Bibhash; Sikdar, Biplab K.
2013-01-01
Further downscaling of CMOS technology becomes challenging as it faces limitation of feature size reduction. Quantum-dot cellular automata (QCA), a potential alternative to CMOS, promises efficient digital design at nanoscale. Investigations on the reduction of QCA primitives (majority gates and inverters) for various adders are limited, and very few designs exist for reference. As a result, design of adders under QCA framework is gaining its importance in recent research. This work targets developing multi-layered full adder architecture in QCA framework based on five-input majority gate proposed here. A minimum clock zone (2 clock) with high compaction (0.01 μm2) for a full adder around QCA is achieved. Further, the usefulness of such design is established with the synthesis of high-level logic. Experimental results illustrate the significant improvements in design level in terms of circuit area, cell count, and clock compared to that of conventional design approaches. PMID:23844385
Modelling the role of nucleation on recrystallization kinetics: A cellular automata approach
NASA Astrophysics Data System (ADS)
Tripathy, Haraprasanna; Rai, Arun Kumar; Hajra, Raj Narayan; Raju, Subramanian; Saibaba, Saroja
2016-05-01
In present study, a two dimensional cellular automata (CA) simulation has been carried out to study the effect of nucleation mode on the kinetics of recrystallization and microstructure evolution in an austenitic stainless steel. Two different nucleation modes i.e. site saturation and continuous nucleation with interface control growth mechanism has been considered in this modified CA algorithm. The observed Avrami exponent for both nucleation modes shows a better agreement with the theoretical predicted values. The site saturated nucleation mode shows a nearly consistent value of Avrami exponent, whereas in the case of continuous nucleation the exponent shows a little variation during transformation. The simulations in the present work can be applied for the optimization of microstructure and properties in austenitic steels.
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.
Scale-invariant cellular automata and self-similar Petri nets
NASA Astrophysics Data System (ADS)
Schaller, M.; Svozil, K.
2009-05-01
Two novel computing models based on an infinite tessellation of space-time are introduced. They consist of recursively coupled primitive building blocks. The first model is a scale-invariant generalization of cellular automata, whereas the second one utilizes self-similar Petri nets. Both models are capable of hypercomputations and can, for instance, “solve” the halting problem for Turing machines. These two models are closely related, as they exhibit a step-by-step equivalence for finite computations. On the other hand, they differ greatly for computations that involve an infinite number of building blocks: the first one shows indeterministic behavior, whereas the second one halts. Both models are capable of challenging our understanding of computability, causality, and space-time.
Non-probabilistic cellular automata-enhanced stereo vision simultaneous localization and mapping
NASA Astrophysics Data System (ADS)
Nalpantidis, Lazaros; Sirakoulis, Georgios Ch; Gasteratos, Antonios
2011-11-01
In this paper, a visual non-probabilistic simultaneous localization and mapping (SLAM) algorithm suitable for area measurement applications is proposed. The algorithm uses stereo vision images as its only input and processes them calculating the depth of the scenery, detecting occupied areas and progressively building a map of the environment. The stereo vision-based SLAM algorithm embodies a stereo correspondence algorithm that is tolerant to illumination differentiations, the robust scale- and rotation-invariant feature detection and matching speeded-up robust features method, a computationally effective v-disparity image calculation scheme, a novel map-merging module, as well as a sophisticated cellular automata-based enhancement stage. A moving robot equipped with a stereo camera has been used to gather image sequences and the system has autonomously mapped and measured two different indoor areas.
Khan, Muhammad Sadiq Ali; Yousuf, Sidrah
2016-03-01
Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each electrical activity during cardiac cycle should be monitor non-invasively for the assessment of "Action Potential" (regular) and "Arrhythmia" (irregular) rhythms. Many heart diseases can easily be examined through Automata model like Cellular Automata concepts. This paper deals with the different states of cardiac rhythms using cellular automata with the comparison of neural network also provides fast and highly effective stimulation for the contraction of cardiac muscles on the Atria in the result of genesis of electrical spark or wave. The specific formulated model named as "States of automaton Proposed Model for CEA (Cardiac Electrical Activity)" by using Cellular Automata Methodology is commonly shows the three states of cardiac tissues conduction phenomena (i) Resting (Relax and Excitable state), (ii) ARP (Excited but Absolutely refractory Phase i.e. Excited but not able to excite neighboring cells) (iii) RRP (Excited but Relatively Refractory Phase i.e. Excited and able to excite neighboring cells). The result indicates most efficient modeling with few burden of computation and it is Action Potential during the pumping of blood in cardiac cycle. PMID:27087101
NASA Astrophysics Data System (ADS)
Afshar, M. H.; Rohani, M.
2012-01-01
In this article, cellular automata based hybrid methods are proposed for the optimal design of sewer networks and their performance is compared with some of the common heuristic search methods. The problem of optimal design of sewer networks is first decomposed into two sub-optimization problems which are solved iteratively in a two stage manner. In the first stage, the pipe diameters of the network are assumed fixed and the nodal cover depths of the network are determined by solving a nonlinear sub-optimization problem. A cellular automata (CA) method is used for the solution of the optimization problem with the network nodes considered as the cells and their cover depths as the cell states. In the second stage, the nodal cover depths calculated from the first stage are fixed and the pipe diameters are calculated by solving a second nonlinear sub-optimization problem. Once again a CA method is used to solve the optimization problem of the second stage with the pipes considered as the CA cells and their corresponding diameters as the cell states. Two different updating rules are derived and used for the CA of the second stage depending on the treatment of the pipe diameters. In the continuous approach, the pipe diameters are considered as continuous variables and the corresponding updating rule is derived mathematically from the original objective function of the problem. In the discrete approach, however, an adhoc updating rule is derived and used taking into account the discrete nature of the pipe diameters. The proposed methods are used to optimally solve two sewer network problems and the results are presented and compared with those obtained by other methods. The results show that the proposed CA based hybrid methods are more efficient and effective than the most powerful search methods considered in this work.
Takesue, Shinji )
1989-08-01
This is the first part of a series devoted to the study of thermodynamic behavior of large dynamical systems with the use of a family of full-discrete and conservative models named elementary reversible cellular automata (ERCAs). In this paper, basic properties such as conservation laws and phase space structure are investigated in preparation for the later studies. ERCAs are a family of one-dimensional reversible cellular automata having two Boolean variables on each site. Reflection and Boolean conjugation symmetries divide them into 88 equivalence classes. For each rule, additive conserved quantities written in a certain form are regarded as a kind of energy, if they exist. By the aid of the discreteness of the variables, every ERCA satisfies the Liouville theorem or the preservation of phase space volume. Thus, if an energy exists in the above sense, statistical mechanics of the model can formally be constructed. If a locally defined quantity is conserved, however, it prevents the realization of statistical mechanics. The existence of such a quantity is examined for each class and a number of rules which have at least one energy but no local conservation laws are selected as hopeful candidates for the realization of thermodynamic behavior. In addition, the phase space structure of ERCAs is analyzed by enumerating cycles exactly in the phase space for systems of comparatively small sizes. As a result, it is revealed that a finite ERCA is not ergodic, that is, a large number of orbits coexist on an energy surface. It is argued that this fact does not necessarily mean the failure of thermodynamic behavior on the basis of an analogy with the ergodic nature of infinite systems.
Raines, G.L.; Zientek, M.L.; Causey, J.D.; Boleneus, D.E.
2002-01-01
For public land management in Idaho and western Montana, the U.S. Forest Service (USFS) has requested that the U.S. Geological Survey (USGS) predict where mineral-related activity will occur in the next decade. Cellular automata provide an approach to simulation of this human activity. Cellular automata (CA) are defined by an array of cells, which evolve by a simple transition rule, the automaton. Based on exploration trends, we assume that future exploration will focus in areas of past exploration. Spatial-temporal information about mineral-related activity, that is permits issued by USFS and Bureau of Land Management (BLM) in the last decade, and spatial information about undiscovered resources, provide a basis to calibrate a CA. The CA implemented is a modified annealed voting rule that simulates mineral-related activity with spatial and temporal resolution of 1 mi2 and 1 year based on activity from 1989 to 1998. For this CA, the state of the economy and exploration technology is assumed constant for the next decade. The calibrated CA reproduces the 1989-1998-permit activity with an agreement of 94%, which increases to 98% within one year. Analysis of the confusion matrix and kappa correlation statistics indicates that the CA underestimates high activity and overestimates low activity. Spatially, the major differences between the actual and calculated activity are that the calculated activity occurs in a slightly larger number of small patches and is slightly more uneven than the actual activity. Using the calibrated CA in a Monte Carlo simulation projecting from 1998 to 2010, an estimate of the probability of mineral activity shows high levels of activity in Boise, Caribou, Elmore, Lincoln, and western Valley counties in Idaho and Beaverhead, Madison, and Stillwater counties in Montana, and generally low activity elsewhere. ?? 2002 International Association for Mathematical Geology.
