Effect of self-interaction on the phase diagram of a Gibbs-like measure derived by a reversible Probabilistic Cellular Automata

TL;DR

This paper investigates how self-interaction influences the ground states and low-temperature phase diagram of a Gibbs measure derived from a reversible Probabilistic Cellular Automaton with a cross-shaped update rule.

Contribution

It introduces a detailed analysis of the role of self-interaction in the phase behavior of a specific class of reversible PCA, expanding understanding of their ground states and phase transitions.

Findings

Self-interaction significantly affects the ground states.

The phase diagram varies with the self-interaction parameter.

New insights into the low-temperature behavior of the model.

Abstract

Cellular Automata are discrete-time dynamical systems on a spatially extended discrete space which provide paradigmatic examples of nonlinear phenomena. Their stochastic generalizations, i.e., Probabilistic Cellular Automata (PCA), are discrete time Markov chains on lattice with finite single-cell states whose distinguishing feature is the \emph{parallel} character of the updating rule. We study the ground states of the Hamiltonian and the low-temperature phase diagram of the related Gibbs measure naturally associated with a class of reversible PCA, called the \textit{cross PCA}. In such a model the updating rule of a cell depends indeed only on the status of the five cells forming a cross centered at the original cell itself. In particular, it depends on the value of the center spin (\textit{self-interaction}). The goal of the paper is that of investigating the role played by the self-interaction parameter in connection with the ground states of the Hamiltonian and the low-temperature phase diagram of the Gibbs measure associated with this particular PCA.