English

Concentration for Poisson functionals: component counts in random geometric graphs

Probability 2016-01-14 v2

Abstract

Upper bounds for the probabilities P(FEF+r)\mathbb{P}(F\geq \mathbb{E} F + r) and P(FEFr)\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.

Keywords

Cite

@article{arxiv.1506.08191,
  title  = {Concentration for Poisson functionals: component counts in random geometric graphs},
  author = {Sascha Bachmann},
  journal= {arXiv preprint arXiv:1506.08191},
  year   = {2016}
}

Comments

26 pages, 1 figure

R2 v1 2026-06-22T10:01:08.939Z