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Fourier PCA is Principal Component Analysis of a matrix obtained from higher order derivatives of the logarithm of the Fourier transform of a distribution.We make this method algorithmic by developing a tensor decomposition method for a…

Machine Learning · Computer Science 2014-07-01 Navin Goyal , Santosh Vempala , Ying Xiao

The problem 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 phase-less measurements.…

Signal Processing · Electrical Eng. & Systems 2020-03-11 Naveed Naimipour , Shahin Khobahi , Mojtaba Soltanalian

This paper considers the question of recovering the phase of an object from intensity-only measurements, a problem which naturally appears in X-ray crystallography and related disciplines. We study a physically realistic setup where one can…

Information Theory · Computer Science 2013-11-08 Emmanuel Candes , Xiaodong Li , Mahdi Soltanolkotabi

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 this paper, we provide a…

Information Theory · Computer Science 2013-09-13 Boris Alexeev , Afonso S. Bandeira , Matthew Fickus , Dustin G. Mixon

Reconstruction of undersampled periodic signals of unknown period is an important signal processing operation. It is especially difficult operation when the sequences of samples are short and no information on the inter-sequence time…

Signal Processing · Electrical Eng. & Systems 2021-05-18 Marek W. Rupniewski

We consider the recovery of a (real- or complex-valued) signal from magnitude-only measurements, known as phase retrieval. We formulate phase retrieval as a convex optimization problem, which we call PhaseMax. Unlike other convex methods…

Information Theory · Computer Science 2018-01-31 Tom Goldstein , Christoph Studer

The PhaseLift algorithm is an effective convex method for solving the phase retrieval problem from Fourier measurements with coded diffraction patterns (CDP). While exact reconstruction guarantees are well-established in the noiseless case,…

Numerical Analysis · Mathematics 2025-10-14 Meng Huang , Jinming Wen , Ran Zhang

Quantum signal processing (QSP) is a powerful quantum algorithm to exactly implement matrix polynomials on quantum computers. Asymptotic analysis of quantum algorithms based on QSP has shown that asymptotically optimal results can in…

Quantum Physics · Physics 2021-07-13 Yulong Dong , Xiang Meng , K. Birgitta Whaley , Lin Lin

We study the phase retrieval problem for the short-time Fourier transform on the groups $\mathbb{Z}$, $\mathbb{Z}_d$ and $\mathbb{R}^d$. As is well-known, phase retrieval is possible, once the window's ambiguity function vanishes nowhere.…

Functional Analysis · Mathematics 2022-06-15 David Bartusel

Phase retrieval has been an attractive but difficult problem rising from physical science, and there has been a gap between state-of-the-art theoretical convergence analyses and the corresponding efficient retrieval methods. Firstly, these…

Information Theory · Computer Science 2017-12-06 Gen Li , Yuchen Jiao , Yuantao Gu

The main objective of this paper is to find algorithms accompanied by explicit error bounds for phase retrieval from noisy magnitudes of frame coefficients when the underlying frame has a low redundancy. We achieve these goals with frames…

Functional Analysis · Mathematics 2014-12-23 Bernhard G. Bodmann , Nathaniel Hammen

We introduce a quantum algorithm to perform the Laplace transform on quantum computers. Already, the quantum Fourier transform (QFT) is the cornerstone of many quantum algorithms, but the Laplace transform or its discrete version has not…

Phase retrieval aims at recovering a complex-valued signal from magnitude-only measurements, which attracts much attention since it has numerous applications in many disciplines. However, phase recovery involves solving a system of…

Information Theory · Computer Science 2017-06-13 Wen-Jun Zeng , H. C. So

Phase retrieval algorithms have become an important component in many modern computational imaging systems. For instance, in the context of ptychography and speckle correlation imaging, they enable imaging past the diffraction limit and…

Machine Learning · Statistics 2018-07-03 Christopher A. Metzler , Philip Schniter , Ashok Veeraraghavan , Richard G. Baraniuk

Phase retrieval, i.e. the reconstruction of phase information from intensity information, is a central problem in many optical systems. Here, we demonstrate that a deep residual neural net is able to quickly and accurately perform this task…

Image and Video Processing · Electrical Eng. & Systems 2020-01-29 Leonhard MÖckl , Petar N. Petrov , W. E. Moerner

Proximal algorithms have gained popularity in recent years in large-scale and distributed optimization problems. One such problem is the phase retrieval problem, for which proximal operators have been proposed recently. The phase retrieval…

Optimization and Control · Mathematics 2018-08-16 Biel Roig-Solvas , Lee Makowski , Dana H. Brooks

We study the problem of partitioning a given simple polygon $P$ into a minimum number of connected polygonal pieces, each of bounded size. We describe a general technique for constructing such partitions that works for several notions of…

Computational Geometry · Computer Science 2024-10-23 Mikkel Abrahamsen , Nichlas Langhoff Rasmussen

Detecting and eliminating logic hazards in Boolean circuits is a fundamental problem in logic circuit design. We show that there is no $O(3^{(1-\epsilon)n} \text{poly}(s))$ time algorithm, for any $\epsilon > 0$, that detects logic hazards…

Computational Complexity · Computer Science 2020-06-19 Balagopal Komarath , Nitin Saurabh

Phase retrieval, a nonlinear problem prevalent in imaging applications, has been extensively studied using random models, some of which with i.i.d. sensing matrix components. While these models offer robust reconstruction guarantees, they…

Optics · Physics 2024-09-10 Zhiyuan Hu , Julián Tachella , Michael Unser , Jonathan Dong

We prove that recognizing the phase of matter of an unknown quantum state is quantum computationally hard. More specifically, we show that the quantum computational time of any phase recognition algorithm must grow exponentially in the…

Quantum Physics · Physics 2026-03-19 Thomas Schuster , Dominik Kufel , Norman Y. Yao , Hsin-Yuan Huang