Optimal and Near-Optimal Constructions for Bootstrap Percolation in Hypercubes

๐Ÿ“… 2026-04-16
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๐Ÿค– AI Summary
This study addresses the extremal problem of 4-neighbor bootstrap percolation on the $d$-dimensional hypercube graph $Q_d$, aiming to determine the minimum number $m(Q_d;4)$ of initially infected vertices required to eventually infect the entire graph. By combining combinatorial constructions, extremal graph theory arguments, and AlphaEvolve-assisted search, the authors establish for the first time that the Morrisonโ€“Noel lower bound is tight for infinitely many dimensions. They further provide a general upper bound that differs from this lower bound by only $O(d)$. A key contribution is the exact formula $m(Q_d;4) = \frac{d(d^2 + 3d + 14)}{24} + 1$, which holds for infinitely many values of $d$, substantially advancing the understanding of the $r=4$ bootstrap percolation regime on hypercubes.

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๐Ÿ“ Abstract
The $r$-neighbour bootstrap process on a graph $G$ begins with a set of infected vertices; subsequently, healthy vertices become infected once they have at least $r$ infected neighbours. The central extremal problem in bootstrap percolation is to determine the minimum cardinality of an initial infected set that eventually spreads to all vertices of $G$, denoted $m(G;r)$. Morrison and Noel established a general lower bound on $m(Q_d;r)$, where $Q_d$ is the $d$-dimensional hypercube, and asked whether it is tight whenever $d$ is sufficiently large with respect to $r$. This question was answered affirmatively for $r\leq 3$. In this paper, we show that $m(Q_d;4)=\frac{d(d^2+3d+14)}{24}+1$, matching the bound in of Morrison and Noel, for infinitely many $d$. We also obtain, for general $d$, an upper bound on $m(Q_d;4)$ that differs from the Morrison--Noel lower bound by an additive $O(d)$ term. Several key constructions in this paper were obtained with the assistance of AlphaEvolve.
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Research questions and friction points this paper is trying to address.

bootstrap percolation
hypercubes
extremal problem
initial infected set
minimum cardinality
Innovation

Methods, ideas, or system contributions that make the work stand out.

bootstrap percolation
hypercubes
extremal combinatorics
AlphaEvolve
infection threshold
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