From Rates of mixing to recurrence times via large deviations

TL;DR

This paper explores how stochastic-like statistical properties in dynamical systems imply underlying geometric structures, establishing a two-way connection and deriving new large deviation results for specific systems.

Contribution

It demonstrates that stochastic-like behavior implies geometric properties in dynamical systems, providing necessary and sufficient conditions, and introduces new large deviation results for Viana maps and piecewise expanding maps.

Findings

Stochastic-like behavior implies certain geometric structures.

Established necessary and sufficient conditions for statistical properties.

Derived new large deviation results for Viana maps and multidimensional maps.

Abstract

A classic approach in dynamical systems is to use particular geometric structures to deduce statistical properties, for example the existence of invariant measures with stochastic-like behaviour such as large deviations or decay of correlations. Such geometric structures are generally highly non-trivial and thus a natural question is the extent to which this approach can be applied. In this paper we show that in many cases stochastic-like behaviour itself implies that the system has certain non-trivial geometric properties, which are therefore necessary as well as sufficient conditions for the occurrence of the statistical properties under consideration. As a by product of our techniques we also obtain some new results on large deviations for certain classes of systems which include Viana maps and multidimensional piecewise expanding maps.