On the timescale at which statistical stability breaks down

TL;DR

This paper investigates the timescale at which statistical stability breaks down in dynamical systems, specifically in the quadratic family, showing that for Misiurewicz parameters, instability appears after a time proportional to the inverse of parameter change.

Contribution

It provides a precise characterization of the timescale for statistical stability breakdown in quadratic maps with Misiurewicz parameters.

Findings

Statistical stability fails after a timescale proportional to |t|^{-1} for parameter changes of size t.

The result is sharp and applies specifically to the quadratic family with Misiurewicz parameters.

The study clarifies the relationship between parameter perturbations and observable statistical properties.

Abstract

In dynamical systems, understanding statistical properties shared by most orbits and how these properties depend on the system are basic and important questions. Statistical properties may persist as one perturbs the system (\emph{statistical stability} is said to hold), or may vary wildly. The latter case is our subject of interest, and we ask at what timescale does statistical stability break down. This is the time needed to observe, with a certain probability, a substantial difference in the statistical properties as described by (large but finite time) Birkhoff averages. The quadratic (or logistic) family is a natural and fundamental example where statistical stability does not hold. We study this family. When the base parameter is of Misiurewicz type, we show, sharply, that if the parameter changes by $t$, it is necessary and sufficient to observe the system for a time at least of the order of $|t|^{-1}$ to see the lack of statistical stability.