Bootstrap percolation on the high-dimensional Hamming graph
Mihyun Kang, Michael Missethan, Dominik Schmid

TL;DR
This paper analyzes the critical probability for bootstrap percolation on high-dimensional Hamming graphs, extending previous results from hypercubes to more general Cartesian products of complete graphs.
Contribution
It extends the asymptotic analysis of the critical probability for 2-neighbour bootstrap percolation from hypercubes to Hamming graphs with arbitrary size, for large dimensions.
Findings
Determines the asymptotic critical probability for Hamming graphs.
Extends previous hypercube results to more general graphs.
Provides bounds valid for large dimensions and vertex counts.
Abstract
In the random -neighbour bootstrap percolation process on a graph , a set of initially infected vertices is chosen at random by retaining each vertex of independently with probability , and "healthy" vertices get infected in subsequent rounds if they have at least infected neighbours. A graph \emph{percolates} if every vertex becomes eventually infected. A central problem in this process is to determine the critical probability , at which the probability that percolates passes through one half. In this paper, we study random -neighbour bootstrap percolation on the -dimensional Hamming graph , which is the graph obtained by taking the Cartesian product of copies of the complete graph on vertices. We extend a result of Balogh and Bollob\'{a}s [Bootstrap percolation on the hypercube, Probab. Theory Related…
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Taxonomy
TopicsStochastic processes and statistical mechanics · Complex Network Analysis Techniques · Opinion Dynamics and Social Influence
