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arXiv 2102.05522math.CO
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局部可着色图的色度剖面

The chromatic profile of locally colourable graphs

Freddie Illingworth

AI总结:

本文研究局部 $b$-分图及团公共邻域可着色图的色度剖面,确定其色度阈值,并给出保证局部 $b$-分图为 $(b+1)$-可着色的最小度条件。

摘要:

经典的 Andrásfai-Erdős-Sós 定理研究具有较大最小度的无 $K_{r+1}$ 图的色数;在 $r=2$ 的情形下,该定理表明,任何具有 $n$ 个顶点、最小度大于 $2/5\cdot n$ 的无三角形图都是二分图。这开启了对无三角形图色度剖面的研究:对于每个 $k$,怎样的最小度能够保证一个无三角形图是 $k$-可着色的?该剖面已得到广泛研究,并最终由 Brandt 和 Thomassé 确定。无三角形图恰好是每个邻域都为一可着色的图。作为一种自然的推广,Łuczak 和 Thomassé 引入了局部二分图的概念,即每个邻域都是二可着色的图。本文研究两类图的色度剖面:一类是每个邻域都为 $b$-可着色的图(局部 $b$-分图),另一类是每个 $a$-团的公共邻域都为 $b$-可着色的图。我们的结果包括这些图族的色度阈值,并证明每个具有 $n$ 个顶点、最小度大于 $(1-1/(b+1/7))\cdot n$ 的局部 $b$-分图都是 $(b+1)$-可着色的。理解这些局部可着色图对于将 Andrásfai-Erdős-Sós 定理推广到非完全图至关重要,我们将在其他工作中展开这一推广。

英文摘要:

The classical Andrásfai-Erdős-Sós theorem considers the chromatic number of $K_{r + 1}$-free graphs with large minimum degree, and in the case $r = 2$ says that any $n$-vertex triangle-free graph with minimum degree greater than $2/5 \cdot n$ is bipartite. This began the study of the chromatic profile of triangle-free graphs: for each $k$, what minimum degree guarantees that a triangle-free graph is $k$-colourable? The profile has been extensively studied and was finally determined by Brandt and Thomassé. Triangle-free graphs are exactly those in which each neighbourhood is one-colourable. As a natural variant, Łuczak and Thomassé introduced the notion of a locally bipartite graph in which each neighbourhood is 2-colourable. Here we study the chromatic profile of the family of graphs in which every neighbourhood is $b$-colourable (locally $b$-partite graphs) as well as the family where the common neighbourhood of every $a$-clique is $b$-colourable. Our results include the chromatic thresholds of these families as well as showing that every $n$-vertex locally $b$-partite graph with minimum degree greater than $(1 - 1/(b + 1/7)) \cdot n$ is $(b + 1)$-colourable. Understanding these locally colourable graphs is crucial for extending the Andrásfai-Erdős-Sós theorem to non-complete graphs, which we develop elsewhere.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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