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Arithmetic Progression Hypergraphs: Examining the Second Moment Method

机译:算术进展超图:检查第二次方法

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In many data structure settings, it has been shown that using "double hashing" in place of standard hashing, by which we mean choosing multiple hash values according to an arithmetic progression instead of choosing each hash value independently, has asymptotically negligible difference in performance. We attempt to extend these ideas beyond data structure settings by considering how threshold arguments based on second moment methods can be generalized to "arithmetic progression" versions of problems. With this motivation, we define a novel "quasi-random" hypergraph model, random arithmetic progression (AP) hypergraphs, which is based on edges that form arithmetic progressions and unifies many previous problems. Our main result is to show that second moment arguments for 3-NAE-SAT and 2-coloring of 3-regular hypergraphs extend to the double hashing setting. We can generalize these results to larger sized hyperedges, when randomly chosen hyperedges satisfy an appropriate notion limited independence. We leave several open problems related to these quasi-random hypergraphs and the thresholds of associated problem variations.
机译:在许多数据结构设置中,已经表明,使用“双散列”代替标准散列,我们的意思是根据算术进展选择多个哈希值,而不是独立选择每个哈希值,具有渐近可忽略的性能差异。我们通过考虑基于第二时刻方法的阈值参数,我们试图通过数据结构设置来扩展这些想法可以概括为“算术进展”问题。通过这种动机,我们定义了一种新颖的“准随机”超图模型,随机算术进展(AP)超图,其基于形成算术进展的边缘并统一许多先前问题。我们的主要结果是显示3-nae-sat的第二个时刻参数和3常长的3常图像的2色延伸到双散列设置。我们可以将这些结果概括为更大尺寸的超高度,当随机选择的超高限制有限的独立性。我们留下与这些准随机超图相关的几个打开问题以及相关问题变化的阈值。

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