Concentration for Poisson functionals: component counts in random geometric graphs

preprint2016arXivOpen access

Abstract

Upper bounds for the probabilities P(F≥EF+r)\mathbb{P}(F\geq \mathbb{E} F + r) and P(F≤EF−r)\mathbb{P}(F\leq \mathbb{E} F - r) are proved, where FF is a certain component count associated with a random geometric graph built over a Poisson point process on Rd\mathbb{R}^d. The bounds for the upper tail decay exponentially, and the lower tail estimates even have a Gaussian decay. For the proof of the concentration inequalities, recently developed methods based on logarithmic Sobolev inequalities are used and enhanced. A particular advantage of this approach is that the resulting inequalities even apply in settings where the underlying Poisson process has infinite intensity measure.

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