English

On phase and norm retrieval by subspaces

Functional Analysis 2026-01-06 v1

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=1NRN\{\varphi_i^\perp\}_{i=1}^N\subset \mathbb{R}^N allow norm retrieval and the vectors {φi}i=1N\{\varphi_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\{\varphi_i\}_{i=1}^M in RN\mathbb{R}^N is not dense in the set of all MM-element frames when M<2N1M < 2N-1. We extend this result to subspaces. Several alternative proofs of fundamental results in phase and norm retrieval are also provided.

Keywords

Cite

@article{arxiv.2601.01111,
  title  = {On phase and norm retrieval by subspaces},
  author = {Tin T. Tran and Phung T. Huynh},
  journal= {arXiv preprint arXiv:2601.01111},
  year   = {2026}
}
R2 v1 2026-07-01T08:49:12.935Z