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arXiv 1601.05481math.COmath.PR
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局部割引理

The Local Cut Lemma

Anton Bernshteyn

摘要:

Lovász局部引理是概率组合学中一个非常强大的工具,经常被用来证明满足某些约束的组合对象的存在性。Moser和Tardos已经证明,LLL给出的不仅仅是纯粹的存在结果:存在一个有效的随机算法,可以用来找到一个想要的对象。为了分析这种算法,Moser和Tardos开发了所谓的熵压缩方法。事实证明,人们可以通过直接应用熵压缩方法而不是简单地诉诸LLL来获得更好的组合结果。本文的目的是提供一个推广的LLL这意味着这些新的组合结果。这个推广,我们称之为局部割引理,涉及有向图中具有某些性质的随机割。请注意,我们的结果有一个简短的概率证明,没有使用熵压缩。因此,它不仅表明了某个概率是正的,而且给出了这个概率的一个明确的下界。作为一个例子,我们提出了一个新的应用程序(改进的下界上的颜色临界超图的边数),以及解释如何使用局部割引理推导出一些先前使用熵压缩方法获得的结果。

英文摘要:

The Lovász Local Lemma is a very powerful tool in probabilistic combinatorics, that is often used to prove existence of combinatorial objects satisfying certain constraints. Moser and Tardos have shown that the LLL gives more than just pure existence results: there is an effective randomized algorithm that can be used to find a desired object. In order to analyze this algorithm, Moser and Tardos developed the so-called entropy compression method. It turned out that one could obtain better combinatorial results by a direct application of the entropy compression method rather than simply appealing to the LLL. The aim of this paper is to provide a generalization of the LLL which implies these new combinatorial results. This generalization, which we call the Local Cut Lemma, concerns a random cut in a directed graph with certain properties. Note that our result has a short probabilistic proof that does not use entropy compression. As a consequence, it not only shows that a certain probability is positive, but also gives an explicit lower bound for this probability. As an illustration, we present a new application (an improved lower bound on the number of edges in color-critical hypergraphs) as well as explain how to use the Local Cut Lemma to derive some of the results obtained previously using the entropy compression method.

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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