Transition from susceptible-infected to susceptible-infected-recovered dynamics in a susceptible-cleric-zombie-recovered active matter model

Simulating pedestrian avoidance: The human-zombie game

This study introduces a simulated active matter system, applying the pedestrian collision avoidance paradigm, which involves dynamically adjusting the desired velocity. We present a human-zombie game set within a closed geometry, combining predator-prey behavior with a one-way contagion process that transforms prey into predators. The system demonstrates varied responses in our implemented model: with agents having the same maximum speeds, a single zombie always captures a human, whereas two zombies never capture a single human agent. As the number of human agents increases, observables such as the final fraction of zombie agents and total conversion times exhibit significant changes in the system's behavior at intermediate density values. Most notably, there is evidence of a first-order phase transition when analyzing the mean population speed as an order parameter.

Burstiness and information spreading in active particle systems

We construct a temporal network using the two-dimensional Vicsek model. The bursts of the interevent times for a specific pair of particles are investigated numerically. We found that, for different noise strengths, the distribution of the interevent times of a target edge follows a heavy tail, revealing the burstiness of the signals. To further characterize the nature of the burstiness, we calculate the burstiness parameters and the memory coefficients. The results show that, near the phase transition points of the Vicsek model, the burstiness parameters reach the minimum values for each density, indicating a relationship between the phase transition of the Vicsek model and the bursty nature of the signals. Furthermore, we investigate the spreading dynamics on our temporal network using a susceptible-infected model and observe a positive correlation between them.