Limit theorems for mixed-norm sequence spaces with applications to volume distribution

TL;DR

This paper establishes limit theorems for mixed-norm sequence spaces and applies them to analyze volume distribution in the intersection of mixed-norm balls, using a new probabilistic representation of uniform distributions.

Contribution

It introduces a Poincaré-Maxwell-Borel lemma and limit theorems for mixed-norm spaces, advancing understanding of volume distribution in these geometric structures.

Findings

Proved a Poincaré-Maxwell-Borel lemma for scaled matrices in mixed-norm balls.

Derived central and non-central limit theorems for mixed-norm norms.

Analyzed asymptotic volume distribution in intersections of mixed-norm sequence balls.

Abstract

Let $p, q \in (0, \infty]$ and $\ell_p^m(\ell_q^n)$ be the mixed-norm sequence space of real matrices $x = (x_{i, j})_{i \leq m, j \leq n}$ endowed with the (quasi-)norm $\Vert x \Vert_{p, q} := \big\Vert \big( \Vert (x_{i, j})_{j \leq n} \Vert_q \big)_{i \leq m} \Vert_p$. We shall prove a Poincar\'e-Maxwell-Borel lemma for suitably scaled matrices chosen uniformly at random in the $\ell_p^m(\ell_q^n)$ unit balls $\mathbb{B}_{p, q}^{m, n}$, and obtain both central and non-central limit theorems for their $\ell_p(\ell_q)$-norms. We use those limit theorems to study the asymptotic volume distribution in the intersection of two mixed-norm sequence balls. Our approach is based on a new probabilistic representation of the uniform distribution on $\mathbb{B}_{p, q}^{m, n}$.