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arXiv 1806.02565math.PR
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存在硬墙时的分支随机游走

Branching random walk in the presence of a hard wall

Rishideep Roy

AI总结:

本文研究带硬墙约束的 d 叉树分支随机游走,计算其在第 n 代所有顶点均为正的概率,并证明正性条件下典型顶点的高斯变量条件期望比期望最大值小 log n 阶。

摘要:

我们考虑高度为 $n$($n \in \mathbb{N}$)的 $d$ 叉树上的分支随机游走,在存在硬墙限制每个值为正的条件下,其中 $d$ 是满足 $d\geqslant2$ 的自然数。对于具有长程相互作用的高斯过程,例如离散高斯自由场,在其在大子集顶点上为正的条件下,其行为问题以及与该过程期望最大值的关系已被观察到。我们找到了分支随机游走在第 $n$ 代每个顶点处均为正的事件的概率,并证明了在正性条件下,典型顶点处高斯变量的条件期望比期望最大值小 $\log n$ 阶。

英文摘要:

We consider a branching random walk on a $d$-ary tree of height $n$ ($n \in \mathbb{N}$), under the presence of a hard wall which restricts each value to be positive, where $d$ is a natural number satisfying $d\geqslant2$. The question of behaviour of Gaussian processes with long range interactions, for example the discrete Gaussian free field, under the condition that it is positive on a large subset of {\color{blue}vertices}, and a relation with the expected maximum of the processes has been observed. We find the probability of the event that the branching random {\color{blue}walk} is positive at every vertex in the $n^{th}$ generation, and show that the conditional expectation of the Gaussian variable at a typical vertex, under positivity, is less than the expected maximum by order of $\log n$.

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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