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We present a rigorous derivation of the flow at arbitrary time in a deterministic cellular automaton model of traffic flow. The derivation employs regularities in preimages of blocks of zeros, reducing the problem of preimage enumeration to…

comp-gas · Physics 2009-10-31 Henryk Fuks

Large deviations in chaotic dynamics have potentially significant and dramatic consequences. We study large deviations of series of finite lengths $N$ generated by chaotic maps. The distributions generally display an exponential decay with…

Chaotic Dynamics · Physics 2022-10-21 Naftali R. Smith

We investigate number conserving cellular automata with up to five inputs and two states with the goal of comparing their dynamics with diffusion. For this purpose, we introduce the concept of decompression ratio describing expansion of…

Cellular Automata and Lattice Gases · Physics 2023-12-18 Henryk Fukś , Sanchala Abeykoon Mudiyanselage

Cellular automata (CA) provide a minimal formalism for investigating how simple local interactions generate rich spatiotemporal behavior in domains as diverse as traffic flow, ecology, tissue morphogenesis and crystal growth. However,…

Machine Learning · Computer Science 2025-06-24 Jaime A. Berkovich , Noah S. David , Markus J. Buehler

Within the class of stochastic cellular automata models of traffic flows, we look at the velocity dependent randomization variant (VDR-TCA) whose parameters take on a specific set of extreme values. These initial conditions lead us to the…

Cellular Automata and Lattice Gases · Physics 2007-05-23 Sven Maerivoet , Bart De Moor

Cellular automata (CA) have been utilized for decades as discrete models of many physical, mathematical, chemical, biological, and computing systems. The most widely known form of CA, the elementary cellular automaton (ECA), has been…

Cellular Automata and Lattice Gases · Physics 2013-10-15 Lucas Kang

A probabilistic cellular automaton for cargo transport is presented that generalizes the totally asymmetric exclusion process with a defect from continuous time to parallel dynamics. It appears as an underlying principle in cellular…

Statistical Mechanics · Physics 2010-06-25 Marko Woelki

This article presents a new characterization of controllability and regional controllability of Deterministic Cellular Automata (CA for short). It focuses on analyzing these problems within the framework of control theory, which have been…

Dynamical Systems · Mathematics 2025-01-07 Sara Dridi

Dynamical phase transitions are crucial features of the fluctuations of statistical systems, corresponding to boundaries between qualitatively different mechanisms of maintaining unlikely values of dynamical observables over long periods of…

Statistical Mechanics · Physics 2017-06-02 Alexandre Lazarescu

A method for studying the qualitative dynamical properties of abstract computing machines based on the approximation of their program-size complexity using a general lossless compression algorithm is presented. It is shown that the…

Computational Complexity · Computer Science 2011-01-24 Hector Zenil

Many diffusion processes in nature and society were found to be anomalous, in the sense of being fundamentally different from conventional Brownian motion. An important example is the migration of biological cells, which exhibits…

Statistical Mechanics · Physics 2018-02-13 J. M. Nava-Sedeno , H. Hatzikirou , R. Klages , A. Deutsch

Within the class of stochastic cellular automata models of traffic flows, we look at the velocity dependent randomization variant (VDR-TCA) whose parameters take on a specific set of extreme values. These initial conditions lead us to the…

Statistical Mechanics · Physics 2009-09-29 Sven Maerivoet , Bart De Moor

In cellular automata with memory, the unchanged maps of the conventional cellular automata are applied to cells endowed with memory of their past states in some specified interval. We implement Rule 30 automata with a majority memory and…

Cellular Automata and Lattice Gases · Physics 2010-11-23 Genaro J. Martinez , Andrew Adamatzky , Ramon Alonso-Sanz , J. C. Seck-Touh-Mora

Probabilistic cellular automata (CA) provides a classic framework for studying non-equilibrium statistical physics on a lattices. A notable example is the Domany-Kinzel CA, which has been used to investigate the process of directed…

Quantum Physics · Physics 2022-04-26 Ramil Nigmatullin , Elisabeth Wagner , Gavin K. Brennen

We explore some aspects of phase transitions in cellular automata. We start recalling the standard formulation of statistical mechanics of discrete systems (Ising model), illustrating the Monte Carlo approach as Markov chains and stochastic…

Statistical Mechanics · Physics 2023-12-05 Franco Bagnoli , Raul Rechtman

We show how to construct a deterministic nearest-neighbour cellular automaton (CA) with four states which emulates diffusion on a one-dimensional lattice. The pseudo-random numbers needed for directing random walkers in the diffusion…

Cellular Automata and Lattice Gases · Physics 2023-12-19 Henryk Fukś

We investigate the critical behaviour of a probabilistic mixture of cellular automata (CA) rules 182 and 200 (in Wolfram's enumeration scheme) by mean-field analysis and Monte Carlo simulations. We found that as we switch off one CA and…

Statistical Mechanics · Physics 2011-03-23 J. Ricardo G. Mendonça , Mário J. de Oliveira

A simple one-dimensional cellular automaton model with threshold dynamics is introduced. The cumulative distribution of the size of the relaxations is analytically computed and behaves as a power law with an exponent equal to -1. This…

Cellular Automata and Lattice Gases · Physics 2008-08-20 Alejandro Tejedor , Samuel Ambroj , Javier B. Gómez , Amalio F. Pacheco

We present results from an experiment similar to one performed by Packard (1988), in which a genetic algorithm is used to evolve cellular automata (CA) to perform a particular computational task. Packard examined the frequency of evolved CA…

adap-org · Physics 2008-02-03 Melanie Mitchell , Peter Hraber , James P. Crutchfield

Recent work has shown the effectiveness of tensor network methods for computing large deviation functions in constrained stochastic models in the infinite time limit. Here we show that these methods can also be used to study the statistics…

Statistical Mechanics · Physics 2022-03-08 Luke Causer , Mari Carmen Bañuls , Juan P. Garrahan