A Cellular Automata Based Model for Simulating Surface Hydrological Processes in Catchments
NASA Astrophysics Data System (ADS)
Shao, Qi; Baumgartl, Thomas; Huang, Longbin; Weatherley, Dion
2014-05-01
The Runoff Model Based on Cellular Automata (RunCA) has been developed to simulate the surface hydrological processes at the catchment scale by integrating basic cellular automata (CA) rules with fundamental measureable hydraulic properties. In this model, a two-dimensional lattice composed of a series of rectangular cells was employed to cover the study area. Runoff production within each cell was simulated by determining its water depth based on the rainfall, interception, infiltration and the balance between inflows and outflows. Particularly different infiltration equations were incorporated to make the model applicable for both single rainfall event (short term simulation) and multiple rainfall events (long term simulation). The distribution of water flow among cells was determined by applying CA transition rules based on the improved minimization-of-difference algorithm and the calculated spatially and temporally varied flow velocities according to the Manning's equation. RunCA was tested and validated at two catchments (Pine Glen Basin and Snow Shoe Basin, USA) with data taken from literature. The predicted hydrographs agreed well with the measured results. Simulated flow maps also demonstrated the model capability in capturing both the spatial and temporal variations in the runoff process. Model sensitivity analysis results showed that the simulated hydrographs were mostly influenced by the input parameters that represent the final steady infiltration rate, as well as the model settings of time step and cell size. Compared to some conventional distributed hydrologic models that calculate the runoff routing process by solving complex continuity equations, this model integrates a novel method and is expected to be more computationally efficient as it is based on simple CA transition rules when determining the flow distribution.
RunCA: A cellular automata model for simulating surface runoff at different scales
NASA Astrophysics Data System (ADS)
Shao, Qi; Weatherley, Dion; Huang, Longbin; Baumgartl, Thomas
2015-10-01
The Runoff Model Based on Cellular Automata (RunCA) has been developed to simulate surface runoff at different scales by integrating basic cellular automata (CA) rules with fundamental measureable hydraulic properties. In this model, a two-dimensional lattice composed of a series of rectangular cells was employed to cover the study area. Runoff production within each cell was simulated by determining the cell state (height) that consists of both cell elevation and water depth. The distribution of water flow among cells was determined by applying CA transition rules based on the minimization-of-difference algorithm and the calculated spatially varied flow velocities. RunCA was verified and validated by three steps. Good agreement with the analytical solution was achieved under simplified conditions in the first step. Then, results from runoff experiments on small laboratory plots (2 m × 1 m) showed that the model was able to well predict the hydrographs, with the mean Nash-Sutcliffe efficiency greater than 0.90. RunCA was also applied to a large scale site (Pine Glen Basin, USA) with data taken from literature. The predicted hydrograph agreed well with the measured results. Simulated flow maps in this basin also demonstrated the model capability in capturing both the spatial and temporal variations in the runoff process. Model sensitivity analysis results showed that the calculated total runoff and total infiltration were most sensitive to the input parameters representing the final steady infiltration rate at both scales. The Manning's roughness coefficient and the setting of cell size did not affect the results much at the small plot scale, but had large influences at the large basin scale.
Phenomenological study of irregular cellular automata based on Lyapunov exponents and Jacobians.
Baetens, Jan M; De Baets, Bernard
2010-09-01
Originally, cellular automata (CA) have been defined upon regular tessellations of the n-dimensional Euclidean space, while CA on irregular tessellations have received only little attention from the scientific community, notwithstanding serious shortcomings are associated with the former manner of subdividing Rn. In this paper we present a profound phenomenological study of two-state, two-dimensional irregular CA from a dynamical systems viewpoint. We opted to exploit properly defined quantitative measures instead of resorting to qualitative methods for discriminating between behavioral classes. As such, we employ Lyapunov exponents, measuring the divergence rate of close trajectories in phase space, and Jacobians, formulated using Boolean derivatives and expressing the sensitivity of a cellular automaton to its inputs. Both are stated for two-state CA on irregular tessellations, enabling us to characterize these discrete dynamical systems, and advancing us to propose a classification scheme for this CA family. In addition, a relationship between these quantitative measures is established in extension of the insights already developed for the classical CA paradigm. Finally, we discuss the repercussions on the CA dynamics that arise when the geometric variability of the spatial entities is taken into account during the CA simulation. PMID:20887052
Modelling approaches for coastal simulation based on cellular automata: the need and potential.
Dearing, J A; Richmond, N; Plater, A J; Wolf, J; Prandle, D; Coulthard, T J
2006-04-15
The paper summarizes the theoretical and practical needs for cellular automata (CA)-type models in coastal simulation, and describes early steps in the development of a CA-based model for estuarine sedimentation. It describes the key approaches and formulae used for tidal, wave and sediment processes in a prototype integrated cellular model for coastal simulation designed to simulate estuary sedimentary responses during the tidal cycle in the short-term and climate driven changes in sea-level in the long-term. Results of simple model testing for both one-dimensional and two-dimensional models, and a preliminary parameterization for the Blackwater Estuary, UK, are shown. These reveal a good degree of success in using a CA-type model for water and sediment transport as a function of water level and wave height, but tidal current vectors are not effectively simulated in the approach used. The research confirms that a CA-type model for the estuarine sediment system is feasible, with a real prospect for coupling to existing catchment and nearshore beach/cliff models to produce integrated coastal simulators of sediment response to climate, sea-level change and human actions. PMID:16537155
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.
NASA Astrophysics Data System (ADS)
Wang, Xianmin; Niu, Ruiqing; Wu, Ke
2011-07-01
Remote sensing provides a new idea and an advanced method for lithology identification, but lithology identification by remote sensing is quite difficult because 1. the disciplines of lithology identification in a concrete region are often quite different from the experts' experience; 2. in the regions with flourishing vegetation, lithology information is poor, so it is very difficult to identify the lithologies by remote sensing images. At present, the studies on lithology identification by remote sensing are primarily conducted on the regions with low vegetation coverage and high rock bareness. And there is no mature method of lithology identification in the regions with flourishing vegetation. Traditional methods lacking in the mining and extraction of the various complicated lithology information from a remote sensing image, often need much manual intervention and possess poor intelligence and accuracy. An intelligent method proposed in this paper for lithology identification based on support vector machine (SVM) and adaptive cellular automata (ACA) is expected to solve the above problems. The method adopted Landsat-7 ETM+ images and 1:50000 geological map as the data origins. It first derived the lithology identification factors on three aspects: 1. spectra, 2. texture and 3. vegetation cover. Second, it plied the remote sensing images with the geological map and established the SVM to obtain the transition rules according to the factor values of the samples. Finally, it established an ACA model to intelligently identify the lithologies according to the transition and neighborhood rules. In this paper an ACA model is proposed and compared with the traditional one. Results of 2 real-world examples show that: 1. The SVM-ACA method obtains a good result of lithology identification in the regions with flourishing vegetation; 2. it possesses high accuracies of lithology identification (with the overall accuracies of 92.29% and 85.54%, respectively, in the two
Moustafa, Ahmed; Younes, Ahmed; Hassan, Yasser F
2015-01-01
Quantum-dot cellular automata (QCA) are nanoscale digital logic constructs that use electrons in arrays of quantum dots to carry out binary operations. In this paper, a basic building block for QCA will be proposed. The proposed basic building block can be customized to implement classical gates, such as XOR and XNOR gates, and reversible gates, such as CNOT and Toffoli gates, with less cell count and/or better latency than other proposed designs. PMID:26345412
Moustafa, Ahmed; Younes, Ahmed; Hassan, Yasser F.
2015-01-01
Quantum-dot cellular automata (QCA) are nanoscale digital logic constructs that use electrons in arrays of quantum dots to carry out binary operations. In this paper, a basic building block for QCA will be proposed. The proposed basic building block can be customized to implement classical gates, such as XOR and XNOR gates, and reversible gates, such as CNOT and Toffoli gates, with less cell count and/or better latency than other proposed designs. PMID:26345412
Quasi-classical modeling of molecular quantum-dot cellular automata multidriver gates
2012-01-01
Molecular quantum-dot cellular automata (mQCA) has received considerable attention in nanoscience. Unlike the current-based molecular switches, where the digital data is represented by the on/off states of the switches, in mQCA devices, binary information is encoded in charge configuration within molecular redox centers. The mQCA paradigm allows high device density and ultra-low power consumption. Digital mQCA gates are the building blocks of circuits in this paradigm. Design and analysis of these gates require quantum chemical calculations, which are demanding in computer time and memory. Therefore, developing simple models to probe mQCA gates is of paramount importance. We derive a semi-classical model to study the steady-state output polarization of mQCA multidriver gates, directly from the two-state approximation in electron transfer theory. The accuracy and validity of this model are analyzed using full quantum chemistry calculations. A complete set of logic gates, including inverters and minority voters, are implemented to provide an appropriate test bench in the two-dot mQCA regime. We also briefly discuss how the QCADesigner tool could find its application in simulation of mQCA devices. PMID:22647345
NASA Astrophysics Data System (ADS)
Ding, H. L.; He, Y. Z.; Liu, L. F.; Ding, W. J.
2006-08-01
The microstructure and morphology evolution of grain growth were studied by 3D simulation using the cellular automata (CA) model based on the lowest-energy principle. In the present CA model, the transition of cells during the grain growth has a typical physical meaning due to the application of the lowest-energy principle. The results show that the kinetics of grain growth follows Burke equation with the growth exponent as 2. The average number of grain faces is 13.6 and the highest frequency of grain faces is 10 faces. The grain size distribution follows Weibull function. The relationship between the number of faces of a grain and the average number of faces of its adjacent grains follows the Aboav-Weaire law. There is a correlation between the topologies of the simulated 2D and 3D grain growth. The average number of sides per face for all grains is 5.65 and the average number of sides per face is about equal to 6 when the grain aces is larger than 35.
A cellular automata model for avascular solid tumor growth under the effect of therapy
NASA Astrophysics Data System (ADS)
Reis, E. A.; Santos, L. B. L.; Pinho, S. T. R.
