Random walks on hyperbolic spaces: Concentration inequalities and probabilistic Tits alternative

Author:

Aoun Richard,Sert CagriORCID

Abstract

AbstractThe goal of this article is two-fold: in a first part, we prove Azuma–Hoeffding type concentration inequalities around the drift for the displacement of non-elementary random walks on hyperbolic spaces. For a proper hyperbolic spaceM, we obtain explicit bounds that depend only onM, the size of support of the measure as in the classical case of sums of independent random variables, and on the norm of the driving probability measure in the left regular representation of the group of isometries. We obtain uniform bounds in the case of hyperbolic groups and effective bounds for simple linear groups of rank-one. In a second part, using our concentration inequalities, we give quantitative finite-time estimates on the probability that two independent random walks on the isometry group of a hyperbolic space generate a free non-abelian subgroup. Our concentration results follow from a more general, but less explicit statement that we prove for cocycles which satisfy a certain cohomological equation. For example, this also allows us to obtain subgaussian concentration bounds around the top Lyapunov exponent of random matrix products in arbitrary dimension.

Funder

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Alexander von Humboldt-Stiftung

Publisher

Springer Science and Business Media LLC

Subject

Statistics, Probability and Uncertainty,Statistics and Probability,Analysis

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Stationary measures for SL2(ℝ)-actions on homogeneous bundles over flag varieties;Journal für die reine und angewandte Mathematik (Crelles Journal);2024-07-26

2. Random walks on hyperbolic spaces: second order expansion of the rate function at the drift;Journal de l’École polytechnique — Mathématiques;2023-03-20

3. Effective drift estimates for random walks on graph products;Electronic Communications in Probability;2023-01-01

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