Large Deviations and Effective Equidistribution
Ilya Khayutin

TL;DR
This paper develops large deviation estimates for averaging operators in dynamical systems, applying them to effective equidistribution on arithmetic quotients, with new results on measure rigidity and non-escape of mass in non-archimedean settings.
Contribution
It introduces sharp large deviation bounds for averaging operators and applies them to effective equidistribution, measure rigidity, and non-escape of mass in S-arithmetic quotients.
Findings
Effective large deviation estimates in terms of spectral gap.
Effective rigidity results for measures with large entropy.
Non-escape of mass for measures with large entropy in non-archimedean settings.
Abstract
We study large deviations for measurable averaging operators on state spaces of dynamical systems. Our main motivation is the Hecke operators on the modular curve Y_0(p^n) and their generalization to higher rank S-arithmetic quotients. We prove a relatively sharp large deviations result in terms of the norm of the averaging operator restricted to the orthogonal complement of the constant functions in L2. In the self-adjoint case this norm is expressible by the spectral gap. Developing ideas of Linnik and Ellenberg, Michel and Venkatesh, we use this large deviation result to prove an effective equidistribution theorem on a state space. The novelty of our results is that they apply to measures with sub-optimal bounds on the mass of Bowen balls. We present two new applications to our effective equidistribution result. The first one is effective rigidity for the measure of maximal…
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