2009-04-01
Tumor growth has long been a target of investigation within the context of mathematical and computer modeling. The objective of this study is to propose and analyze a two-dimensional stochastic cellular automata model to describe avascular solid tumor growth, taking into account both the competition between cancer cells and normal cells for nutrients and/or space and a time-dependent proliferation of cancer cells. Gompertzian growth, characteristic of some tumors, is described and some of the features of the time-spatial pattern of solid tumors, such as compact morphology with irregular borders, are captured. The parameter space is studied in order to analyze the occurrence of necrosis and the response to therapy. Our findings suggest that transitions exist between necrotic and non-necrotic phases (no-therapy cases), and between the states of cure and non-cure (therapy cases). To analyze cure, the control and order parameters are, respectively, the highest probability of cancer cell proliferation and the probability of the therapeutic effect on cancer cells. With respect to patterns, it is possible to observe the inner necrotic core and the effect of the therapy destroying the tumor from its outer borders inwards.
Setny, Piotr; Zacharias, Martin
2010-07-01
A simple, semiheuristic solvation model based on a discrete, BCC grid of solvent cells has been presented. The model utilizes a mean field approach for the calculation of solute-solvent and solvent-solvent interaction energies and a cellular automata based algorithm for the prediction of solvent distribution in the presence of solute. The construction of the effective Hamiltonian for a solvent cell provides an explicit coupling between orientation-dependent water-solute electrostatic interactions and water-water hydrogen bonding. The water-solute dispersion interaction is also explicitly taken into account. The model does not depend on any arbitrary definition of the solute-solvent interface nor does it use a microscopic surface tension for the calculation of nonpolar contributions to the hydration free energies. It is demonstrated that the model provides satisfactory predictions of hydration free energies for drug-like molecules and is able to reproduce the distribution of buried water molecules within protein structures. The model is computationally efficient and is applicable to arbitrary molecules described by atomistic force field. PMID:20552986
The Cellular Automata for modelling of spreading of lava flow on the earth surface
NASA Astrophysics Data System (ADS)
Jarna, A.
2012-12-01
Volcanic risk assessment is a very important scientific, political and economic issue in densely populated areas close to active volcanoes. Development of effective tools for early prediction of a potential volcanic hazard and management of crises are paramount. However, to this date volcanic hazard maps represent the most appropriate way to illustrate the geographical area that can potentially be affected by a volcanic event. Volcanic hazard maps are usually produced by mapping out old volcanic deposits, however dynamic lava flow simulation gaining popularity and can give crucial information to corroborate other methodologies. The methodology which is used here for the generation of volcanic hazard maps is based on numerical simulation of eruptive processes by the principle of Cellular Automata (CA). The python script is integrated into ArcToolbox in ArcMap (ESRI) and the user can select several input and output parameters which influence surface morphology, size and shape of the flow, flow thickness, flow velocity and length of lava flows. Once the input parameters are selected, the software computes and generates hazard maps on the fly. The results can be exported to Google Maps (.klm format) to visualize the results of the computation. For validation of the simulation code are used data from a real lava flow. Comparison of the simulation results with real lava flows mapped out from satellite images will be presented.
The cellular automata for modelling of spreading of lava flow on the earth surface
NASA Astrophysics Data System (ADS)
Jarna, Alexandra; Cirbus, Juraj
2013-04-01
Volcanic risk assessment is a very important scientific, political and economic issue in densely populated areas close to active volcanoes. Development of effective tools for early prediction of a potential volcanic hazard and management of crises are paramount. However, to this date volcanic hazard maps represent the most appropriate way to illustrate the geographical area that can potentially be affected by a volcanic event. Volcanic hazard maps are usually produced by mapping out old volcanic deposits, however dynamic lava flow simulation gaining popularity and can give crucial information to corroborate other methodologies. The methodology which is used here for the generation of volcanic hazard maps is based on numerical simulation of eruptive processes by the principle of Cellular Automata (CA). The python script is integrated into ArcToolbox in ArcMap (ESRI) and the user can select several input and output parameters which influence surface morphology, size and shape of the flow, flow thickness, flow velocity and length of lava flows. Once the input parameters are selected, the software computes and generates hazard maps on the fly. The results can be exported to Google Maps (.klm format) to visualize the results of the computation. For validation of the simulation code are used data from a real lava flow.
Dynamics of the HIV infection under antiretroviral therapy: A cellular automata approach
NASA Astrophysics Data System (ADS)
González, Ramón E. R.; Coutinho, Sérgio; Zorzenon dos Santos, Rita Maria; de Figueirêdo, Pedro Hugo
2013-10-01
The dynamics of human immunodeficiency virus infection under antiretroviral therapy is investigated using a cellular automata model where the effectiveness of each drug is self-adjusted by the concentration of CD4+ T infected cells present at each time step. The effectiveness of the drugs and the infected cell concentration at the beginning of treatment are the control parameters of the cell population’s dynamics during therapy. The model allows describing processes of mono and combined therapies. The dynamics that emerges from this model when considering combined antiretroviral therapies reproduces with fair qualitative agreement the phases and different time scales of the process. As observed in clinical data, the results reproduce the significant decrease in the population of infected cells and a concomitant increase of the population of healthy cells in a short timescale (weeks) after the initiation of treatment. Over long time scales, early treatment with potent drugs may lead to undetectable levels of infection. For late treatment or treatments starting with a low density of CD4+ T healthy cells it was observed that the treatment may lead to a steady state in which the T cell counts are above the threshold associated with the onset of AIDS. The results obtained are validated through comparison to available clinical trial data.
Takada, Ryu; Munetaka, Daigo; Kobayashi, Shoji; Suemitsu, Yoshikazu; Nara, Shigetoshi
2007-09-01
Chaotic dynamics in a recurrent neural network model and in two-dimensional cellular automata, where both have finite but large degrees of freedom, are investigated from the viewpoint of harnessing chaos and are applied to motion control to indicate that both have potential capabilities for complex function control by simple rule(s). An important point is that chaotic dynamics generated in these two systems give us autonomous complex pattern dynamics itinerating through intermediate state points between embedded patterns (attractors) in high-dimensional state space. An application of these chaotic dynamics to complex controlling is proposed based on an idea that with the use of simple adaptive switching between a weakly chaotic regime and a strongly chaotic regime, complex problems can be solved. As an actual example, a two-dimensional maze, where it should be noted that the spatial structure of the maze is one of typical ill-posed problems, is solved with the use of chaos in both systems. Our computer simulations show that the success rate over 300 trials is much better, at least, than that of a random number generator. Our functional simulations indicate that both systems are almost equivalent from the viewpoint of functional aspects based on our idea, harnessing of chaos. PMID:19003512
Cellular Automata Modeling of Decarburization of Metal Droplets in Basic Oxygen Steelmaking
NASA Astrophysics Data System (ADS)
Ankit; Kundu, T. K.
2016-02-01
In steelmaking, a supersonic jet is blown over the bath to refine the hot metal to produce steel. The refining process primarily consists of removal of impurities from the hot metal to a permissible level. The impact of oxygen jet on the surface of the hot metal bath results in ejection of droplets, which mix with slag and form emulsion. The formed emulsion plays an important role in refining reactions kinetics and understanding of this process is required todevelopimproved process control model for the steel industry. In this paper, cellular automata technique has been explored to simulate decarburization in emulsion caused by interfacial reactions between the metal droplets and slag. In the course of the work, a framework has also been developed to quantify the contribution of carbon monoxide, generated by decarburization, in bloating of metal droplets and formation of halo around the droplets. The model has incorporated diffusion and decarburization reaction based on probabilities to study the evolution of the system. Simulations with varying parameters have been performed and decarburization trends obtained are comparable with the experimentally determined data reported in literatures.
Electrical substation service-area estimation using Cellular Automata: An initial report
Fenwick, J.W.; Dowell, L.J.
1998-07-01
The service areas for electric power substations can be estimated using a Cellular Automata (CA) model. The CA model is a discrete, iterative process whereby substations acquire service area by claiming neighboring cells. The service area expands from a substation until a neighboring substation service area is met or the substation`s total capacity or other constraints are reached. The CA-model output is dependent on the rule set that defines cell interactions. The rule set is based on a hierarchy of quantitative metrics that represent real-world factors such as land use and population density. Together, the metrics determine the rate of cell acquisition and the upper bound for service area size. Assessing the CA-model accuracy requires comparisons to actual service areas. These actual service areas can be extracted from distribution maps. Quantitative assessment of the CA-model accuracy can be accomplished by a number of methods. Some are as simple as finding the percentage of cells predicted correctly, while others assess a penalty based on the distance from an incorrectly predicted cell to its correct service area. This is an initial report of a work in progress.
Accurate reliability analysis method for quantum-dot cellular automata circuits
NASA Astrophysics Data System (ADS)
Cui, Huanqing; Cai, Li; Wang, Sen; Liu, Xiaoqiang; Yang, Xiaokuo
2015-10-01
Probabilistic transfer matrix (PTM) is a widely used model in the reliability research of circuits. However, PTM model cannot reflect the impact of input signals on reliability, so it does not completely conform to the mechanism of the novel field-coupled nanoelectronic device which is called quantum-dot cellular automata (QCA). It is difficult to get accurate results when PTM model is used to analyze the reliability of QCA circuits. To solve this problem, we present the fault tree models of QCA fundamental devices according to different input signals. After that, the binary decision diagram (BDD) is used to quantitatively investigate the reliability of two QCA XOR gates depending on the presented models. By employing the fault tree models, the impact of input signals on reliability can be identified clearly and the crucial components of a circuit can be found out precisely based on the importance values (IVs) of components. So this method is contributive to the construction of reliable QCA circuits.
