An extension of the Wiener-Wintner ergodic theorem for pointwise jointly ergodic systems and its applications

TL;DR

This paper extends the Wiener-Wintner ergodic theorem to pointwise jointly ergodic systems with nilsequence weights and explores applications like convergence of weighted averages and subsequence ergodic averages.

Contribution

It introduces an extension of the Wiener-Wintner theorem for joint ergodic systems with nilsequence weights, advancing ergodic theory.

Findings

Extended Wiener-Wintner theorem to joint systems with nilsequences

Proved mean convergence of weighted ergodic averages

Established almost everywhere convergence along subsequences

Abstract

A joint measure-preserving system is $(X, \mathcal{B}, \mu_{1}, \dots, \mu_{k}, T_{1}, \dots, T_{k})$, where each $(X, \mathcal{B}, \mu_{i}, T_{i})$ is a measure-preserving system and any $\mu_{i}$ and $\mu_{j}$ are mutually absolutely continuous probability measures. Such a system is called pointwise jointly ergodic if, for any set of bounded measurable functions $f_{1}, \dots, f_{k}$ on $X$, the multilinear ergodic average of their joint action under the transformations $T_{1}, \dots, T_{k}$ converges almost everywhere to the product of their integrals with respect to the corresponding measures. In this paper, we extend the classical Wiener-Wintner ergodic theorem to the setting of pointwise jointly ergodic systems with nilsequences weight. Additionally, we provide applications that include results on the mean convergence of weighted ergodic averages and the almost everywhere convergence of ergodic averages taken along subsequences of the form $\lfloor \alpha n \rfloor$, where $\alpha \geq 1$.