Submanifold-genericity of $\mathbb{R}^d$-actions and uniform multiplicative Diophantine approximation
Prasuna Bandi, Reynold Fregoli, Dmitry Kleinbock
TL;DR
The paper proves a new ergodic theorem for ${\mathbb R}^{d}$-actions with averages over dilated submanifolds, yielding a quantitative error term under effective mixing. It then applies this abstract framework to multiplicative Diophantine approximation for ${m\times n}$ matrices, showing that almost all matrices are uniformly approximable by $x\mapsto x^{-1}(\log x)^{-1+\varepsilon}$ and connecting these results to Littlewood-type questions via dynamics on the space of lattices. The core methodology combines moment estimates and Borel–Cantelli arguments with a dynamical Dani correspondence, translating Diophantine properties into homogeneous-space dynamics and enabling Khintchine-type statements in the uniform setting. These contributions establish a robust link between submanifold-dilations, mixing rates, and uniform multiplicative approximation, with potential implications for conjectures in Diophantine approximation and uniform Dirichlet-type results.
Abstract
In this paper, we prove a new ergodic theorem for $\mathbb{R}^d$-actions involving averages over dilated submanifolds, thereby generalizing the theory of spherical averages. Our main result is a quantitative estimate for the error term of such averages valid for smooth functions under some effective mixing assumptions on the action. With the aid of this theorem, we investigate multiplicative-type Dirichlet-improvability for $(m\times n)$-matrices with real coefficients. In particular, we establish that almost all matrices are uniformly approximable by the function $x\mapsto x^{-1}(\log x)^{-1+\varepsilon}$ for any $\varepsilon>0$. Results of this type motivate a question which can be thought as a strengthening of Littlewood's conjecture in multiplicative Diophantine approximation.