Periodic forcing in a three-level cellular automata model for a vector-transmitted disease
NASA Astrophysics Data System (ADS)
Santos, L. B. L.; Costa, M. C.; Pinho, S. T. R.; Andrade, R. F. S.; Barreto, F. R.; Teixeira, M. G.; Barreto, M. L.
2009-07-01
A periodically forced two-dimensional cellular automata model is used to reproduce and analyze the complex spatiotemporal patterns observed in the transmission of vector infectious diseases. The system, which comprises three population levels, is introduced to describe complex features of the dynamics of the vector-transmitted dengue epidemics, known to be very sensitive to seasonal variables. The three coupled levels represent the human, the adult, and immature vector populations. The dynamics includes external seasonality forcing, human and mosquito mobility, and vector control effects. The model parameters, even if bounded to well-defined intervals obtained from reported data, can be selected to reproduce specific epidemic outbursts. In the current study, explicit results are obtained by comparison with actual data retrieved from the time series of dengue epidemics in two cities in Brazil. The results show fluctuations that are not captured by mean-field models. It also reveals the qualitative behavior of the spatiotemporal patterns of the epidemics. In the extreme situation of the absence of external periodic drive, the model predicts a completely distinct long-time evolution. The model is robust in the sense that it is able to reproduce the time series of dengue epidemics of different cities, provided that the forcing term takes into account the local rainfall modulation. Finally, an analysis is provided of the effect of the dependence between epidemics threshold and vector control actions, both in the presence and absence of human mobility factor.
Bennett clocking of quantum-dot cellular automata and the limits to binary logic scaling
NASA Astrophysics Data System (ADS)
Lent, Craig S.; Liu, Mo; Lu, Yuhui
2006-08-01
We examine power dissipation in different clocking schemes for molecular quantum-dot cellular automata (QCA) circuits. 'Landauer clocking' involves the adiabatic transition of a molecular cell from the null state to an active state carrying data. Cell layout creates devices which allow data in cells to interact and thereby perform useful computation. We perform direct solutions of the equation of motion for the system in contact with the thermal environment and see that Landauer's Principle applies: one must dissipate an energy of at least kBT per bit only when the information is erased. The ideas of Bennett can be applied to keep copies of the bit information by echoing inputs to outputs, thus embedding any logically irreversible circuit in a logically reversible circuit, at the cost of added circuit complexity. A promising alternative which we term 'Bennett clocking' requires only altering the timing of the clocking signals so that bit information is simply held in place by the clock until a computational block is complete, then erased in the reverse order of computation. This approach results in ultralow power dissipation without additional circuit complexity. These results offer a concrete example in which to consider recent claims regarding the fundamental limits of binary logic scaling.
NASA Astrophysics Data System (ADS)
Jokar Arsanjani, Jamal; Helbich, Marco; Kainz, Wolfgang; Darvishi Boloorani, Ali
2013-04-01
This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-economic variables dealing with urban sprawl were operationalised to create a probability surface of spatiotemporal states of built-up land use for the years 2006, 2016, and 2026. For validation, the model was evaluated by means of relative operating characteristic values for different sets of variables. The approach was calibrated for 2006 by cross comparing of actual and simulated land use maps. The achieved outcomes represent a match of 89% between simulated and actual maps of 2006, which was satisfactory to approve the calibration process. Thereafter, the calibrated hybrid approach was implemented for forthcoming years. Finally, future land use maps for 2016 and 2026 were predicted by means of this hybrid approach. The simulated maps illustrate a new wave of suburban development in the vicinity of Tehran at the western border of the metropolis during the next decades.
Studies of vehicle lane-changing to avoid pedestrians with cellular automata
NASA Astrophysics Data System (ADS)
Li, Xiang; Sun, Jian-Qiao
2015-11-01
This paper presents studies of interactions between vehicles and crossing pedestrians. A cellular automata system model of the traffic is developed, which includes a number of subsystem models such as the single-lane vehicle model, pedestrian model, interaction model and lane-changing model. The random street crossings of pedestrians are modeled as a Poisson process. The drivers of the passing vehicles are assumed to follow a safety-rule in order not to hit the pedestrians. The results of both single and multiple car simulations are presented. We have found that in general, the traffic can benefit from vehicle lane-changing to avoid road-crossing pedestrians. The traffic flow and average vehicle speed can be increased, which leads to higher traffic efficiency. The interactions between vehicles and pedestrians are reduced, which results in shorter vehicle decelerating time due to pedestrians and less switches of the driving mode, thus leads to the better energy economy. The traffic safety can be improved in the perspective of both vehicles and pedestrians. Finally, pedestrians can cross road faster. The negative effect of lane-changing is that pedestrians have to stay longer between the lanes in the crossing.
Quasi-classical modeling of molecular quantum-dot cellular automata multidriver gates.
Rahimi, Ehsan; Nejad, Shahram Mohammad
2012-01-01
Molecular quantum-dot cellular automata (mQCA) has received considerable attention in nanoscience. Unlike the current-based molecular switches, where the digital data is represented by the on/off states of the switches, in mQCA devices, binary information is encoded in charge configuration within molecular redox centers. The mQCA paradigm allows high device density and ultra-low power consumption. Digital mQCA gates are the building blocks of circuits in this paradigm. Design and analysis of these gates require quantum chemical calculations, which are demanding in computer time and memory. Therefore, developing simple models to probe mQCA gates is of paramount importance. We derive a semi-classical model to study the steady-state output polarization of mQCA multidriver gates, directly from the two-state approximation in electron transfer theory. The accuracy and validity of this model are analyzed using full quantum chemistry calculations. A complete set of logic gates, including inverters and minority voters, are implemented to provide an appropriate test bench in the two-dot mQCA regime. We also briefly discuss how the QCADesigner tool could find its application in simulation of mQCA devices. PMID:22647345
NASA Astrophysics Data System (ADS)
Dolce, Donatello; Perali, Andrea
2015-07-01
Cellular Automata (CA) are represented at an effective level as intrinsic periodic phenomena, classical in the essence, reproducing the complete coherence (perfect recurrences) associated to pure quantum behaviours in condensed matter systems. By means of this approach it is possible to obtain a consistent, novel derivation of SuperConductivity (SC) essential phenomenology and of the peculiar quantum behaviour of electrons in graphene physics and Carbon Nanotubes (CNs), in which electrons cyclic dynamics simulate CA. In this way we will derive, from classical arguments, the essential electronic properties of these — or similar — graphene systems, such as energy bands and density of states. Similarly, in the second part of the paper, we will derive the fundamental phenomenology of SC by means of fundamental quantum dynamics and geometrical considerations, directly derived from the CA evolution law, rather than on empirical microscopical characteristics of the materials as in the standard approaches. This allows for a novel heuristic interpretation of the related gauge symmetry breaking and of the occurrence of high temperature superconductivity by means of simple considerations on the competition of quantum recurrence and thermal noise.
A solution to the biodiversity paradox by logical deterministic cellular automata.
Kalmykov, Lev V; Kalmykov, Vyacheslav L
2015-06-01
The paradox of biological diversity is the key problem of theoretical ecology. The paradox consists in the contradiction between the competitive exclusion principle and the observed biodiversity. The principle is important as the basis for ecological theory. On a relatively simple model we show a mechanism of indefinite coexistence of complete competitors which violates the known formulations of the competitive exclusion principle. This mechanism is based on timely recovery of limiting resources and their spatio-temporal allocation between competitors. Because of limitations of the black-box modeling there was a problem to formulate the exclusion principle correctly. Our white-box multiscale model of two-species competition is based on logical deterministic individual-based cellular automata. This approach provides an automatic deductive inference on the basis of a system of axioms, and gives a direct insight into mechanisms of the studied system. It is one of the most promising methods of artificial intelligence. We reformulate and generalize the competitive exclusion principle and explain why this formulation provides a solution of the biodiversity paradox. In addition, we propose a principle of competitive coexistence. PMID:25980478
A cellular automata-based model of Earth's magnetosphere in relation with Dst index
NASA Astrophysics Data System (ADS)
Banerjee, Adrija; Bej, Amaresh; Chatterjee, T. N.
2015-05-01
The disturbance storm time (Dst) index, a measure of the strength of a geomagnetic storm, is difficult to predict by some conventional methods due to its abstract structural complexity and stochastic nature though a timely geomagnetic storm warning could save society from huge economic losses and hours of related hazards. Self-organized criticality and the concept of many-body interactive nonlinear system can be considered an explanation for the fundamental mechanism of the nonstationary geomagnetic disturbances controlled by the perturbed interplanetary conditions. The present paper approaches this natural phenomena by a sandpile-like cellular automata-based model of magnetosphere, taking the real-time solar wind and both the direction and magnitude of the B-Z component of the real-time interplanetary magnetic field as the system-controlling input parameters. Moreover, three new parameters had been introduced in the model which modify the functional relationships between the variables and regulate the dynamical behavior of the model to closely approximate the actual geomagnetic fluctuations. The statistical similarities between the dynamics of the model and that of the actual Dst index series during the entire 22nd solar cycle signifies the acceptability of the model.
Cellular automata-based modelling and simulation of biofilm structure on multi-core computers.
