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arXiv 1809.01907math.CO
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图随机图中拼图渗流的明确阈值

The sharp threshold for jigsaw percolation in random graphs

Graz University of Technology(格拉茨工业大学);Goethe University(歌德大学);Queen Mary University of London(伦敦大学玛丽女王学院)

Oliver Cooley, Tobias Kapetanopoulos, Tamás Makai

AI总结:

研究确定了图随机图中拼图渗流的明确阈值,证明当两个概率乘积达到特定值时,渗流现象发生相变。

摘要:

我们分析了拼图渗流过程,该过程可以被视为判断两个在同一顶点集上的图是否`联合连接`的度量。Bollobás、Riordan、Slivken和Smith证明当两个图是独立的二项式随机图时,拼图过程是否渗流经历相变,当两个概率的乘积为Θ(1/(n ln n))时。我们证明这个阈值是明确的,并且位于1/(4n ln n)。

英文摘要:

We analyse the jigsaw percolation process, which may be seen as a measure of whether two graphs on the same vertex set are `jointly connected'. Bollobás, Riordan, Slivken and Smith proved that when the two graphs are independent binomial random graphs, whether the jigsaw process percolates undergoes a phase transition when the product of the two probabilities is $Θ\left( \frac{1}{n\ln n} \right)$. We show that this threshold is sharp, and that it lies at $\frac{1}{4n\ln n}$.

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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