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The problem of phase retrieval, i.e., the problem of recovering a function from the magnitudes of its Fourier transform, naturally arises in various fields of physics, such as astronomy, radar, speech recognition, quantum mechanics and,…

Functional Analysis · Mathematics 2020-02-17 Philipp Grohs , Sarah Koppensteiner , Martin Rathmair

The main result of this paper states that phase retrieval in infinite-dimensional Hilbert spaces is never uniformly stable, in sharp contrast to the finite dimensional setting in which phase retrieval is always stable. This leads us to…

Functional Analysis · Mathematics 2016-06-28 Jameson Cahill , Peter G. Casazza , Ingrid Daubechies

In the last five decades, iterative phase retrieval methods draw large amount of interest across the research community as a non-interferometric approach to recover quantitative phase distributions from one (or more) intensity measurement.…

Optics · Physics 2020-07-21 Nathaniel Hai , Joseph Rosen

Phase retrieval seeks to reconstruct a signal from phaseless intensity measurements and, in applications where measurements contain errors, demands stable reconstruction. We study local stability of phase retrieval in reproducing kernel…

Functional Analysis · Mathematics 2026-01-01 Hartmut Führ , Max Getter

One of the most powerful approaches to imaging at the nanometer or subnanometer length scale is coherent diffraction imaging using X-ray sources. For amorphous (non-crystalline) samples, the raw data can be interpreted as the modulus of the…

Numerical Analysis · Mathematics 2020-04-02 Alexander Barnett , Charles L. Epstein , Leslie Greengard , Jeremy Magland

In this paper we prove two results regarding reconstruction from magnitudes of frame coefficients (the so called "phase retrieval problem"). First we show that phase retrievability as an algebraic property implies that nonlinear maps are…

Functional Analysis · Mathematics 2015-06-09 Radu Balan , Dongmian Zou

As a generalization of the standard phase retrieval problem, we seek to reconstruct symmetric rank-1 matrices from inner products with subclasses of positive semidefinite matrices. For such subclasses, we introduce random cubatures for…

Numerical Analysis · Mathematics 2017-09-04 Martin Ehler , Manuel Graef , Franz J. Kiraly

Fusion frames are extensively studied due to their effectiveness in recovering signals from large-scale data. They are applicable in distributed processing, wireless sensor networks, and packet encoding systems due to their robustness and…

Functional Analysis · Mathematics 2025-08-26 Avinash Bhardwaj , Animesh Bhandari

We introduce a generalized version of phase retrieval called multiplexed phase retrieval. We want to recover the phase of amplitude-only measurements from linear combinations of them. This corresponds to the case in which multiple…

Image and Video Processing · Electrical Eng. & Systems 2019-07-02 Jonathan Dong , Florent Krzakala , Sylvain Gigan

The generalized phase retrieval problem over compact groups aims to recover a set of matrices -- representing an unknown signal -- from their associated Gram matrices. This framework generalizes the classical phase retrieval problem, which…

Signal Processing · Electrical Eng. & Systems 2025-11-20 Tal Amir , Tamir Bendory , Nadav Dym , Dan Edidin

In many areas of imaging science, it is difficult to measure the phase of linear measurements. As such, one often wishes to reconstruct a signal from intensity measurements, that is, perform phase retrieval. In several applications the…

Information Theory · Computer Science 2015-06-16 Afonso S. Bandeira , Dustin G. Mixon

We study theoretical limits of \emph{descending} phase retrieval algorithms. Utilizing \emph{Random duality theory} (RDT) we develop a generic program that allows statistical characterization of various algorithmic performance metrics.…

Machine Learning · Statistics 2025-06-24 Mihailo Stojnic

We make a detailed study of norm retrieval. We give several classification theorems for norm retrieval and give a large number of examples to go with the theory. One consequence is a new result about Parseval frames: If a Parseval frame is…

Functional Analysis · Mathematics 2017-01-30 Peter G. Casazza , Dorsa Ghoreishi , Shani Jose , Janet C. Tremain

We consider the phase retrieval problem of reconstructing a $n$-dimensional real or complex signal $\mathbf{X}^{\star}$ from $m$ (possibly noisy) observations $Y_\mu = | \sum_{i=1}^n \Phi_{\mu i} X^{\star}_i/\sqrt{n}|$, for a large class of…

Statistics Theory · Mathematics 2021-02-18 Antoine Maillard , Bruno Loureiro , Florent Krzakala , Lenka Zdeborová

Weaving Hilbert space frames have been introduced recently by Bemrose et al. to deal with some problems in distributed signal processing. In this paper, we survey this topic from the viewpoint of the duality principle, so we obtain new…

Functional Analysis · Mathematics 2019-09-20 Fahimeh Arabyani Neyshaburi , Ali Akbar Arefijamaal

A standardized phase retrieval algorithm is presented and applied to an industry-grade high-energy ultrashort pulsed laser to uncover its spatial phase distribution. We describe in detail how to modify the well-known algorithm in order to…

In phase retrieval, the goal is to recover a complex signal from the magnitude of its linear measurements. While many well-known algorithms guarantee deterministic recovery of the unknown signal using i.i.d. random measurement matrices,…

Information Theory · Computer Science 2017-03-24 Boshra Rajaei , Sylvain Gigan , Florent Krzakala , Laurent Daudet

An exact phase-retrievable frame $\{f_{i}\}_{i}^{N}$ for an $n$-dimensional Hilbert space is a phase-retrievable frame that fails to be phase-retrievable if any one element is removed from the frame. Such a frame could have different…

Functional Analysis · Mathematics 2017-06-26 Deguang Han , Ted Juste , Youfa Li , Wenchang Sun

Exploring the idea of phase retrieval has been intriguing researchers for decades, due to its appearance in a wide range of applications. The task of a phase retrieval algorithm is typically to recover a signal from linear phaseless…

Machine Learning · Statistics 2020-12-22 Naveed Naimipour , Shahin Khobahi , Mojtaba Soltanalian

So far there has not been paid attention to frames that are balanced, i.e. those frames which sum is zero. In this paper we consider balanced frames, and in particular balanced unit norm tight frames, in finite dimensional Hilbert spaces.…

Functional Analysis · Mathematics 2020-09-28 Sigrid B. Heineken , Patricia M. Morillas , Pablo Tarazaga