Majority Bootstrap Percolation on the Hypercube

In majority bootstrap percolation on a graph G, an infection spreads according to the following deterministic rule: if at least half of the neighbours of a vertex v are already infected, then v is also infected, and infected vertices remain infected forever. We say that percolation occurs if eventually every vertex is infected. The elements of the set of initially infected vertices, A subset of V(G), are normally chosen independently at random, each with probability p, say. This process has been extensively Studied on the sequence of torus graphs [n](d), for n = 1, 2,..., where d = d(n) is either fixed or a very slowly growing function of n. For example, Cerf and Manzo [17] showed that the critical probability is o(1) if d(n) <= log.n, i.e., if p = p(n) is bounded away from zero then the probability of percolation on [n]d tends to one as n -> infinity. In this paper we study the case when the growth of d to infinity is not excessively slow; in particular, we show that the critical probability is 1/2 + o(1) if d >= (log log n)(2) log log log 17, and give much,stronger bounds in the case that G is the hypercube, [2](d).