Computing the Difficulty of Critical Bootstrap Percolation Models is NP-hard


Bootstrap percolation is a class of cellular automata with random initial state. Two-dimensional bootstrap percolation models have three universality classes, the most studied being the ‘critical’ one. For this class the scaling of the quantity of greatest interest — the critical probability — was determined by Bollobás, Duminil-Copin, Morris and Smith in terms of a combinatorial quantity called ‘difficulty’, so the subject seemed closed up to finding sharper results. In this paper we prove that computing the difficulty of a critical model is NP-hard and exhibit an algorithm to determine it, in contrast with the upcoming result of Balister, Bollobás, Morris and Smith on undecidability in higher dimensions. The proof of NP-hardness is achieved by a reduction to the Set Cover problem.

SIAM J. Discrete Math. (2020), 34(2), 1444–1459.

My research interests include Graph Theory, Computational Geometry, and Algorithms