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arXiv 2111.06363math.COmath.PR
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概率超图容器

Probabilistic hypergraph containers

Rajko Nenadov

AI总结:

本文提出超图容器定理的概率版本,证明随机 $m$ 元顶点集通常落入由少量顶点构造的几乎独立集容器中,从而加强 Janson 不等式且证明更简洁。

摘要:

给定一个 $k$-一致超图 $\mathcal{H}$,并设 $m \gg m_0(\mathcal{H})$ 充分大,我们证明:从 $V(\mathcal{H})$ 中均匀随机选取的一个含 $m$ 个元素的集合 $I$,以 $1-e^{-\omega(m)}$ 的概率,要么不是独立集,要么包含于 $\mathcal{H}$ 中的一个几乎独立集内;关键在于,该几乎独立集可由 $I$ 中精心选取的 $o(m)$ 个顶点构造出来。作为推论,这意味着如果 $\mathcal{H}$ 中最大的几乎独立集大小为 $o(v(\mathcal{H}))$,那么 $I$ 本身成为独立集的概率为 $e^{-\omega(m)}$。更一般地,$I$ 极有可能继承 $\mathcal{H}$ 中几乎独立集的结构性质。$m_0(\mathcal{H})$ 这一阈值恰好与 Janson 不等式给出 $I$ 为独立集的概率至多为 $e^{-\Theta(m_0)}$ 时的阈值相同。一方面,我们的结果在 $m \gg m_0$ 的范围内是对 Janson 不等式的显著加强。另一方面,它可被视为由 Balogh、Morris 和 Samotij 以及独立地由 Saxton 和 Thomason 发展的超图容器定理的概率变体。尽管从它不适用于所有大小为 $m$ 的独立集这一意义上说,它严格弱于原始容器定理,但它仍足以应对许多应用,并可利用概率思想给出简短证明。

英文摘要:

Given a $k$-uniform hypergraph $\mathcal{H}$ and sufficiently large $m \gg m_0(\mathcal{H})$, we show that an $m$-element set $I \subseteq V(\mathcal{H})$, chosen uniformly at random, with probability $1 - e^{-ω(m)}$ is either not independent or is contained in an almost-independent set in $\mathcal{H}$ which, crucially, can be constructed from carefully chosen $o(m)$ vertices of $I$. As a corollary, this implies that if the largest almost-independent set in $\mathcal{H}$ is of size $o(v(\mathcal{H}))$ then $I$ itself is an independent set with probability $e^{-ω(m)}$. More generally, $I$ is very likely to inherit structural properties of almost-independent sets in $\mathcal{H}$. The value $m_0(\mathcal{H})$ coincides with that for which Janson's inequality gives that $I$ is independent with probability at most $e^{-Θ(m_0)}$. On the one hand, our result is a significant strengthening of Janson's inequality in the range $m \gg m_0$. On the other hand, it can be seen as a probabilistic variant of hypergraph container theorems, developed by Balogh, Morris and Samotij and, independently, by Saxton and Thomason. While being strictly weaker than the original container theorems in the sense that it does not apply to all independent sets of size $m$, it is nonetheless sufficient for many applications and admits a short proof using probabilistic ideas.

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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