A critical phase transition in bee movement dynamics can be modeled using a 2D cellular automata

TL;DR

This paper models bee movement dynamics using a 2D cellular automaton to replicate critical phase transition phenomena like long-range correlations and jamming, enhancing understanding of collective insect behavior.

Contribution

It introduces a discrete cellular automaton model that captures key features of bee hive dynamics, such as correlation divergence and scale-free jammed clusters, aligning with empirical data.

Findings

Model reproduces divergence of correlation length

Captures scale-free distribution of jammed clusters

Shows dependence of correlation length on density

Abstract

The collective behavior of numerous animal species, including insects, exhibits scale-free behavior indicative of the critical (second-order) phase transition. Previous research uncovered such phenomena in the behavior of honeybees, most notably the long-range correlations in space and time. Furthermore, it was demonstrated that the bee activity in the hive manifests the hallmarks of the jamming process. We follow up by presenting a discrete model of the system that faithfully replicates some of the key features found in the data - such as the divergence of correlation length and scale-free distribution of jammed clusters. The dependence of the correlation length on the control parameter - density is demonstrated for both the real data and the model. We conclude with a brief discussion on the contribution of the insights provided by the model to our understanding of the insects' collective behavior.