SEARCH · Searcharxiv
Search indexed arXiv papers on artificial intelligence, large language models, computer vision and robotics. Read source abstracts and follow links to arXiv.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Integer lattice gas automata can be utilized as building blocks in statistical mechanics. The presented deterministic and reversible automaton generates semiclassical statistical distributions. A possible approach to Bose-Einstein statistics from cellular automata position is discussed.
Spatio-temporal dynamics of excitable media with discrete three-level active centers (ACs) and absorbing boundaries is studied numerically by means of a deterministic three-level model (see S. D. Makovetskiy and D. N. Makovetskii, on-line preprint cond-mat/0410460 ), which is a generalization of Zykov- Mikhailov model (see Sov. Phys. -- Doklady, 1986, Vol.31, No.1, P.51) for the case of two-channel diffusion of excitations. In particular, we revealed some qualitatively new features of coexistence, competition and collapse of rotating spiral waves (RSWs) in three-level excitable media under conditions of strong influence of the second channel of diffusion. Part of these features are caused by unusual mechanism of RSWs evolution when RSW's cores get into the surface layer of an active medium (i.~e. the layer of ACs resided at the absorbing boundary). Instead of well known scenario of RSW collapse, which takes place after collision of RSW's core with absorbing boundary, we observed complicated transformations of the core leading to nonlinear ''reflection'' of the RSW from the boundary or even to birth of several new RSWs in the surface layer. To our knowledge, such nonlinear ''reflections'' of RSWs and resulting die hard vorticity in excitable media with absorbing boundaries were unknown earlier. ACM classes: F.1.1, I.6, J.2; PACS numbers: 05.65.+b, 07.05.Tp, 82.20.Wt
We present the results of a detailed study of energy correlations at steady state for a 1-D model of coupled energy and matter transport. Our aim is to discover -- via theoretical arguments, conjectures, and numerical simulations -- how spatial covariances scale with system size, their relations to local thermodynamic quantities, and the randomizing effects of heat baths. Among our findings are that short-range covariances respond quadratically to local temperature gradients, and long-range covariances decay linearly with macroscopic distance. These findings are consistent with exact results for the simple exclusion and KMP models.
We relate structurally dynamic cellular networks, a class of models we developed in fundamental space-time physics, to SDCA, introduced some time ago by Ilachinski and Halpern. We emphasize the crucial property of a non-linear interaction of network geometry with the matter degrees of freedom in order to emulate the supposedly highly erratic and strongly fluctuating space-time structure on the Planck scale. We then embark on a detailed numerical analysis of various large scale characteristics of several classes of models in order to understand what will happen if some sort of macroscopic or continuum limit is performed. Of particular relevance in this context is a notion of network dimension and its behavior in this limit. Furthermore, the possibility of phase transitions is discussed.
Within a one-dimensional semi-classical model with a Morse potential the possibility of microwave multi-photon dissociation of vibrationally excited nitrogen oxide was studied. The dissociation thresholds of typical driving forces and couplings were found to be similar, which indicates that the results were robust to variations of the potential and the definition of dissociation rate.
The aim of this Thesis is to present five new tests for random numbers, which are widely used {\em e.g.} in computer simulations in physics applications. The first two tests, the cluster test and the autocorrelation test, are based on analogies to the two-dimensional Ising model. The next two, the random walk test and the $n$-block test, are based on studies of random walks, and the condition number test presented last uses some results of Gaussian distributed random matrices. Studies with several commonly used pseudorandom number generators reveal that the cluster test is particularly powerful in finding periodic correlations on bit level, and that the autocorrelation test, the random walk test, and the $n$-block test are very effective in detecting short-ranged correlations. The results of the condition number test are mostly inconclusive, however. By means of the tests presented in this work, two important results are found. First, we show quantitatively that the reason for erroneous results in some recent high precision Monte Carlo simulations for some commonly used pseudorandom number generators are the so called triple correlations in the sequences. Then, we show that the properties of such a sequence may be considerably improved, if only a certain portion of it is used.
We study the spacial and temporal multiscale properties of complex systems. We present accelerated algorithms for dilute spin glasses and display explicitly their relation to the effective dynamics of specific collective degrees of freedom (macros). We discuss the difficulties in applying multiscale-cluster algorithms(MCA) to general frustrated systems: MCA does not succeed to break the system into clusters. We relate these difficulties to rigorous negative results in systems with an ultrametric space of ground states: the tunneling between vacua cannot be expressed into an algorithm acting upon independent macros.
We study the phase diagram and the critical behavior of a one-dimensional radius-1 two-state totalistic probabilistic cellular automaton having two absorbing states. This system exhibits a first-order phase transition between the fully occupied state and the empty state, two second-order phase transitions between a partially occupied state and either the fully occupied state or the empty state, and a second-order damage-spreading phase transition. It is found that all the second-order phase transitions have the same critical behavior as the directed percolation model. The mean-field approximation gives a rather good qualitative description of all these phase transitions.
We simulate self-reproducing micellar systems using a recently introduced lattice-gas automaton. This dynamical model correctly describes the equilibrium and non-equilibrium properties of mixtures of oil, water and surfactants. The simulations reported here mimic the experiments of Luisi et al. in which caprylate micelles are formed by alkaline hydrolysis of immiscible ethyl caprylate ester. As in the laboratory experiments, we find an extended induction period during which the concentration of micelles remains small; thereafter the ester is consumed very rapidly with concomitant production of micelles.
