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arXiv 1709.01896math.PR
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一种异步多重合并的乘法合并算法

A multiplicative coalescent with asynchronous multiple mergers

Sophie Lemaire

摘要:

我们定义了一个马尔可夫过程的分区$[n]=\{1,\ldots,n\}$通过绘制一个样本在$[n]$在每一个时间的泊松过程,通过合并块,包含这些点之一,并保持所有其他块不变。这种合并过程出现在随机图过程的连通分量的研究中,其中连通子图随着时间的推移而增加,其概率仅取决于它们的大小。首先,我们确定的合并时间的渐近分布。然后,我们定义了一个Bienayme-Galton-Watson(BGW)过程,使得它的总总体规模支配一个元素的块大小。我们计算总人口大小分布和块大小分布之间的距离在一个时间成比例的$n$的界限。作为这一结果的第一个应用,我们建立了与此聚结过程相关的混凝方程。作为第二个应用程序,我们估计的最大块的大小在亚临界和超临界制度,以及在临界窗口。

英文摘要:

We define a Markov process on the partitions of $[n]=\{1,\ldots,n\}$ by drawing a sample in $[n]$ at each time of a Poisson process, by merging blocks that contain one of these points and by leaving all other blocks unchanged. This coalescent process appears in the study of the connected components of random graph processes in which connected subgraphs are added over time with probabilities that depend only on their size. First, we determine the asymptotic distribution of the coalescent time. Then, we define a Bienayme-Galton-Watson (BGW) process such that its total population size dominates the block size of an element. We compute a bound for the distance between the total population size distribution and the block size distribution at a time proportional to $n$. As a first application of this result, we establish the coagulation equations associated with this coalescent process. As a second application, we estimate the size of the largest block in the subcritical and supercritical regimes as well as in the critical window.

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