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arXiv 1003.3632math.PR
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马尔可夫分枝树的标度极限及其在Galton-Watson和随机无序树中的应用

Scaling limits of Markov branching trees with applications to Galton-Watson and random unordered trees

Bénédicte Haas, Grégory Miermont

摘要:

我们考虑一个家庭的随机树满足马尔可夫分支性质。粗略地说,这个性质是说,在某个给定高度以上的子树是独立的,只依赖于它们的总大小,后者是叶子或顶点的数量。这样的家庭是参数化的分布序列的分区的整数,确定如何大小的树是分布在其不同的子树。根据这些分布的一些自然假设,规定“宏观”分裂事件是罕见的,我们表明,马尔可夫分支树承认所谓的自相似的碎片树的Gromov-Hausdorff-Prokhorov拓扑的缩放限制。这些结果的主要应用是随机均匀无序树的标度极限是布朗连续随机树。这推广了Marckert-Miermont的一个结果,并充分证明了Aldous的一个猜想.我们还恢复,偶尔延长,结果一致的马尔可夫分支模型和已知的收敛结果的高尔顿-沃森树的布朗和稳定的连续随机树的缩放限制。

英文摘要:

We consider a family of random trees satisfying a Markov branching property. Roughly, this property says that the subtrees above some given height are independent with a law that depends only on their total size, the latter being either the number of leaves or vertices. Such families are parameterized by sequences of distributions on partitions of the integers that determine how the size of a tree is distributed in its different subtrees. Under some natural assumption on these distributions, stipulating that "macroscopic" splitting events are rare, we show that Markov branching trees admit the so-called self-similar fragmentation trees as scaling limits in the Gromov-Hausdorff-Prokhorov topology. The main application of these results is that the scaling limit of random uniform unordered trees is the Brownian continuum random tree. This extends a result by Marckert-Miermont and fully proves a conjecture by Aldous. We also recover, and occasionally extend, results on scaling limits of consistent Markov branching models and known convergence results of Galton-Watson trees toward the Brownian and stable continuum random trees.

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