Eigenvalue estimates for Fourier concentration operators on two domains

TL;DR

This paper provides non-asymptotic eigenvalue estimates for Fourier concentration operators on complex domains, quantifying their deviation from ideal projectors and applicable to non-convex, non-symmetric regions.

Contribution

It introduces new eigenvalue bounds for Fourier concentration operators on general domains, including non-convex and non-symmetric ones, extending previous work limited to convex intervals.

Findings

Eigenvalue estimates depend on domain geometry.

Bounds are non-asymptotic and nearly match asymptotic benchmarks.

Applicable to complex, non-convex, non-symmetric domains.

Abstract

We study concentration operators associated with either the discrete or the continuous Fourier transform, that is, operators that incorporate a spatial cut-off and a subsequent frequency cut-off to the Fourier inversion formula. Their spectral profiles describe the number of prominent degrees of freedom in problems where functions are assumed to be supported on a certain domain and their Fourier transforms are known or measured on a second domain. We derive eigenvalue estimates that quantify the extent to which Fourier concentration operators deviate from orthogonal projectors, by bounding the number of eigenvalues that are away from 0 and 1 in terms of the geometry of the spatial and frequency domains, and a factor that grows at most poly-logarithmically on the inverse of the spectral margin. The estimates are non-asymptotic in the sense that they are applicable to concrete domains and spectral thresholds, and almost match asymptotic benchmarks. Our work covers for the first time non-convex and non-symmetric spatial and frequency concentration domains, as demanded by numerous applications that exploit the expected approximate low dimensionality of the modeled phenomena. The proofs build on Israel's work on one dimensional intervals [arXiv: 1502.04404v1]. The new ingredients are the use of redundant wave-packet expansions and a dyadic decomposition argument to obtain Schatten norm estimates for Hankel operators.