English

Optimal constants in concentration inequalities on the sphere and in the Gauss space

Probability 2026-04-02 v2 Functional Analysis

Abstract

We show several variants of concentration inequalities on the sphere stated as subgaussian estimates with optimal constants. For a Lipschitz function, we give one-sided and two-sided bounds for deviation from the median as well as from the mean. For example, we show that if μ\mu is the normalized surface measure on Sn1S^{n-1} with n3n\geq 3, f:Sn1Rf : S^{n-1} \to \mathbb{R} is 11-Lipschitz, MM is the median of ff, and t>0t >0, then μ(fM+t)12ent2/2\mu\big(f \geq M +t\big) \leq \frac 12 e^{-nt^2/2}. If MM is the mean of ff, we have a two-sided bound μ(fMt)ent2/2\mu\big(|f - M| \geq t\big) \leq e^{-nt^2/2}. Consequently, if γ\gamma is the standard Gaussian measure on Rn\mathbb{R}^n and f:RnRf : \mathbb{R}^{n} \to \mathbb{R} (again, 11-Lipschitz, with the mean equal to MM), then γ(fMt)et2/2\gamma \big(|f - M| \geq t\big) \leq e^{-t^2/2}. These bounds are slightly better and arguably more elegant than those available elsewhere in the literature.

Keywords

Cite

@article{arxiv.2406.13581,
  title  = {Optimal constants in concentration inequalities on the sphere and in the Gauss space},
  author = {Guillaume Aubrun and Justin Jenkinson and Stanislaw J. Szarek},
  journal= {arXiv preprint arXiv:2406.13581},
  year   = {2026}
}

Comments

30 pages, 6 figures; minor edits, added references; to be published in High Dimensional Probability, Vol 10