Gaussian limits for multidimensional random sequential packing at saturation (extended version)

Abstract

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 $\lambda \to \infty$. 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.

31 pages

References in corpus (2)

• Random Sequential Addition of Hard Spheres in High Euclidean Dimensions
• Gaussian limits for random measures in geometric probability

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