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Phase transitions in random mixtures of elementary cellular automata

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  • Cirillo, Emilio N.M.
  • Nardi, Francesca R.
  • Spitoni, Cristian

Abstract

We investigate one-dimensional probabilistic cellular automata, called Diploid Elementary Cellular Automata (DECA), obtained as random mixtures of two different elementary cellular automata rules. All the cells are updated synchronously and the probability for one cell to be 0 or 1 at time t depends only on the value of the same cell and that of its neighbors at time t−1. These very simple models show a very rich behavior strongly depending on the choice of the two elementary cellular automata that are randomly mixed together and on the parameter which governs probabilistically the mixture. In particular, we study the existence of phase transition for the whole set of possible DECA obtained by mixing the null rule which associates 0 to any possible local configuration, with any of the other 255 elementary rules. We approach the problem analytically via a mean field approximation and via the use of a rigorous approach based on the application of the Dobrushin criterion. The main feature of our approach is the possibility to describe the behavior of the whole set of considered DECA without exploiting the local properties of the individual models. The results that we find are consistent with numerical studies already published in the scientific literature and also with some rigorous results proven for some specific models.

Suggested Citation

  • Cirillo, Emilio N.M. & Nardi, Francesca R. & Spitoni, Cristian, 2021. "Phase transitions in random mixtures of elementary cellular automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    • Handle: RePEc:eee:phsmap:v:573:y:2021:i:c:s0378437121002144
    DOI: 10.1016/j.physa.2021.125942
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    References listed on IDEAS

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    1. Jahnel, Benedikt & Külske, Christof, 2015. "A class of non-ergodic probabilistic cellular automata with unique invariant measure and quasi-periodic orbit," Stochastic Processes and their Applications, Elsevier, vol. 125(6), pages 2427-2450.
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    Cited by:

    1. Shang, Xue-Cheng & Li, Xin-Gang & Xie, Dong-Fan & Jia, Bin & Jiang, Rui & Liu, Feng, 2022. "A data-driven two-lane traffic flow model based on cellular automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).

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