Switching particle systems for foraging ants showing phase transitions in path selections

Ayana Ezoe, Saori Morimoto, Yuya Tanaka, Makoto Katori and Hiraku Nishimori

Physica A: Statistical Mechanics and its Applications, 2024, vol. 643, issue C

Abstract: Switching interacting particle systems studied in probability theory are the stochastic processes of hopping particles on a lattice made up of slow and fast particles, where the switching between these types of particles occurs randomly at a given transition rate. This paper explores how such stochastic processes involving multiple particles can model group behaviors of ants. Recent experimental research by the last author’s group has investigated how ants switch between two types of primarily relied cues to select foraging paths based on the current situation. Here, we propose a discrete-time interacting random walk model on a square lattice, incorporating two types of hopping rules. Numerical simulation results demonstrate global changes in selected homing paths, transitioning from trailing paths of the ‘pheromone road’ to nearly optimal paths depending on the switching parameters. By introducing two types of order parameters characterizing the dependence of homing duration distributions on switching parameters, we discuss these global changes as phase transitions in ant path selections. We also study critical phenomena associated with continuous phase transitions.

Keywords: Switching interacting particle systems; Group behaviors of ants; Switching of cues in foraging path selections; Interacting random walk model; Order parameters; Phase transitions and critical phenomena (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:643:y:2024:i:c:s0378437124003078

DOI: 10.1016/j.physa.2024.129798

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