arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2007.03667math.CO
收藏

从局部考虑的大独立集

Large independent sets from local considerations

Matija Bucić, Benny Sudakov

摘要:

下面的自然问题是由Erdens-Hajnal和Linial-Rabinovich在80年代后期独立提出的。如果图$G$的每一个$m$顶点都包含一个大小为$r$的独立集,那么图的独立数$α(G)$必须有多大?在本文中,我们将讨论新的方法来解决这个问题。第一种新的方法,基于某些图的Ramsey数的边界,使我们能够提高以前的最佳下界由于Linial-Rabinovich,Erdens-Hajnal和Alon-Sudakov。作为一个例子,我们证明了任何$n$ -顶点图$G$在每个$7$顶点之间有一个独立的大小集$3$,则它有$α(G) \ge Ω(n^{5/12})$ .这证实了Erdens和Hajnal的猜想,即$α(G)$应该至少是$n^{1/3+\varepsilon}$,并使指数达到$1/2$的最佳可能值的一半。我们的第二种方法处理上界。它依赖于将原始问题简化为以下自然极值问题。在没有独立的大小集$r$的$m$顶点上的图的$2$ -密度的最小可能值是多少?这使我们能够改善以前的上限由于Linial-Rabinovich,Krivelevich和Kostochka-Jancey。作为我们的论点的一部分,我们联系的问题Erdens-Hajnal和Linial-Rabinovich和我们的新极值$2$ -密度问题的一些其他研究问题。这为未来的研究带来了许多有趣的方向。

英文摘要:

The following natural problem was raised independently by Erdős-Hajnal and Linial-Rabinovich in the late 80's. How large must the independence number $α(G)$ of a graph $G$ be whose every $m$ vertices contain an independent set of size $r$? In this paper we discuss new methods to attack this problem. The first new approach, based on bounding Ramsey numbers of certain graphs, allows us to improve previously best lower bounds due to Linial-Rabinovich, Erdős-Hajnal and Alon-Sudakov. As an example, we prove that any $n$-vertex graph $G$ having an independent set of size $3$ among every $7$ vertices has $α(G) \ge Ω(n^{5/12})$. This confirms a conjecture of Erdős and Hajnal that $α(G)$ should be at least $n^{1/3+\varepsilon}$ and brings the exponent half-way to the best possible value of $1/2$. Our second approach deals with upper bounds. It relies on a reduction of the original question to the following natural extremal problem. What is the minimum possible value of the $2$-density of a graph on $m$ vertices having no independent set of size $r$? This allows us to improve previous upper bounds due to Linial-Rabinovich, Krivelevich and Kostochka-Jancey. As part of our arguments we link the problem of Erdős-Hajnal and Linial-Rabinovich and our new extremal $2$-density problem to a number of other well-studied questions. This leads to many interesting directions for future research.

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。

↑