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In this paper, we primarily focus on analyzing the stability property of phase retrieval by examining the bi-Lipschitz property of the map $\Phi_{\boldsymbol{A}}(\boldsymbol{x})=|\boldsymbol{A}\boldsymbol{x}|\in \mathbb{R}_+^m$, where…

Information Theory · Computer Science 2024-04-17 Yu Xia , Zhiqiang Xu , Zili Xu

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

The aim of this paper is to study the stability of the $\ell_1$ minimization for the compressive phase retrieval and to extend the instance-optimality in compressed sensing to the real phase retrieval setting. We first show that the…

Functional Analysis · Mathematics 2016-01-12 Bing Gao , Yang Wang , Zhiqiang Xu

The classical phase retrieval problem arises in contexts ranging from speech recognition to x-ray crystallography and quantum state tomography. The generalization to matrix frames is natural in the sense that it corresponds to quantum…

Quantum Physics · Physics 2022-09-13 Radu Balan , Chris B. Dock

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

A frame $(x_j)_{j\in J}$ for a Hilbert space $H$ is said to do phase retrieval if for all distinct vectors $x,y\in H$ the magnitude of the frame coefficients $(|\langle x, x_j\rangle|)_{j\in J}$ and $(|\langle y, x_j\rangle|)_{j\in J}$…

Functional Analysis · Mathematics 2022-12-22 Wedad Alharbi , Salah Alshabhi , Daniel Freeman , Dorsa Ghoreishi

Phase retrieval refers to the problem of recovering some signal (which is often modelled as an element of a Hilbert space) from phaseless measurements. It has been shown that in the deterministic setting phase retrieval from frame…

Numerical Analysis · Mathematics 2021-11-11 Rima Alaifari , Matthias Wellershoff

Let $(\Omega,\Sigma,\mu)$ be a measure space, and $1\leq p\leq \infty$. A subspace $E\subseteq L_p(\mu)$ is said to do stable phase retrieval (SPR) if there exists a constant $C\geq 1$ such that for any $f,g\in E$ we have $$…

Functional Analysis · Mathematics 2022-10-12 D. Freeman , T. Oikhberg , B. Pineau , M. A. Taylor

Recent advances in convex optimization have led to new strides in the phase retrieval problem over finite-dimensional vector spaces. However, certain fundamental questions remain: What sorts of measurement vectors uniquely determine every…

Functional Analysis · Mathematics 2013-10-16 Afonso S. Bandeira , Jameson Cahill , Dustin G. Mixon , Aaron A. Nelson

Phase retrieval is concerned with recovering a function $f$ from the absolute value of its Fourier transform $|\widehat{f}|$. We study the stability properties of this problem in Lebesgue spaces. Our main results shows that $$ \|…

Functional Analysis · Mathematics 2021-03-29 Stefan Steinerberger

A frame $(x_j)_{j\in J}$ for a Hilbert space $H$ is said to do phase retrieval if for all distinct vectors $x,y\in H$ the magnitude of the frame coefficients $(|\langle x, x_j\rangle|)_{j\in J}$ and $(|\langle y, x_j\rangle|)_{j\in J}$…

Functional Analysis · Mathematics 2022-12-29 Wedad Alharbi , Daniel Freeman , Dorsa Ghoreishi , Claire Lois , Shanea Sebastian

In this paper, we focus on low-rank phase retrieval, which aims to reconstruct a matrix $\mathbf{X}_0\in \mathbb{R}^{n\times m}$ with ${\mathrm{ rank}}(\mathbf{X}_0)\le r$ from noise-corrupted amplitude measurements…

Information Theory · Computer Science 2025-09-30 Huanmin Ge , Zhiqiang Xu

We consider the one-dimensional Schroedinger equation on a ring, with the cubic term, of either self-attractive or repulsive sign, confined to a narrow segment. This setting can be realized in optics and Bose-Einstein condensates. For the…

Optics · Physics 2018-11-14 Elad Shamriz , Boris A. Malomed

In this paper, we consider the phase retrieval problem in which one aims to recover a signal from the magnitudes of affine measurements. Let $\{{\mathbf a}_j\}_{j=1}^m \subset {\mathbb H}^d$ and ${\mathbf b}=(b_1, \ldots,…

Information Theory · Computer Science 2016-08-23 Bing Gao , Qiyu Sun , Yang Wang , Zhiqiang Xu

The stability of an approximating sequence $(A_n)$ for an operator $A$ usually requires, besides invertibility of $A$, the invertibility of further operators, say $B, C, \dots$, that are well-associated to the sequence $(A_n)$. We study…

Numerical Analysis · Mathematics 2023-10-13 Marko Lindner , Dennis Schmeckpeper

In this short note, we consider the worst case noise robustness of any phase retrieval algorithm which aims to reconstruct all nonvanishing vectors $\mathbf{x} \in \mathbb{C}^d$ (up to a single global phase multiple) from the magnitudes of…

Numerical Analysis · Mathematics 2018-06-22 Mark A. Iwen , Sami Merhi , Michael Perlmutter

Recent results in the literature provide computational evidence that stabilized semi-implicit time-stepping method can efficiently simulate phase field problems involving fourth-order nonlinear dif- fusion, with typical examples like the…

Numerical Analysis · Mathematics 2016-06-22 Dong Li , Zhonghua Qiao , Tao Tang

The aim of noisy phase retrieval is to estimate a signal $\mathbf{x}_0\in \mathbb{C}^d$ from $m$ noisy intensity measurements $b_j=\left\lvert \langle \mathbf{a}_j,\mathbf{x}_0 \rangle \right\rvert^2+\eta_j, \; j=1,\ldots,m$, where…

Information Theory · Computer Science 2021-12-30 Meng Huang , Zhiqiang Xu

We derive bounds for the minimum and maximum eigenvalues and the spectral condition number of matrices for isogeometric discretizations of elliptic partial differential equations in an open, bounded, simply connected Lipschitz domain…

Numerical Analysis · Mathematics 2014-06-27 Krishan P. S. Gahalaut , Satyendra K. Tomar , Craig. C. Douglas

We study information theoretic limits of recovering an unknown $n$ dimensional, complex signal vector $\mathbf{x}_\star$ with unit norm from $m$ magnitude-only measurements of the form $y_i = |(\mathbf{A} \mathbf{x}_\star)_i|^2, \; i = 1,2…

Statistics Theory · Mathematics 2020-08-05 Rishabh Dudeja , Junjie Ma , Arian Maleki
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