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Occupancy fraction, fractional colouring, and triangle fraction

Authors: Ewan Davies; Rémi de Joannis de Verclos; Ross J. Kang; François Pirot;

Occupancy fraction, fractional colouring, and triangle fraction

Abstract

Given $\varepsilon>0$, there exists $f_0$ such that, if $f_0 \le f \le ��^2+1$, then for any graph $G$ on $n$ vertices of maximum degree $��$ in which the neighbourhood of every vertex in $G$ spans at most $��^2/f$ edges, (i) an independent set of $G$ drawn uniformly at random has at least $(1/2-\varepsilon)(n/��)\log f$ vertices in expectation, and (ii) the fractional chromatic number of $G$ is at most $(2+\varepsilon)��/\log f$. These bounds cannot in general be improved by more than a factor $2$ asymptotically. One may view these as stronger versions of results of Ajtai, Koml��s and Szemer��di (1981) and Shearer (1983). The proofs use a tight analysis of the hard-core model.

13 pages

Countries
Netherlands, France
Keywords

FOS: Computer and information sciences, Discrete Mathematics (cs.DM), Probability (math.PR), Articles, hard-core model, fractional colouring, [MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO], 05C35, 05D10 (Primary), 05C15 (Secondary), Coloring of graphs and hypergraphs, Vertex subsets with special properties (dominating sets, independent sets, cliques, etc.), independent sets, FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), hard‐core model, Mathematics, Mathematics - Probability, Computer Science - Discrete Mathematics

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    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.
    Top 10%
    influence
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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
hybrid