Information Flow in Finite Flocks

TL;DR

This study simulates the Vicsek model to analyze how information transfer varies with noise, revealing that global transfer entropy remains constant across the phase transition, unlike in simpler models.

Contribution

It demonstrates that in finite flocks, information flow does not peak at the phase transition, challenging previous assumptions based on simpler models.

Findings

Global transfer entropy remains constant across the phase transition.

Information flow does not peak near the critical point.

Provides groundwork for analyzing real-world flocking data.

Abstract

We simulate the canonical Vicsek model and estimate the flow of information as a function of noise (the variability in the extent to which each animal aligns with its neighbours). We show that the global transfer entropy for finite flocks not only fails to peak near the phase transition, as demonstrated for the canonical 2D Ising model, but remains constant from the transition to very low noise values. This provides a foundation for future study regarding information flow in more complex models and real-world flocking data.