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Phase retrieval aims to recover a signal $x \in \mathbb{C}^{n}$ from its amplitude measurements $|<x, a_i > |^2$, $i=1,2,...,m$, where $a_i$'s are over-complete basis vectors, with $m$ at least $3n -2$ to ensure a unique solution up to a…

Optimization and Control · Mathematics 2014-10-09 Penghang Yin , Jack Xin

A fundamental task in phase retrieval is to recover an unknown signal $\vx\in \Rn$ from a set of magnitude-only measurements $y_i=\abs{\nj{\va_i,\vx}}, \; i=1,\ldots,m$. In this paper, we propose two novel perturbed amplitude models (PAMs)…

Numerical Analysis · Mathematics 2021-12-16 Jian-Feng Cai , Meng Huang , Dong Li , Yang Wang

We consider the problem of high-dimensional misspecified phase retrieval. This is where we have an $s$-sparse signal vector $\mathbf{x}_*$ in $\mathbb{R}^n$, which we wish to recover using sampling vectors…

Information Theory · Computer Science 2017-12-14 Yan Shuo Tan

The problem of phase retrieval is to determine a signal $f\in \mathcal{H}$, with $\mathcal{H}$ a Hilbert space, from intensity measurements $|F(\omega)|$, where $F(\omega):=\langle f , \varphi_\omega\rangle$ are measurements of $f$ with…

Functional Analysis · Mathematics 2017-02-02 Rima Alaifari , Ingrid Daubechies , Philipp Grohs , Rujie Yin

Phase retrieval problem has been studied in various applications. It is an inverse problem without the standard uniqueness guarantee. To make complete theoretical analyses and devise efficient algorithms to recover the signal is…

Information Theory · Computer Science 2019-05-22 Ziyang Yuan , Hongxia Wang

High-Throughput materials discovery involves the rapid synthesis, measurement, and characterization of many different but structurally-related materials. A key problem in materials discovery, the phase map identification problem, involves…

Iterative projection algorithms are successfully being used as a substitute of lenses to recombine, numerically rather than optically, light scattered by illuminated objects. Images obtained computationally allow aberration-free…

Optics · Physics 2007-05-23 S. Marchesini

We design a system of phase oscillators that is able to produce temporally periodic sequences of patterns. Patterns are cluster partitions which encode information as phase differences between phase oscillators. The architecture of our…

Chaotic Dynamics · Physics 2012-01-18 Pablo Kaluza , Hildegard Meyer-Ortmanns

Fourier phase retrieval is the problem of reconstructing a signal given only the magnitude of its Fourier transformation. Optimization-based approaches, like the well-established Gerchberg-Saxton or the hybrid input output algorithm,…

Image and Video Processing · Electrical Eng. & Systems 2021-06-21 Tobias Uelwer , Tobias Hoffmann , Stefan Harmeling

Iterative phase retrieval algorithms are widely used in digital optics for their efficiency and simplicity. Conventionally, these algorithms do not consider aberrations as they assume an ideal, aberration-free optical system. Here, we…

Optics · Physics 2025-02-10 Dylan Brault , Corinne Fournier , Tatiana Latychevskaia

The problem of recovering a vector from the absolute values of its inner products against a family of measurement vectors has been well studied in mathematics and engineering. A generalization of this phase retrieval problem also exists in…

Functional Analysis · Mathematics 2013-07-19 Jameson Cahill , Peter G. Casazza , Jesse Peterson , Lindsey Woodland

Phase retrieval refers to the problem of recovering a signal $\mathbf{x}_{\star}\in\mathbb{C}^n$ from its phaseless measurements $y_i=|\mathbf{a}_i^{\mathrm{H}}\mathbf{x}_{\star}|$, where $\{\mathbf{a}_i\}_{i=1}^m$ are the measurement…

Information Theory · Computer Science 2020-09-10 Junjie Ma , Rishabh Dudeja , Ji Xu , Arian Maleki , Xiaodong Wang

Hypercomplex signal processing (HSP) offers powerful tools for analyzing and processing multidimensional signals by explicitly exploiting inter-dimensional correlations through Clifford algebra. In recent years, hypercomplex formulations of…

Signal Processing · Electrical Eng. & Systems 2026-03-02 Kumar Vijay Mishra , Henry Arguello , Brian M. Sadler

We study convex relaxation algorithms for phase retrieval on imaging problems. We show that structural assumptions on the signal and the observations, such as sparsity, smoothness or positivity, can be exploited to both speed-up convergence…

Optimization and Control · Mathematics 2014-04-09 Fajwel Fogel , Irène Waldspurger , Alexandre d'Aspremont

This work introduces a novel Fourier phase retrieval model, called polarimetric phase retrieval that enables a systematic use of polarization information in Fourier phase retrieval problems. We provide a complete characterization of…

Signal Processing · Electrical Eng. & Systems 2022-06-28 Julien Flamant , Konstantin Usevich , Marianne Clausel , David Brie

Adaptable computing is an increasingly important paradigm that specializes system resources to variable application requirements, environmental conditions, or user requirements. Adapting computing resources to variable application…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-11-03 Keeley Criswell , Tosiron Adegbija

The phase retrieval problem is found in various areas of applications of engineering and applied physics. It is also a very active field of research in mathematics, signal processing and machine learning. In this paper, we present an…

Optimization and Control · Mathematics 2023-04-26 Rossen Nenov , Dang-Khoa Nguyen , Peter Balazs

We propose a network of oscillators to retrieve given patterns in which the oscillators keep a fixed phase relationship with one another. In this description, the phase and the amplitude of the oscillators can be regarded as the timing and…

adap-org · Physics 2009-10-22 Toshio Aoyagi

RESPACK is a first-principles calculation software for evaluating the interaction parameters of materials and is able to calculate maximally localized Wannier functions, response functions based on the random phase approximation and related…

The phase retrieval problem asks to recover a natural signal $y_0 \in \mathbb{R}^n$ from $m$ quadratic observations, where $m$ is to be minimized. As is common in many imaging problems, natural signals are considered sparse with respect to…

Information Theory · Computer Science 2018-07-12 Paul Hand , Oscar Leong , Vladislav Voroninski