On phase and norm retrieval by subspaces
Abstract
This paper studies phase and norm retrieval by subspaces. We first investigate norm retrieval by hyperplanes. We show that if N hyperplanes \i\i=1N⊂ RN allow norm retrieval and the vectors \i\i=1N are linearly independent, then these vectors must be an orthonormal basis for RN. We then present several new properties of subspaces that allow phase and norm retrieval. In particular, we provide a complete classification of two proper subspaces that perform norm retrieval. It is known that the collection of norm-retrievable frames \i\i=1M in RN is not dense in the set of all M-element frames when M < 2N-1. We extend this result to subspaces. Several alternative proofs of fundamental results in phase and norm retrieval are also provided.
Turn this paper into a full lesson
ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.