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Extremal $4$-Neighbour Bootstrap Percolation in the Hypercube

The -neighbour bootstrap process starts with an initial set of "infected" vertices in a graph and, at each step, a healthy vertex becomes infected if it has at least
infected neighbours. Say that the initial set of infected vertices percolates if every vertex of
is eventually infected. Let
denote the smallest percolating set in
under the
-neighbour process.
Let denote the hypercube of dimension
. Balogh and Bollobás [BB] proved the following.


They also conjectured that for fixed
and
. This conjecture was proved by Morrison and Noel [MN], who also showed the following.


It seems possible that one could obtain a general formula for for all
and
. However, the precise formula for
(in terms of
) is not known for any fixed
. A solution to this problem may have applications in proving probabilistic results for bootstrap percolation in the hypercube; see [BBM].
Bibliography
[BB] J. Balogh and B. Bollobás, Bootstrap percolation on the hypercube, Probab. Theory Related Fields 134 (2006), no. 4, 624–648.
[BBM] J. Balogh, B. Bollobás and R. Morris, Bootstrap percolation in high dimensions, Combin. Probab. Comput. 19 (2010), no. 5-6, 643–692.
[MN] N. Morrison and J. A. Noel, Extremal Bounds for Bootstrap Percolation in the Hypercube, preprint, arXiv:1506.04686v1.
* indicates original appearance(s) of problem.