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arXiv 0912.3868math.CO
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一个集中结果及其在子图计数中的应用

A concentration result with application to subgraph count

Guy Wolfovitz

摘要:

设H =(V,E)是一个k-一致超图,其顶点集V和边集E都是k-一致超图。设V_p是由V中的每个顶点以概率p独立地取来构造的,X是E中包含在V_p中的边的个数,我们给出了一个保证X在其均值附近的一个小区间内集中的条件。通过推导二项随机图中小的完全和完全二部图的拷贝数的新的次高斯尾证明了这一结果的适用性,推广了Rucibrski和Vu的结果.

英文摘要:

Let H = (V,E) be a k-uniform hypergraph with a vertex set V and an edge set E. Let V_p be constructed by taking every vertex in V independently with probability p. Let X be the number of edges in E that are contained in V_p. We give a condition that guarantees the concentration of X within a small interval around its mean. The applicability of this result is demonstrated by deriving new sub-Gaussian tails for the number of copies of small complete and complete bipartite graphs in the binomial random graph, extending results of Ruciński and Vu.

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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