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arXiv · 0705.1347

Slow Convergence in Bootstrap Percolation

Janko Gravner·Alexander E. Holroyd
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Abstract

In the bootstrap percolation model, sites in an L by L square are initially infected independently with probability p. At subsequent steps, a healthy site becomes infected if it has at least 2 infected neighbours. As (L,p)->(infinity,0), the probability that the entire square is eventually infected is known to undergo a phase transition in the parameter p log L, occurring asymptotically at lambda = pi^2/18. We prove that the discrepancy between the critical parameter and its limit lambda is at least Omega((log L)^(-1/2)). In contrast, the critical window has width only Theta((log L)^(-1)). For the so-called modified model, we prove rigorous explicit bounds which imply for example that the relative discrepancy is at least 1% even when L = 10^3000. Our results shed some light on the observed differences between simulations and rigorous asymptotics.

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Janko Gravner, Alexander E. Holroyd. 2007-05-09. Slow Convergence in Bootstrap Percolation. https://arxiv.org/abs/0705.1347

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