On phase and norm retrieval by subspaces

preprint2026arXivOpen access

Abstract

This paper studies phase and norm retrieval by subspaces. We first investigate norm retrieval by hyperplanes. We show that if NN hyperplanes {φi⊥}i=1N⊂RN\{φ_i^\perp\}_{i=1}^N\subset \mathbb{R}^N allow norm retrieval and the vectors {φi}i=1N\{φ_i\}_{i=1}^N are linearly independent, then these vectors must be an orthonormal basis for RN\mathbb{R}^N. 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 {φi}i=1M\{φ_i\}_{i=1}^M in RN\mathbb{R}^N is not dense in the set of all MM-element frames when M<2N−1M < 2N-1. We extend this result to subspaces. Several alternative proofs of fundamental results in phase and norm retrieval are also provided.

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