Toric Symplectic Geometry and Full Spark Frames

TL;DR

This paper explores the geometric structure of frame spaces using toric symplectic geometry, demonstrating that random frames are almost surely full spark and characterizing when these spaces have singularities.

Contribution

It establishes a novel connection between frame spaces and toric symplectic manifolds, enabling new insights into their probabilistic and geometric properties.

Findings

Random frames are almost surely full spark.

Frame spaces relate to toric symplectic manifolds.

Characterization of singularities in frame spaces.

Abstract

The collection of $d \times N$ complex matrices with prescribed column norms and prescribed (nonzero) singular values forms a compact algebraic variety, which we refer to as a frame space. Elements of frame spaces -- i.e., frames -- are used to give robust representations of complex-valued signals, so that geometrical and measure-theoretic properties of frame spaces are of interest to the signal processing community. This paper is concerned with the following question: what is the probability that a frame drawn uniformly at random from a given frame space has the property that any subset of $d$ of its columns gives a basis for $\mathbb{C}^d$? We show that the probability is one, generalizing recent work of Cahill, Mixon and Strawn. To prove this, we first show that frame spaces are related to highly structured objects called toric symplectic manifolds. This relationship elucidates the geometric meaning of eigensteps -- certain spectral invariants of a frame -- and should be a more broadly applicable tool for studying probabilistic questions about the structure of frame spaces. As another application of our symplectic perspective, we completely characterize the norm and spectral data for which the corresponding frame space has singularities, answering some open questions in the frame theory literature.