Majority bootstrap percolation on the hypercube

József Balogh, Béla Bollobás, Robert Morris

Research output: Contribution to journalArticlepeer-review


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 ⊂ 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 → ∞. In this paper we study the case when the growth of d to 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 n, and give much stronger bounds in the case that G is the hypercube, [2]d.

Original languageEnglish (US)
Pages (from-to)17-51
Number of pages35
JournalCombinatorics Probability and Computing
Issue number1-2
StatePublished - Mar 2009

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Statistics and Probability
  • Computational Theory and Mathematics
  • Applied Mathematics


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