Skoneczny, Szymon
2015-01-01
The article presents a mathematical model of biofilm growth for aerobic biodegradation of a toxic carbonaceous substrate. Modelling of biofilm growth has fundamental significance in numerous processes of biotechnology and mathematical modelling of bioreactors. The process following double-substrate kinetics with substrate inhibition proceeding in a biofilm has not been modelled so far by means of cellular automata. Each process in the model proposed, i.e. diffusion of substrates, uptake of substrates, growth and decay of microorganisms and biofilm detachment, is simulated in a discrete manner. It was shown that for flat biofilm of constant thickness, the results of the presented model agree with those of a continuous model. The primary outcome of the study was to propose a mathematical model of biofilm growth; however a considerable amount of focus was also placed on the development of efficient algorithms for its solution. Two parallel algorithms were created, differing in the way computations are distributed. Computer programs were created using OpenMP Application Programming Interface for C++ programming language. Simulations of biofilm growth were performed on three high-performance computers. Speed-up coefficients of computer programs were compared. Both algorithms enabled a significant reduction of computation time. It is important, inter alia, in modelling and simulation of bioreactor dynamics. PMID:26606102
NASA Astrophysics Data System (ADS)
Egger, Jan; Nimsky, Christopher
2016-03-01
Due to the aging population, spinal diseases get more and more common nowadays; e.g., lifetime risk of osteoporotic fracture is 40% for white women and 13% for white men in the United States. Thus the numbers of surgical spinal procedures are also increasing with the aging population and precise diagnosis plays a vital role in reducing complication and recurrence of symptoms. Spinal imaging of vertebral column is a tedious process subjected to interpretation errors. In this contribution, we aim to reduce time and error for vertebral interpretation by applying and studying the GrowCut - algorithm for boundary segmentation between vertebral body compacta and surrounding structures. GrowCut is a competitive region growing algorithm using cellular automata. For our study, vertebral T2-weighted Magnetic Resonance Imaging (MRI) scans were first manually outlined by neurosurgeons. Then, the vertebral bodies were segmented in the medical images by a GrowCut-trained physician using the semi-automated GrowCut-algorithm. Afterwards, results of both segmentation processes were compared using the Dice Similarity Coefficient (DSC) and the Hausdorff Distance (HD) which yielded to a DSC of 82.99+/-5.03% and a HD of 18.91+/-7.2 voxel, respectively. In addition, the times have been measured during the manual and the GrowCut segmentations, showing that a GrowCutsegmentation - with an average time of less than six minutes (5.77+/-0.73) - is significantly shorter than a pure manual outlining.
Modelling the shrub encroachment in a grassland with a Cellular Automata Model
NASA Astrophysics Data System (ADS)
Caracciolo, D.; Noto, L. V.; Istanbulluoglu, E.
2014-09-01
Arid and semi-arid grasslands of southwestern North America have changed dramatically over the last 150 years as a result of shrub encroachment, i.e. the increase in density, cover and biomass of indigenous shrubby plants in grasslands. Numerous studies have documented the expansion of shrublands in the southwestern American grasslands; in particular shrub encroachment has occurred strongly in part of the northern Chihuahuan desert since 1860. This encroachment has been simulated using an ecohydrological Cellular Automata model, CATGraSS. It is a spatially distributed model driven by spatially explicit irradiance and runs on a fine-resolution gridded domain. Plant competition is modelled by keeping track of mortality and establishment of plants; both are calculated probabilistically based on soil moisture stress. For this study CATGraSS has been improved with a stochastic fire module and a grazing function. The model has been implemented in a small area in Sevilleta National Wildlife Refuge (SNWR), characterized by two vegetation types (grass savanna and creosote bush shrub), considering as encroachment causes the fire return period increase, the grazing increase, the seed dispersal caused by animals, the role of wind direction and plant type competition. The model is able to reproduce the encroachment that has occurred in SNWR, simulating an increase of the shrub from 2% in 1860 to the current shrub percentage, 42%, and highlighting among the most influential factors the reduced fire frequency and the increased grazing intensity.
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.
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.
Nanopatterned graphene quantum dots as building blocks for quantum cellular automata
NASA Astrophysics Data System (ADS)
Wang, Z. F.; Liu, Feng
2011-10-01
Quantum cellular automata (QCA) is an innovative approach that incorporates quantum entities in classical computation processes. Binary information is encoded in different charge states of the QCA cells and transmitted by the inter-cell Coulomb interaction. Despite the promise of QCA, however, it remains a challenge to identify suitable building blocks for the construction of QCA. Graphene has recently attracted considerable attention owing to its remarkable electronic properties. The planar structure makes it feasible to pattern the whole device architecture in one sheet, compatible with the existing electronics technology. Here, we demonstrate theoretically a new QCA architecture built upon nanopatterned graphene quantum dots (GQDs). Using the tight-binding model, we determine the phenomenological cell parameters and cell-cell response functions of the GQD-QCA to characterize its performance. Furthermore, a GQD-QCA architecture is designed to demonstrate the functionalities of a fundamental majority gate. Our results show great potential in manufacturing high-density ultrafast QCA devices from a single nanopatterned graphene sheet.
A scale-invariant cellular-automata model for distributed seismicity
NASA Technical Reports Server (NTRS)
Barriere, Benoit; Turcotte, Donald L.
1991-01-01
In the standard cellular-automata model for a fault an element of stress is randomly added to a grid of boxes until a box has four elements, these are then redistributed to the adjacent boxes on the grid. The redistribution can result in one or more of these boxes having four or more elements in which case further redistributions are required. On the average added elements are lost from the edges of the grid. The model is modified so that the boxes have a scale-invariant distribution of sizes. The objective is to model a scale-invariant distribution of fault sizes. When a redistribution from a box occurs it is equivalent to a characteristic earthquake on the fault. A redistribution from a small box (a foreshock) can trigger an instability in a large box (the main shock). A redistribution from a large box always triggers many instabilities in the smaller boxes (aftershocks). The frequency-size statistics for both main shocks and aftershocks satisfy the Gutenberg-Richter relation with b = 0.835 for main shocks and b = 0.635 for aftershocks. Model foreshocks occur 28 percent of the time.
Evolutionary Design of one-dimensional Rule Changing cellular automata using genetic algorithms
NASA Astrophysics Data System (ADS)
Yun, Wu; Kanoh, Hitoshi
In this paper we propose a new method to obtain transition rules of one-dimensional two-state cellular automata (CAs) using genetic algorithms (GAs). CAs have the advantages of producing complex systems from the interaction of simple elements, and have attracted increased research interest. However, the difficulty of designing CAs' transition rules to perform a particular task has severely limited their applications. The evolutionary design of CA rules has been studied by the EVCA group in detail. A GA was used to evolve CAs for two tasks: density classification and synchronization problems. That GA was shown to have discovered rules that gave rise to sophisticated emergent computational strategies. Sipper has studied a cellular programming algorithm for 2-state non-uniform CAs, in which each cell may contain a different rule. Meanwhile, Land and Belew proved that the perfect two-state rule for performing the density classification task does not exist. However, Fuks´ showed that a pair of human written rules performs the task perfectly when the size of neighborhood is one. In this paper, we consider a pair of rules and the number of rule iterations as a chromosome, whereas the EVCA group considers a rule as a chromosome. The present method is meant to reduce the complexity of a given problem by dividing the problem into smaller ones and assigning a distinct rule to each one. Experimental results for the two tasks prove that our method is more efficient than a conventional method. Some of the obtained rules agree with the human written rules shown by Fuks´. We also grouped 1000 rules with high fitness into 4 classes according to the Langton's λ parameter. The rules obtained by the proposed method belong to Class- I, II, III or IV, whereas most of the rules by the conventional method belong to Class-IV only. This result shows that the combination of simple rules can perform complex tasks.
NASA Astrophysics Data System (ADS)
Huang, Hua-mei; Zhang, Li-quan; Guan, Yu-juan; Wang, Dong-hui
2008-03-01
Biological invasion has received considerable attention recently because of increasing impacts on local ecosystems. Expansion of Spartina alterniflora, a non-native species, on the intertidal mudflats of Jiuduansha Shoals at the Yangtze River Estuary is a prime example of a spatially-structured invasion in a relatively simple habitat, for which strategic control efforts can be modeled and applied. Here, we developed a Cellular Automata (CA) model, in conjunction with Remote Sensing and Geographical Information Systems, to simulate the expanding process of S. alterniflora for a period of 8 years after being introduced to the new shoals, and to study the interactions between spatial pattern and ecosystem processes for the saltmarsh vegetation. The results showed that the CA model could simulate the population dynamics of S. alterniflora and Phragmites australis on the Jiuduansha Shoals successfully. The results strongly support the hypothesis of space pre-emption as well as range expansion with simple advancing wave fronts for these two species. In the Yangtze River Estuary, the native species P. australis shares the same niche with the exotic species S. alterniflora. However, the range expansion rate of P. australis was much slower than that of S. alterniflora. With the accretion of the Jiuduansha Shoals due to the large quantity of sediments deposited by the Yangtze River, a rapid range expansion of S. alterniflora is predicted to last for a long period into future. This study indicated the potential for this approach to provide valuable insights into population and community ecology of invasive species, which could be very important for wetland biodiversity conservation and resource management in the Yangtze River Estuary and other such impacted areas.