We investigate the allowed configurations in the stationary state of the cellular automaton model for single-lane traffic. It is found that certain states in the configuration space can not be reached if one uses parallel dynamics. These so-called Garden of Eden (GoE) states do not exist for random-sequential dynamics and are responsible for the strong short-ranged correlations found in parallel dynamics. By eliminating the GoE states we obtain a simple and effective approximative description of the model. For $v_{max}=1$ the exact solution is recovered. For $v_{max}=2$ this elimination leads to much higher values of the flux compared to the mean-field result which are in good agreement with Monte Carlo simulations.
In dynamical systems such as cellular automata and iterated maps, it is often useful to look at a language or set of symbol sequences produced by the system. There are well-established classification schemes, such as the Chomsky hierarchy, with which we can measure the complexity of these sets of sequences, and thus the complexity of the systems which produce them. In this paper, we look at the first few levels of a hierarchy of complexity for two-or-more-dimensional patterns. We show that several definitions of ``regular language'' or ``local rule'' that are equivalent in d=1 lead to distinct classes in d >= 2. We explore the closure properties and computational complexity of these classes, including undecidability and L-, NL- and NP-completeness results. We apply these classes to cellular automata, in particular to their sets of fixed and periodic points, finite-time images, and limit sets. We show that it is undecidable whether a CA in d >= 2 has a periodic point of a given period, and that certain ``local lattice languages'' are not finite-time images or limit sets of any CA. We also show that the entropy of a d-dimensional CA's finite-time image cannot decrease faster than t^{-d} unless it maps every initial condition to a single homogeneous state.
We show that the lattice Boltzmann formalism can be used to describe wave propagation in a heterogeneous media, as well as solid-body-like systems and fracture propagation. Several fundamental properties of real fractures (such as propagation speed and transition between rough and smooth crack surfaces) are well captured by our approach.
We describe software that searches for spaceships in Conway's Game of Life and related two-dimensional cellular automata. Our program searches through a state space related to the de Bruijn graph of the automaton, using a method that combines features of breadth first and iterative deepening search, and includes fast bit-parallel graph reachability and path enumeration algorithms for finding the successors of each state. Successful results include a new 2c/7 spaceship in Life, found by searching a space with 2^126 states.
We provide the first classification of different types of Random Boolean Networks (RBNs). We study the differences of RBNs depending on the degree of synchronicity and determinism of their updating scheme. For doing so, we first define three new types of RBNs. We note some similarities and differences between different types of RBNs with the aid of a public software laboratory we developed. Particularly, we find that the point attractors are independent of the updating scheme, and that RBNs are more different depending on their determinism or non-determinism rather than depending on their synchronicity or asynchronicity. We also show a way of mapping non-synchronous deterministic RBNs into synchronous RBNs. Our results are important for justifying the use of specific types of RBNs for modelling natural phenomena.
In this paper I present a first attempt for a possible description of fluids dynamics by mean of a cellular automata technique. With the use of simple and elementary rules, based on random behaviour either, the model permits to obtain the evolution in time for a two-dimensional grid, where one molecule of the material fluid can ideally place itself on a single geometric square. By mean of computational simulations, some realistic effects, here showed by use of digital pictures, have been obtained. In a subsequent step of this work I think to use a parallel program for a high performances computational simulation, for increasing the degree of realism of the digital rendering by mean of a three-dimensional grid too. For the execution of the simulations, numerical methods of resolution for differential equations have not been used.
In the computational-mechanics structural analysis of one-dimensional cellular automata the following automata-theoretic analogue of the \emph{change-point problem} from time series analysis arises: \emph{Given a string $σ$ and a collection $\{\mc{D}_i\}$ of finite automata, identify the regions of $σ$ that belong to each $\mc{D}_i$ and, in particular, the boundaries separating them.} We present two methods for solving this \emph{multi-regular language filtering problem}. The first, although providing the ideal solution, requires a stack, has a worst-case compute time that grows quadratically in $σ$'s length and conditions its output at any point on arbitrarily long windows of future input. The second method is to algorithmically construct a transducer that approximates the first algorithm. In contrast to the stack-based algorithm, however, the transducer requires only a finite amount of memory, runs in linear time, and gives immediate output for each letter read; it is, moreover, the best possible finite-state approximation with these three features.
We investigate the description of statistical field theories using Daubechies' orthonormal compact wavelets on a lattice. A simple variational approach is used to extend mean field theory and make predictions for the fluctuation strengths of wavelet coefficients and thus for the correlation function. The results are compared to Monte Carlo simulations. We find that wavelets provide a reasonable description of critical phenomena with only a small number of variational parameters. This lets us hope for an implementation of the renormalization group in wavelet space.
A new class of parallel algorithms is introduced that can achieve a complexity of O(n^3/2) with respect to the interprocessor communication, in the exact computation of systems with pairwise mutual interactions of all elements. Hitherto, conventional methods exhibit a communicational complexity of O(n^2). The amount of computation operations is not altered for the new algorithm which can be formulated as a kind of h-range problem, known from the mathematical field of Additive Number Theory. We will demonstrate the reduction in communicational expense by comparing the standard-systolic algorithm and the new algorithm on the connection machine CM5 and the CRAY T3D. The parallel method can be useful in various scientific and engineering fields like exact n-body dynamics with long range forces, polymer chains, protein folding or signal processing.