Complexity of the Freezing Majority Rule with L-shaped Neighborhoods

Fuente: arXiv
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Main Authors: Concha-Vega, Pablo, Goles, Eric, Montealegre, Pedro, Perrot, Kévin
Format: Preprint
Published: 2025
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author Concha-Vega, Pablo
Goles, Eric
Montealegre, Pedro
Perrot, Kévin
author_facet Concha-Vega, Pablo
Goles, Eric
Montealegre, Pedro
Perrot, Kévin
contents In this article we investigate the computational complexity of predicting two dimensional freezing majority cellular automata with states $\{-1,+1\}$, where the local interactions are based on an L-shaped neighborhood structure. In these automata, once a cell reaches state $+1$, it remains fixed in that state forever, while cells in state $-1$ update to the most represented state among their neighborhoods. We consider L-shaped neighborhoods, which mean that the vicinity of a given cell $c$ consists in a subset of cells in the north and east of $c$. We focus on the prediction problem, a decision problem that involves determining the state of a given cell after a given number of time-steps. We prove that when restricted to the simplest L-shaped neighborhood, consisting of the central cell and its nearest north and east neighbors, the prediction problem belongs to $\mathsf{NC}$, meaning it can be solved efficiently in parallel. We generalize this result for any L-shaped neighborhood of size two. On the other hand, for other L-shaped neighborhoods, the problem becomes $\mathsf{P}$-complete, indicating that the problem might be inherently sequential.
format Preprint
id arxiv_https___arxiv_org_abs_2509_16065
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Complexity of the Freezing Majority Rule with L-shaped Neighborhoods
Concha-Vega, Pablo
Goles, Eric
Montealegre, Pedro
Perrot, Kévin
Computational Complexity
Discrete Mathematics
In this article we investigate the computational complexity of predicting two dimensional freezing majority cellular automata with states $\{-1,+1\}$, where the local interactions are based on an L-shaped neighborhood structure. In these automata, once a cell reaches state $+1$, it remains fixed in that state forever, while cells in state $-1$ update to the most represented state among their neighborhoods. We consider L-shaped neighborhoods, which mean that the vicinity of a given cell $c$ consists in a subset of cells in the north and east of $c$. We focus on the prediction problem, a decision problem that involves determining the state of a given cell after a given number of time-steps. We prove that when restricted to the simplest L-shaped neighborhood, consisting of the central cell and its nearest north and east neighbors, the prediction problem belongs to $\mathsf{NC}$, meaning it can be solved efficiently in parallel. We generalize this result for any L-shaped neighborhood of size two. On the other hand, for other L-shaped neighborhoods, the problem becomes $\mathsf{P}$-complete, indicating that the problem might be inherently sequential.
title Complexity of the Freezing Majority Rule with L-shaped Neighborhoods
topic Computational Complexity
Discrete Mathematics
url https://arxiv.org/abs/2509.16065