论文标题
泊松空间上的定量两尺度稳定
Quantitative two-scale stabilization on the Poisson space
论文作者
论文摘要
我们建立了评估泊松随机度量(可能多维)功能的分布与高斯元素的分布之间的距离。我们的边界仅涉及一个订单的添加成本运算符 - 我们在两个不同的尺度上进行了评估和比较 - 专门针对研究弱稳定形式的几何函数序列的高斯波动 - 参见Penrose和Yukich(2001)和Penrose(2005)。我们的主要界限扩展了Chatterjee和Sen(2017)最近利用的估计值,证明了中央限制定理(CLT)的定量版本,用于基于泊松的欧几里得最小生成树(MST)的长度。 We develop in full detail three applications of our bounds, namely: (i) to a quantitative multidimensional spatial CLT for functionals of the on-line nearest neighbor graph, (ii) to a quantitative multidimensional CLT involving functionals of the empirical measure associated with the edge-length of the Euclidean MST, and (iii) to a collection of multidimensional CLTs for geometric functionals of the excursion set of重尾射击噪声随机字段。应用(i)基于具有强大稳定功能的一般概率近似值的集合,即具有独立关注的功能。
We establish inequalities for assessing the distance between the distribution of a (possibly multidimensional) functional of a Poisson random measure and that of a Gaussian element. Our bounds only involve add-one cost operators at the order one - that we evaluate and compare at two different scales - and are specifically tailored for studying the Gaussian fluctuations of sequences of geometric functionals displaying a form of weak stabilization - see Penrose and Yukich (2001) and Penrose (2005). Our main bounds extend the estimates recently exploited by Chatterjee and Sen (2017) in the proof of a quantitative version of the central limit theorem (CLT) for the length of the Poisson-based Euclidean minimal spanning tree (MST). We develop in full detail three applications of our bounds, namely: (i) to a quantitative multidimensional spatial CLT for functionals of the on-line nearest neighbor graph, (ii) to a quantitative multidimensional CLT involving functionals of the empirical measure associated with the edge-length of the Euclidean MST, and (iii) to a collection of multidimensional CLTs for geometric functionals of the excursion set of heavy-tailed shot noise random fields. Application (i) is based on a collection of general probabilistic approximations for strongly stabilizing functionals, that is of independent interest.