Coarse-graining of cellular automata, emergence, and the predictability of complex systems
NASA Astrophysics Data System (ADS)
Israeli, Navot; Goldenfeld, Nigel
2006-02-01
We study the predictability of emergent phenomena in complex systems. Using nearest-neighbor, one-dimensional cellular automata (CA) as an example, we show how to construct local coarse-grained descriptions of CA in all classes of Wolfram’s classification. The resulting coarse-grained CA that we construct are capable of emulating the large-scale behavior of the original systems without accounting for small-scale details. Several CA that can be coarse-grained by this construction are known to be universal Turing machines; they can emulate any CA or other computing devices and are therefore undecidable. We thus show that because in practice one only seeks coarse-grained information, complex physical systems can be predictable and even decidable at some level of description. The renormalization group flows that we construct induce a hierarchy of CA rules. This hierarchy agrees well with apparent rule complexity and is therefore a good candidate for a complexity measure and a classification method. Finally we argue that the large-scale dynamics of CA can be very simple, at least when measured by the Kolmogorov complexity of the large-scale update rule, and moreover exhibits a novel scaling law. We show that because of this large-scale simplicity, the probability of finding a coarse-grained description of CA approaches unity as one goes to increasingly coarser scales. We interpret this large-scale simplicity as a pattern formation mechanism in which large-scale patterns are forced upon the system by the simplicity of the rules that govern the large-scale dynamics.
NASA Astrophysics Data System (ADS)
Chen, Qingcai; Shi, Jianghong; Liu, Xiaowei; Wu, Wei; Liu, Bo; Zhang, Hui
2013-03-01
A cellular automata model (CA model) was used to simulate the soil column leaching process of estrogens during the processes of migration and transformation. The results of the simulated leaching experiment showed that the first-order degradation rates of 17α-ethynylestradiol (EE2), 17β-estradiol (E2) and estrone (E1) were 0.131 h- 1 for E2, 0.099 h- 1 for E1 and 0.064 h- 1 for EE2 in the EE2 and E2 leaching process, and the first-order sorption rates were 5.94 h- 1 for E2, 5.63 h- 1 for EE2, 3.125 h- 1 for E1. Their sorption rates were positively correlated with the n-octanol/water partition coefficients. When the diffusion rate was low, its impact on the simulation results was insignificant. The increase in sorption and degradation rates caused the decrease in the total estrogens that leached. In addition, increasing the sorption rate could delay the emerging time of the maximum concentration of estrogen that leached, whereas increasing the degradation rate could shorten the emerging time of the maximum concentration of estrogen that leached. The comparison made between the experimental data and the simulation results of the CA model and the HYDRUS-1D software showed that the establishment of one-component and multi-component CA models could simulate EE2 and E2 soil column leaching processes, and the CA models achieve an intuitive, dynamic, and visual simulation.
NASA Astrophysics Data System (ADS)
Zheng, Zhi-Zhen; Wang, Ai-Ling
2009-02-01
Spatially explicit models have become widely used in today's mathematical ecology and epidemiology to study the persistence of populations. For simplicity, population dynamics is often analysed by using ordinary differential equations (ODEs) or partial differential equations (PDEs) in the one-dimensional (1D) space. An important question is to predict species extinction or persistence rate by mean of computer simulation based on the spatial model. Recently, it has been reported that stable turbulent and regular waves are persistent based on the spatial susceptible-infected-resistant-susceptible (SIRS) model by using the cellular automata (CA) method in the two-dimensional (2D) space [Proc. Natl. Acad. Sci. USA 101, 18246 (2004)]. In this paper, we address other important issues relevant to phase transitions of epidemic persistence. We are interested in assessing the significance of the risk of extinction in 1D space. Our results show that the 2D space can considerably increase the possibility of persistence of spread of epidemics when the degree distribution of the individuals is uniform, i.e. the pattern of 2D spatial persistence corresponding to extinction in a 1D system with the same parameters. The trade-offs of extinction and persistence between the infection period and infection rate are observed in the 1D case. Moreover, near the trade-off (phase transition) line, an independent estimation of the dynamic exponent can be performed, and it is in excellent agreement with the result obtained by using the conjectured relationship of directed percolation. We find that the introduction of a short-range diffusion and a long-range diffusion among the neighbourhoods can enhance the persistence and global disease spread in the space.
NASA Astrophysics Data System (ADS)
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.
Chen, Qingcai; Shi, Jianghong; Liu, Xiaowei; Wu, Wei; Liu, Bo; Zhang, Hui
2013-03-01
A cellular automata model (CA model) was used to simulate the soil column leaching process of estrogens during the processes of migration and transformation. The results of the simulated leaching experiment showed that the first-order degradation rates of 17α-ethynylestradiol (EE2), 17β-estradiol (E2) and estrone (E1) were 0.131 h(-1) for E2, 0.099 h(-1) for E1 and 0.064 h(-1) for EE2 in the EE2 and E2 leaching process, and the first-order sorption rates were 5.94 h(-1) for E2, 5.63 h(-1) for EE2, 3.125 h(-1) for E1. Their sorption rates were positively correlated with the n-octanol/water partition coefficients. When the diffusion rate was low, its impact on the simulation results was insignificant. The increase in sorption and degradation rates caused the decrease in the total estrogens that leached. In addition, increasing the sorption rate could delay the emerging time of the maximum concentration of estrogen that leached, whereas increasing the degradation rate could shorten the emerging time of the maximum concentration of estrogen that leached. The comparison made between the experimental data and the simulation results of the CA model and the HYDRUS-1D software showed that the establishment of one-component and multi-component CA models could simulate EE2 and E2 soil column leaching processes, and the CA models achieve an intuitive, dynamic, and visual simulation. PMID:23376816
NASA Astrophysics Data System (ADS)
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)
Mozumder, Chandan K.
The objective in crashworthiness design is to generate plastically deformable energy absorbing structures which can satisfy the prescribed force-displacement (FD) response. The FD behavior determines the reaction force, displacement and the internal energy that the structure should withstand. However, attempts to include this requirement in structural optimization problems remain scarce. The existing commercial optimization tools utilize models under static loading conditions because of the complexities associated with dynamic/impact loading. Due to the complexity of a crash event and the consequent time required to numerically analyze the dynamic response of the structure, classical methods (i.e., gradient-based and direct) are not well developed to solve this undertaking. This work presents an approach under the framework of the hybrid cellular automaton (HCA) method to solve the above challenge. The HCA method has been successfully applied to nonlinear transient topology optimization for crashworthiness design. In this work, the HCA algorithm has been utilized to develop an efficient methodology for synthesizing shell-based sheet metal structures with optimal material thickness distribution under a dynamic loading event using topometry optimization. This method utilizes the cellular automata (CA) computing paradigm and nonlinear transient finite element analysis (FEA) via ls-dyna. In this method, a set field variables is driven to their target states by changing a convenient set of design variables (e.g., thickness). These rules operate locally in cells within a lattice that only know local conditions. The field variables associated with the cells are driven to a setpoint to obtain the desired structure. This methodology is used to design for structures with controlled energy absorption with specified buckling zones. The peak reaction force and the maximum displacement are also constrained to meet the desired safety level according to passenger safety
Optimal design of variable-stiffness fiber-reinforced composites using cellular automata
NASA Astrophysics Data System (ADS)
Setoodeh, Shahriar
The growing number of applications of composite materials in aerospace and naval structures along with advancements in manufacturing technologies demand continuous innovations in the design of composite structures. In the traditional design of composite laminates, fiber orientation angles are constant for each layer and are usually limited to 0, 90, and +/-45 degrees. To fully benefit from the directional properties of composite laminates, such limitations have to be removed. The concept of variable-stiffness laminates allows the stiffness properties to vary spatially over the laminate. Through tailoring of fiber orientations and laminate thickness spatially in an optimal fashion, mechanical properties of a part can be improved. In this thesis, the optimal design of variable-stiffness fiber-reinforced composite laminates is studied using an emerging numerical engineering optimization scheme based on the cellular automata paradigm. A cellular automaton (CA) based design scheme uses local update rule for both field variables (displacements) and design variables (lay-up configuration and laminate density measure) in an iterative fashion to convergence to an optimal design. In the present work, the displacements are updated based on the principle of local equilibrium and the design variables are updated according to the optimality criteria for minimum compliance design. A closed form displacement update rule for constant thickness isotropic continua is derived, while for the general anisotropic continua with variable thickness a numeric update rule is used. Combined lay-up and topology design of variable-stiffness flat laminates is performed under the action of in-plane loads and bending loads. An optimality criteria based formulation is used to obtain local design rules for minimum compliance design subject to a volume constraint. It is shown that the design rule splits into a two step application. In the first step an optimal lay-up configuration is computed and in
Yang, Qing-Sheng; Qiao, Ji-Gang; Ai, Bin
2013-09-01
Taking the Dongguan City with rapid urbanization as a case, and selecting landscape ecological security level as evaluation criterion, the urbanization cellular number of 1 km x 1 km ecological security cells was obtained, and imbedded into the transition rules of cellular automata (CA) as the restraint term to control urban development, establish ecological security urban CA, and simulate ecological security urban development pattern. The results showed the integrated landscape ecological security index of the City decreased from 0.497 in 1998 to 0.395 in 2005, indicating that the ecological security at landscape scale was decreased. The CA-simulated integrated ecological security index of the City in 2005 was increased from the measured 0.395 to 0.479, showing that the simulated urban landscape ecological pressure from human became lesser, ecological security became better, and integrated landscape ecological security became higher. CA could be used as an effective tool in researching urban ecological security. PMID:24417120
Simulation of debris flow events in Sicily by cellular automata model SCIDDICA_SS3
NASA Astrophysics Data System (ADS)
Cancelliere, A.; Lupiano, V.; Peres, D. J.; Stancanelli, L.; Avolio, M.; Foti, E.; Di Gregorio, S.
