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Upper Tail Bounds for Stars

Upper tail bounds for stars
Authors: Matas Sileikis; Lutz Warnke;

Upper Tail Bounds for Stars

Abstract

For $r \ge 2$, let $X$ be the number of $r$-armed stars $K_{1,r}$ in the binomial random graph $G_{n,p}$. We study the upper tail ${\mathbb P}(X \ge (1+\epsilon){\mathbb E} X)$, and establish exponential bounds which are best possible up to constant factors in the exponent (for the special case of stars $K_{1,r}$ this solves a problem of Janson and Ruciński, and confirms a conjecture by DeMarco and Kahn). In contrast to the widely accepted standard for the upper tail problem, we do not restrict our attention to constant $\epsilon$, but also allow for $\epsilon \ge n^{-\alpha}$ deviations.

Country
Czech Republic
Keywords

upper tail, 05C80, 60C05, 60F10, Combinatorial probability, binomial random graph, Probability (math.PR), Random graphs (graph-theoretic aspects), \(r\)-armed stars, large deviations, Large deviations, concentration inequalities, FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), Subgraph counts, random graphs, 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!
7
Top 10%
Average
Top 10%
Green
gold