Burstiness and information spreading in the active particles systems

TL;DR

This paper studies the burstiness and information spreading in active particle systems modeled by the Vicsek model, revealing how phase transitions influence burstiness and how burstiness correlates with spreading dynamics.

Contribution

It introduces a temporal network construction from active particle systems and links burstiness characteristics to phase transitions and spreading behavior.

Findings

Burstiness follows a heavy-tail distribution across different noise levels.

Burstiness parameters reach minima near critical points of the Vicsek model.

Higher burstiness correlates positively with faster information spreading.

Abstract

We construct the temporal network using the two-dimensional active particle systems which are described by the Vicsek model. The bursts of the interevent times for a specific pair of particles are investigated numerically. We find that for different noise strength, the distribution of the interevent times of a target edge follows by a heavy-tail, revealing a strong burstiness of the signals. To further characterize the nature of the burstiness, the burstiness parameter and the memory coefficient are calculated. The results show that near the critical points of the Vicsek model, the burstiness parameters reach the minimum values for each density, indicating a relation between the phase transition of the Vicsek model and the bursty nature of the signals. Besides, the memory plays a negligible role in the burstiness. Further, we investigate the spreading dynamics on our temporal network with the susceptible-infected model, and observe a positive correlation between the burstiness and the information spreading dynamics.