Abstract
We explore information flow in finite active matter flocks by simulating the canonical Vicsek model and estimating 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 throughout the entire ordered regime to very low noise values. This provides a foundation for future study regarding information flow in more complex models and real-world flocking data.
Highlights
We explore information flow in finite active matter flocks by simulating the canonical Vicsek model and estimating the flow of information as a function of noise
A principal finding of this paper is the surprising result that the information flow in the canonical Vicsek flocking model reaches a maximum around the time the flock becomes stable and remains high until very low noise, where noise represents the uncertainty with which an agent aligns with its neighbours
To analyse the long-term limit GTE of the minimalist Standard Vicsek Model (SVM)[16] of collective motion[17,18] we developed a closed-form dimensional reduction, obtained by exploiting an approximate isometry in the SVM
Summary
We explore information flow in finite active matter flocks by simulating the canonical Vicsek model and estimating the flow of information as a function of noise (the variability in the extent to which each animal aligns with its neighbours). This new behaviour may inform future studies on real-world flocks or other more sophisticated models, noting that for the SVM maximum information flow occurs not just near the phase transition, but throughout the entire low noise regime as well.
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