Chase-Escape Percolation on the 2D Square Lattice
Aanjaneya Kumar, Peter Grassberger, and Deepak Dhar

TL;DR
This paper investigates chase-escape percolation on a 2D square lattice, estimating critical thresholds, analyzing universality classes, and exploring front dynamics and phase transitions with Monte Carlo simulations.
Contribution
It introduces a discrete-time version of chase-escape percolation, estimates the critical probability, and connects the model to undirected percolation and front fluctuation theories.
Findings
Critical probability p_c ≈ 0.49451 with Monte Carlo simulations.
The model's critical exponents match the undirected percolation universality class.
Front fluctuations follow KPZ scaling and exhibit a depinning transition at p=1.
Abstract
Chase-escape percolation is a variation of the standard epidemic spread models. In this model, each site can be in one of three states: unoccupied, occupied by a single prey, or occupied by a single predator. Prey particles spread to neighboring empty sites at rate , and predator particles spread only to neighboring sites occupied by prey particles at rate , killing the prey particle that existed at that site. It was found that the prey can survive with non-zero probability, if with . Using Monte Carlo simulations on the square lattice, we estimate the value of , and the critical exponents are consistent with the undirected percolation universality class. We define a discrete-time parallel-update version of the model, which brings out the relation between chase-escape and undirected bond percolation. For all in -dimensions,…
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