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Electronic Journal of Probability
Article . 2021 . Peer-reviewed
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Electronic Journal of Probability
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https://dx.doi.org/10.48550/ar...
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A sharp threshold for bootstrap percolation in a random hypergraph

Authors: Morrison, Natasha; Noel, Jonathan A.;

A sharp threshold for bootstrap percolation in a random hypergraph

Abstract

Given a hypergraph $\mathcal{H}$, the $\mathcal{H}$-bootstrap process starts with an initial set of infected vertices of $\mathcal{H}$ and, at each step, a healthy vertex $v$ becomes infected if there exists a hyperedge of $\mathcal{H}$ in which $v$ is the unique healthy vertex. We say that the set of initially infected vertices percolates if every vertex of $\mathcal{H}$ is eventually infected. We show that this process exhibits a sharp threshold when $\mathcal{H}$ is a hypergraph obtained by randomly sampling hyperedges from an approximately $d$-regular $r$-uniform hypergraph satisfying some mild degree and codegree conditions; this confirms a conjecture of Morris. As a corollary, we obtain a sharp threshold for a variant of the graph bootstrap process for strictly $2$-balanced graphs which generalises a result of Korándi, Peled and Sudakov. Our approach involves an application of the differential equations method.

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Keywords

differential equations method, Probability (math.PR), Random graphs (graph-theoretic aspects), Interacting random processes; statistical mechanics type models; percolation theory, Hypergraphs, hypergraphs, martingales, sharp threshold, FOS: Mathematics, Mathematics - Combinatorics, Martingales with discrete parameter, Combinatorics (math.CO), bootstrap percolation, Mathematics - Probability

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Average
Green
gold