The multilinear circle method and a question of Bergelson

TL;DR

This paper proves pointwise convergence of multilinear polynomial ergodic averages for measure-preserving systems with multiple transformations, advancing the understanding of polynomial ergodic theory and answering a longstanding question of Bergelson.

Contribution

It introduces a multilinear circle method and extends the Ionescu-Wainger multiplier theorem to canonical fractions, providing new tools for polynomial ergodic averages and higher order Fourier analysis.

Findings

Established pointwise convergence for multilinear polynomial ergodic averages.

Developed a versatile multilinear circle method and extended the Ionescu-Wainger multiplier theorem.

Proved sharp multilinear $L^p$-improving bounds and an inverse theorem in higher order Fourier analysis.

Abstract

Let $k\in \mathbb Z_+$ and $(X, \mathcal B(X), \mu)$ be a probability space equipped with a family of commuting invertible measure-preserving transformations $T_1,\ldots, T_k \colon X\to X$. Let $P_1,\ldots, P_k\in\mathbb Z[\rm n]$ be polynomials with integer coefficients and distinct degrees. We establish pointwise almost everywhere convergence of the multilinear polynomial ergodic averages \[A_{N; X, T_1,\ldots, T_k}^{P_1,\ldots, P_k}(f_1,\ldots, f_k)(x) = \frac{1}{N}\sum_{n=1}^Nf_1\big(T_1^{P_1(n)}x\big)\cdots f_k\big(T_k^{P_k(n)}x\big), \qquad x\in X, \]cas $N\to\infty$ for any functions $f_1, \ldots, f_k\in L^{\infty}(X)$. Besides a couple of results in the bilinear setting (when $k=2$ and then only for single transformations), this is the first pointwise result for general polynomial multilinear ergodic averages in arbitrary measure-preserving systems. This answers a question of Bergelson from 1996 in the affirmative for any polynomials with distinct degrees, and makes progress on the Furstenberg-Bergelson-Leibman conjecture. In this paper, we build a versatile multilinear circle method by developing the Ionescu-Wainger multiplier theorem for the set of canonical fractions, which gives a positive answer to a question of Ionescu and Wainger from 2005. We also establish sharp multilinear $L^p$-improving bounds and an inverse theorem in higher order Fourier analysis for averages over polynomial corner configurations, which we use to establish a multilinear analogue of Weyl's inequality and its real counterpart, a Sobolev smoothing inequality.