2013-12-01
Debris flow models are widely used for hazard mapping or for evaluating the effectiveness of risk mitigation measures. Several models analyze the dynamics of debris flow runout solving Partial Differential Equations. In use of such models, difficulties arise in estimating kinematic geotechnical soil parameters for real phenomena. In order to overcome such difficulties, alternative semi-empirical approaches can be employed, such as macroscopic Cellular Automata (CA). In particular, for CA simulation purposes, the runout of debris flows emerges from local interactions in a dynamical system, subdivided into elementary parts, whose state evolves within a spatial and temporal discretum. The attributes of each cell (substates) describe physical characteristics. For computational reasons, the natural phenomenon is splitted into a number of elementary processes, whose proper composition makes up the CA transition function. By simultaneously applying this function to all the cells, the evolution of the phenomenon can be simulated in terms of modifications of the substates. In this study, we present an application of the macroscopic CA semi-empirical model SCIDDICA_SS3 to the Peloritani Mountains area in Sicily island, Italy. The model was applied using detailed data from the 1 October 2009 debris flow event, which was triggered by a rainfall event of about 250 mm falling in 9 hours, that caused the death of 37 persons. This region is characterized by river valleys with large hillslope angles (30°-60°), catchment basins of small extensions (0.5-12 km2) and soil composed by metamorphic material, which is easy to be eroded. CA usage implies a calibration phase, that identifies an optimal set of parameters capable of adequately play back the considered case, and a validation phase, that tests the model on a sufficient (and different) number of cases similar in terms of physical and geomorphological properties. The performance of the model can be measured in terms of a fitness
NASA Astrophysics Data System (ADS)
Vanwalleghem, T.; Jiménez-Hornero, F. J.; Giráldez, J. V.; Laguna, A.
2009-04-01
The process of tillage translocation is well studied and can be described adequately by different existing models. Nevertheless, in complex environments such as olive orchards, characterized by numerous obstacles, application of such conventional tillage erosion models is not straightforward. However, these obstacles have important effects on the spatial pattern of soil redistribution and on resulting soil properties. In this kind of environment, cellular automata could provide a valuable alternative. This study aims at developing a cellular automata model for tillage translocation (CATT) that can take into account such obstacles and at exploring its possibilities and limitations. A simple model was developed, which main parameters are tillage direction, speed and depth. Firstly, the modeĺs outcome was tested against existing 137Cs inventories for a study site in the Belgian loam belt. The observed spatial soil redistribution patterns could be adequately represented by the CATT model. Secondly, a sensitivity analysis was performed to explore the effect of input uncertainty on several selected model outputs. The variance-based extended FAST method was used to determine first and total order sensitivity indices. Tillage depth was identified as the input parameter that determined most of the output variance, followed respectively by tillage direction and speed. The difference between the total and first-order sensitivity indices, between 0.8 and 2, indicated that, in spite of the simple model structure, the model behaves non-linearly with respect to some of the model output variables. Higher-order interactions were especially important for determining the proportion of eroding and deposition cells. Finally, simulations were performed to analyse the model behaviour in complex landscapes, applying it to a field with protruding obstacles (e.g. olive trees). The model adequately represented some morphological features observed in the olive orchards, such as mounds around
NASA Astrophysics Data System (ADS)
van Wijk, Mark T.; Rodriguez-Iturbe, Ignacio
2002-09-01
Water is a key resource in determining the composition and structure of savanna ecosystems. In this study we present a simple cellular automata model in which death and reproduction chances of trees and grasses are based on the dynamical description of plant water stress by a probabilistic ecohydrological point model, using the parameterization for a Texas savanna. The results show that the model behavior, despite its simplicity, can be linked to ecological reality: the model yields a dynamic tree-grass coexistence driven by the annual rainfall, and the space-time behavior shows that both random and clustered tree distributions for periods up to 100 years can be observed. Both temporal and spatial model output display fractal characteristics suggesting the possibility of a self-organized critical dynamics. Thus power law behavior is observed in both the spectral density function and the cluster size distribution. The presence of spatial fractal characteristic opens avenues for more thorough model testing.
Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein
2016-06-01
This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy. PMID:27154739
Christie, John A; Forrest, Ryan P; Corcelli, Steven A; Wasio, Natalie A; Quardokus, Rebecca C; Brown, Ryan; Kandel, S Alex; Lu, Yuhui; Lent, Craig S; Henderson, Kenneth W
2015-12-14
The preparation of 7-Fc(+) -8-Fc-7,8-nido-[C2 B9 H10 ](-) (Fc(+) FcC2 B9 (-) ) demonstrates the successful incorporation of a carborane cage as an internal counteranion bridging between ferrocene and ferrocenium units. This neutral mixed-valence Fe(II) /Fe(III) complex overcomes the proximal electronic bias imposed by external counterions, a practical limitation in the use of molecular switches. A combination of UV/Vis-NIR spectroscopic and TD-DFT computational studies indicate that electron transfer within Fc(+) FcC2 B9 (-) is achieved through a bridge-mediated mechanism. This electronic framework therefore provides the possibility of an all-neutral null state, a key requirement for the implementation of quantum-dot cellular automata (QCA) molecular computing. The adhesion, ordering, and characterization of Fc(+) FcC2 B9 (-) on Au(111) has been observed by scanning tunneling microscopy. PMID:26516063
NASA Astrophysics Data System (ADS)
Bengtsson, L.
2014-12-01
A common way of addressing forecast uncertainty in Numerical Weather Prediction (NWP) models is to use ensemble prediction. The idea behind ensemble predictionis to simulate the sensitivity of the forecast to the initial and boundary conditions, as well as model construction error, such as sub-grid physical parameterizations. Existing methods used in order to account for such model consturction uncertainty include; multi-model ensembles, adding random perturbations to the tendencies produced by the parameterizations, or perturbing parameters within the parameterizations. Although such methods are successful in a probabilistic sense, individual ensemble members can be degraded in a deterministic sense by adding random non-physical perturbations. Furthermore, different ensemble members can have different bias (and skill) since they are based on separate models and/or parameters. Another way of accounting for model uncertainty (due to sub-grid variability) is to introduce random variability in the convection parameterization itself. Here we will present the impact of the stochastic deep convection parameterization using cellular automata described in Bengtsson et. al. 2013, as implemented in the high resolution meso-scale ensemble prediction system HarmonEPS. The questions we would like to answer are; can we improve the forecast skill both in a deterministic and probabilistic sense using the stochastic convection scheme? Can the stochastic parameterization in terms of the spread/skill relationship compete with the multi-model approach? Furthermore, the stochastic parameterization proposed in Bengtsson et. al. 2013 addresses lateral communication between model grid-boxes by using a cellular automaton. It was demonstrated that the scheme in a deterministic model is capable of contributing to the organization of convective squall-lines and meso-scale convective systems. We study if and how uncertainties with origin on the sub-grid scale transfer to the larger atmospheric
NASA Astrophysics Data System (ADS)
Ramírez-López, A.; Romero-Romo, M. A.; Muñoz-Negron, D.; López-Ramírez, S.; Escarela-Pérez, R.; Duran-Valencia, C.
2012-10-01
Computational models are developed to create grain structures using mathematical algorithms based on the chaos theory such as cellular automaton, geometrical models, fractals, and stochastic methods. Because of the chaotic nature of grain structures, some of the most popular routines are based on the Monte Carlo method, statistical distributions, and random walk methods, which can be easily programmed and included in nested loops. Nevertheless, grain structures are not well defined as the results of computational errors and numerical inconsistencies on mathematical methods. Due to the finite definition of numbers or the numerical restrictions during the simulation of solidification, damaged images appear on the screen. These images must be repaired to obtain a good measurement of grain geometrical properties. Some mathematical algorithms were developed to repair, measure, and characterize grain structures obtained from cellular automata in the present work. An appropriate measurement of grain size and the corrected identification of interfaces and length are very important topics in materials science because they are the representation and validation of mathematical models with real samples. As a result, the developed algorithms are tested and proved to be appropriate and efficient to eliminate the errors and characterize the grain structures.
Conway's game of life is a near-critical metastable state in the multiverse of cellular automata
NASA Astrophysics Data System (ADS)
Reia, Sandro M.; Kinouchi, Osame
2014-05-01
Conway's cellular automaton Game of Life has been conjectured to be a critical (or quasicritical) dynamical system. This criticality is generally seen as a continuous order-disorder transition in cellular automata (CA) rule space. Life's mean-field return map predicts an absorbing vacuum phase (ρ =0) and an active phase density, with ρ =0.37, which contrasts with Life's absorbing states in a square lattice, which have a stationary density of ρ2D≈0.03. Here, we study and classify mean-field maps for 6144 outer-totalistic CA and compare them with the corresponding behavior found in the square lattice. We show that the single-site mean-field approach gives qualitative (and even quantitative) predictions for most of them. The transition region in rule space seems to correspond to a nonequilibrium discontinuous absorbing phase transition instead of a continuous order-disorder one. We claim that Life is a quasicritical nucleation process where vacuum phase domains invade the alive phase. Therefore, Life is not at the "border of chaos," but thrives on the "border of extinction."
Conway's Game of Life is a near-critical metastable state in the multiverse of cellular automata.
