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Electronic Journal of Combinatorics
Article . 2024 . Peer-reviewed
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Coloring Hypergraphs from Random Lists

Coloring hypergraphs from random lists
Authors: Casselgren, Carl Johan;

Coloring Hypergraphs from Random Lists

Abstract

We introduce and study problems on coloring hypergraphs from randomly chosen color lists. Let $H=H(n)$ be an $r$-uniform hypergraph on $n$ vertices where each vertex is assigned a list of colors of size $k$ chosen independently and uniformly at random from all $k$-subsets of a set of colors of size $\sigma=\sigma(n)$. We prove a number of results concerning the probability of the existence of a list coloring of $H$ from the random lists. One such result is that for fixed $r$, $k$ and growing $n$, if $\sigma = \omega\left(n^{\frac{1}{k^2(r-1)}}\Delta^{\frac{1}{k(r-1)}}\right)$, and $H(n)$ has maximum degree $\Delta = O\left(n^{\frac{k-1}{k^2(k^2+k) r(r - 1)}}\right)$, then with probability tending to $1$, as $n \to \infty$, $H$ has a proper coloring from the random lists. The bound on $\sigma$ is tight. We also prove analogous results for hypergraphs of bounded maximum degree and complete hypergraphs where the size $k$ of the random lists either is constant or an increasing function of $n$. In particular, for the complete $r$-uniform hypergraph $K_n^r$, if $\sigma = \lceil n/(r-1) \rceil$, then the property of being colorable from random lists of size $k$ has a sharp threshold at $k(n) = \frac{\log n}{r-1}$.

Country
Sweden
Related Organizations
Keywords

randomly chosen color lists, Coloring of graphs and hypergraphs, Combinatorial probability, Discrete Mathematics, Diskret matematik, Hypergraphs, \(r\)-uniform hypergraph

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selected citations
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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!
0
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