Multi-scale sparse domination
David Beltran, Joris Roos, Andreas Seeger
TL;DR
This work develops a comprehensive framework for multi-scale sparse domination of linear operators, culminating in a bilinear (p,q') sparse bound for sums T=∑_j T_j under natural scale- and regularity-conditions. The authors extend sparse domination to vector-valued settings, derive necessary conditions, and apply the framework to a broad array of operators, including Fourier multipliers, maximal functions, square functions, and variation-norm operators, with consequences for weighted inequalities. The core contributions include a sharp main theorem, a robust single-scale analysis, a resolution-of-identity tool, and a suite of multiplier theorems that yield new sparse bounds in diverse contexts. The results unify and extend prior sparse domination results beyond Calderón–Zygmund theory, with potential impact on analysis in multiple scales, oscillatory phenomena, and weighted harmonic analysis. Overall, the paper provides a versatile, broadly applicable approach to sparse domination that yields concrete quantitative bounds for a wide class of multi-scale operators.
Abstract
We prove a bilinear form sparse domination theorem that applies to many multi-scale operators beyond Calderón-Zygmund theory, and also establish necessary conditions. Among the applications, we cover large classes of Fourier multipliers, maximal functions, square functions and variation norm operators.
