随机正则图的狄拉克定理

Padraig Condon, Alberto Espuny Díaz, António Girão, Daniela Kühn, Deryk Osthus
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引用次数: 4

摘要

摘要在随机正则图的集合中证明了狄拉克定理的一个“弹性”版本。更准确地说,我们表明,当d与$\epsilon > 0$相比足够大时,也就是说,以下成立。设$G'$为随机n顶点d正则图$G_{n,d}$最小度至少为$$(1/2 + \epsilon )d$$的任意子图。那么$G'$就是汉密尔顿函数。这证明了Ben-Shimon, Krivelevich和Sudakov的一个猜想。我们的结果是最好的:首先d很大的条件不能省略,其次最小度界不能改进。
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Dirac’s theorem for random regular graphs
Abstract We prove a ‘resilience’ version of Dirac’s theorem in the setting of random regular graphs. More precisely, we show that whenever d is sufficiently large compared to $\epsilon > 0$ , a.a.s. the following holds. Let $G'$ be any subgraph of the random n-vertex d-regular graph $G_{n,d}$ with minimum degree at least $$(1/2 + \epsilon )d$$ . Then $G'$ is Hamiltonian. This proves a conjecture of Ben-Shimon, Krivelevich and Sudakov. Our result is best possible: firstly the condition that d is large cannot be omitted, and secondly the minimum degree bound cannot be improved.
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