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Gaussian limits for multidimensional random sequential packing at saturation

机译:饱和时多维随机顺序堆积的高斯极限

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摘要

Consider the random sequential packing model with infinite input and in any dimension. When the input consists of non-zero volume convex solids we show that the total number of solids accepted over cubes of volume lambda is asymptotically normal as lambda -> infinity. We provide a rate of approximation to the normal and show that the finite dimensional distributions of the packing measures converge to those of a mean zero generalized Gaussian field. The method of proof involves showing that the collection of accepted solids satisfies the weak spatial dependence condition known as stabilization.
机译:考虑具有无限输入和任意维度的随机顺序包装模型。当输入包含非零体积的凸形实体时,我们表明在体积为lambda的多维数据集上接受的实体总数在渐近正态上为lambda->无穷大。我们提供了与法线近似的比率,并证明了填充量度的有限维分布收敛于平均零广义高斯场的有限维分布。证明方法涉及证明可接受的固体的收集满足称为稳定的弱空间依赖性条件。

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