Reia, Sandro M; Kinouchi, Osame
2014-05-01
Conway's cellular automaton Game of Life has been conjectured to be a critical (or quasicritical) dynamical system. This criticality is generally seen as a continuous order-disorder transition in cellular automata (CA) rule space. Life's mean-field return map predicts an absorbing vacuum phase (ρ = 0) and an active phase density, with ρ = 0.37, which contrasts with Life's absorbing states in a square lattice, which have a stationary density of ρ(2D) ≈ 0.03. Here, we study and classify mean-field maps for 6144 outer-totalistic CA and compare them with the corresponding behavior found in the square lattice. We show that the single-site mean-field approach gives qualitative (and even quantitative) predictions for most of them. The transition region in rule space seems to correspond to a nonequilibrium discontinuous absorbing phase transition instead of a continuous order-disorder one. We claim that Life is a quasicritical nucleation process where vacuum phase domains invade the alive phase. Therefore, Life is not at the "border of chaos," but thrives on the "border of extinction." PMID:25353755
NASA Astrophysics Data System (ADS)
Chen, Qun; Wang, Yan
2015-08-01
This paper discusses the interaction of vehicle flows and pedestrian crossings on uncontrolled low-grade roads or branch roads without separating barriers in cities where pedestrians may cross randomly from any location on both sides of the road. The rules governing pedestrian street crossings are analyzed, and a cellular automata (CA) model to simulate the interaction of vehicle flows and pedestrian crossings is proposed. The influence of the interaction of vehicle flows and pedestrian crossings on the volume and travel time of the vehicle flow and the average wait time for pedestrians to cross is investigated through simulations. The main results of the simulation are as follows: (1) The vehicle flow volume decreases because of interruption from pedestrian crossings, but a small number of pedestrian crossings do not cause a significant delay to vehicles. (2) If there are many pedestrian crossings, slow vehicles will have little chance to accelerate, causing travel time to increase and the vehicle flow volume to decrease. (3) The average wait time for pedestrians to cross generally decreases with a decrease in vehicle flow volume and also decreases with an increase in the number of pedestrian crossings. (4) Temporal and spatial characteristics of vehicle flows and pedestrian flows and some interesting phenomena such as "crossing belt" and "vehicle belt" are found through the simulations.
Chai, C; Wong, Y D
2014-02-01
At intersection, vehicles coming from different directions conflict with each other. Improper geometric design and signal settings at signalized intersection will increase occurrence of conflicts between road users and results in a reduction of the safety level. This study established a cellular automata (CA) model to simulate vehicular interactions involving right-turn vehicles (as similar to left-turn vehicles in US). Through various simulation scenarios for four case cross-intersections, the relationships between conflict occurrences involving right-turn vehicles with traffic volume and right-turn movement control strategies are analyzed. Impacts of traffic volume, permissive right-turn compared to red-amber-green (RAG) arrow, shared straight-through and right-turn lane as well as signal setting are estimated from simulation results. The simulation model is found to be able to provide reasonable assessment of conflicts through comparison of existed simulation approach and observed accidents. Through the proposed approach, prediction models for occurrences and severity of vehicle conflicts can be developed for various geometric layouts and traffic control strategies. PMID:24275720
NASA Astrophysics Data System (ADS)
Gong, Wenfeng; Yuan, Li; Fan, Wenyi; Stott, Philip
2015-02-01
There have been rapid population and accelerating urban growth with associated changes in land use and soil degradation in northeast China, an important grain-producing region. The development of integrated use of remote sensing, geographic information systems, and combined cellular automata- Markov models has provided new means of assessing changes in land use and land cover, and has enabled projection of trajectories into the future. We applied such techniques to the prefecture-level city of Harbin, the tenth largest city in China. We found that there had been significant losses of the land uses termed "cropland", "grassland", "wetland", and "floodplain" in favour of "built-up land" and lesser transformations from "floodplain" to "forestland" and "water body" over the 18-year period. However, the transition was not a simple process but a complex network of changes, interchanges, and multiple transitions. In the absence of effective land use policies, projection of past trajectories into a balance state in the future would result in the decline of cropland from 65.6% to 46.9% and the increase of built-up area from 7.7% to 23.0% relative to the total area of the prefecture in 1989. It also led to the virtual elimination of land use types such as unused wetland and floodplain.
NASA Astrophysics Data System (ADS)
He, Yingqing; Ai, Bin; Yao, Yao; Zhong, Fajun
2015-06-01
Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model's parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China's Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model's parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.
Pokkuluri, Kiran Sree; Inampudi, Ramesh Babu; Nedunuri, S S S N Usha Devi
2014-01-01
Protein coding and promoter region predictions are very important challenges of bioinformatics (Attwood and Teresa, 2000). The identification of these regions plays a crucial role in understanding the genes. Many novel computational and mathematical methods are introduced as well as existing methods that are getting refined for predicting both of the regions separately; still there is a scope for improvement. We propose a classifier that is built with MACA (multiple attractor cellular automata) and MCC (modified clonal classifier) to predict both regions with a single classifier. The proposed classifier is trained and tested with Fickett and Tung (1992) datasets for protein coding region prediction for DNA sequences of lengths 54, 108, and 162. This classifier is trained and tested with MMCRI datasets for protein coding region prediction for DNA sequences of lengths 252 and 354. The proposed classifier is trained and tested with promoter sequences from DBTSS (Yamashita et al., 2006) dataset and nonpromoters from EID (Saxonov et al., 2000) and UTRdb (Pesole et al., 2002) datasets. The proposed model can predict both regions with an average accuracy of 90.5% for promoter and 89.6% for protein coding region predictions. The specificity and sensitivity values of promoter and protein coding region predictions are 0.89 and 0.92, respectively. PMID:25132849
NASA Astrophysics Data System (ADS)
Tiihonen, Juha; Schramm, Andreas; Kylänpää, Ilkka; Rantala, Tapio T.
2016-02-01
A thorough simulation study is carried out on thermal and quantum delocalization effects on the feasibility of a quantum-dot cellular automata (QCA) cell. The occupation correlation of two electrons is modeled with a simple four-site array of harmonic quantum dots (QD). QD sizes range from 20 nm to 40 nm with site separations from 20 nm to 100 nm, relevant for state-of-the-art GaAs/InAs semiconductor technology. The choice of parameters introduces QD overlap, which is only simulated properly with exact treatment of strong Coulombic correlation and thermal equilibrium quantum statistics. These are taken into account with path integral Monte Carlo approach. Thus, we demonstrate novel joint effects of quantum delocalization and decoherence in QCA, but also highly sophisticated quantitative evidence supporting the traditional relations in pragmatic QCA design. Moreover, we show the effects of dimensionality and spin state, and point out the parameter space conditions, where the ‘classical’ treatment becomes invalid.
NASA Astrophysics Data System (ADS)
Feliciani, Claudio; Nishinari, Katsuhiro
2016-06-01
In this article we present an improved version of the Cellular Automata floor field model making use of a sub-mesh system to increase the maximum density allowed during simulation and reproduce phenomena observed in dense crowds. In order to calibrate the model's parameters and to validate it we used data obtained from an empirical observation of bidirectional pedestrian flow. A good agreement was found between numerical simulation and experimental data and, in particular, the double outflow peak observed during the formation of deadlocks could be reproduced in numerical simulations, thus allowing the analysis of deadlock formation and dissolution. Finally, we used the developed high density model to compute the flow-ratio dependent fundamental diagram of bidirectional flow, demonstrating the instability of balanced flow and predicting the bidirectional flow behavior at very high densities. The model we presented here can be used to prevent dense crowd accidents in the future and to investigate the dynamics of the accidents which already occurred in the past. Additionally, fields such as granular and active matter physics may benefit from the developed framework to study different collective phenomena.
Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun
2013-01-01
Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans. PMID:24244472
Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun
2013-01-01
Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans. PMID:24244472
Robust tracking by cellular automata and neural networks with nonlocal weights
NASA Astrophysics Data System (ADS)
Ososkov, Gennadii A.
1995-04-01
A modified rotor model of the Hopfield neural networks (HNN) is proposed for finding tracks in multiwire proportional chambers. That requires us to apply both raw data prefiltering by cellular automaton and HNN weights furnishing by a special robust multiplier. Then this model is developed to be applicable for a more general type of data and detectors. As an example, data processing of ionospheric measurements are considered. For handling tracks detected by high pressure drift chambers with their up-down ambiguity a modification of deformable templates method is proposed. A new concept of controlled HNN is proposed for solving the so-called track-match problem.
NASA Astrophysics Data System (ADS)
Wang, Li; Liu, Mao; Meng, Bo
2013-02-01
In China, both the mountainous areas and the number of people who live in mountain areas occupy a significant proportion. When production accidents or natural disasters happen, the residents in mountain areas should be evacuated and the evacuation is of obvious importance to public safety. But it is a pity that there are few studies on safety evacuation in rough terrain. The particularity of the complex terrain in mountain areas, however, makes it difficult to study pedestrian evacuation. In this paper, a three-dimensional surface cellular automata model is proposed to numerically simulate the real time dynamic evacuation of residents. The model takes into account topographic characteristics (the slope gradient) of the environment and the biomechanics characteristics (weight and leg extensor power) of the residents to calculate the walking speed. This paper only focuses on the influence of topography and the physiological parameters are defined as constants according to a statistical report. Velocity varies with the topography. In order to simulate the behavior of a crowd with varying movement velocities, and a numerical algorithm is used to determine the time step of iteration. By doing so, a numerical simulation can be conducted in a 3D surface CA model. Moreover, considering residents evacuation around a gas well in a mountain area as a case, a visualization system for a three-dimensional simulation of pedestrian evacuation is developed. In the simulation process, population behaviors of congestion, queuing and collision avoidance can be observed. The simulation results are explained reasonably. Therefore, the model presented in this paper can realize a 3D dynamic simulation of pedestrian evacuation vividly in complex terrain and predict the evacuation procedure and evacuation time required, which can supply some valuable information for emergency management.