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Existing algorithms for fitting the parameters of a sinusoid to noisy discrete time observations are not always successful due to initial value sensitivity and other issues. This paper demonstrates the techniques of FIR filtering, Fast…

General Mathematics · Mathematics 2012-08-27 Francis J. O'Brien, , Nathan Johnnie

We study an approach to solving the phase retrieval problem as it arises in a phase-less imaging modality known as ptychography. In ptychography, small overlapping sections of an unknown sample (or signal, say $x_0\in \mathbb{C}^d$) are…

Numerical Analysis · Mathematics 2019-10-09 Brian Preskitt , Rayan Saab

An atomic force microscope (AFM) is capable of producing ultra-high resolution measurements of nanoscopic objects and forces. It is an indispensable tool for various scientific disciplines such as molecular engineering, solid-state physics,…

Applications · Statistics 2017-06-28 Bryan Yates , Aleksander Labuda , Martin Lysy

We propose an efficient protocol to fully reconstruct a set of high-fidelity quantum gates. Usually, the efficiency of reconstructing high-fidelity quantum gates is limited by the sampling noise. Our protocol is based on a perturbative…

Quantum Physics · Physics 2021-03-24 Ruyu Yang , Ying Li

We develop several algorithms for performing quantum phase estimation based on basic measurements and classical post-processing. We present a pedagogical review of quantum phase estimation and simulate the algorithm to numerically determine…

Quantum Physics · Physics 2013-07-30 Krysta M. Svore , Matthew B. Hastings , Michael Freedman

In this paper, we develop a concrete algorithm for phase retrieval, which we refer to as Gauss-Newton algorithm. In short, this algorithm starts with a good initial estimation, which is obtained by a modified spectral method, and then…

Information Theory · Computer Science 2018-02-12 Bing Gao , Zhiqiang Xu

The estimation of the frequencies of multiple superimposed exponentials in noise is an important research problem due to its various applications from engineering to chemistry. In this paper, we propose an efficient and accurate algorithm…

Numerical Analysis · Mathematics 2016-05-05 Shanglin Ye , Elias Aboutanios

Periodic nonuniform sampling is a known method to sample spectrally sparse signals below the Nyquist rate. This strategy relies on the implicit assumption that the individual samplers are exposed to the entire frequency range. This…

Information Theory · Computer Science 2009-01-27 Moshe Mishali , Yonina C. Eldar , Joel A. Tropp

This paper introduces a structural equation formulation that gives rise to a new family of quasi-periodic Gaussian processes, useful to process a broad class of natural and physiological signals. The proposed formulation simplifies…

Methodology · Statistics 2025-11-04 Unnati Nigam , Radhendushka Srivastava , Faezeh Marzbanrad , Michael Burke

Quantum phase estimation is a fundamental subroutine in many quantum algorithms, including Shor's factorization algorithm and quantum simulation. However, so far results have cast doubt on its practicability for near-term, non-fault…

Given a linear system in a real or complex domain, linear regression aims to recover the model parameters from a set of observations. Recent studies in compressive sensing have successfully shown that under certain conditions, a linear…

Statistics Theory · Mathematics 2016-11-15 Henrik Ohlsson , Allen Y. Yang , Roy Dong , S. Shankar Sastry

Phase retrieval consists in the recovery of a complex-valued signal from intensity-only measurements. As it pervades a broad variety of applications, many researchers have striven to develop phase-retrieval algorithms. Classical approaches…

This paper considers the problem of recovering a $k$-sparse, $N$-dimensional complex signal from Fourier magnitude measurements. It proposes a Fourier optics setup such that signal recovery up to a global phase factor is possible with very…

Information Theory · Computer Science 2014-10-28 Çağkan Yapar , Volker Pohl , Holger Boche

This paper introduces a quasi-Bayesian method that integrates frequentist nonparametric estimation with Bayesian inference in a two-stage process. Applied to an endogenous discrete choice model, the approach first uses kernel or sieve…

Econometrics · Economics 2025-05-20 Ruixuan Liu , Zhengfei Yu

The estimation of phase errors from digital-holography data is critical for applications such as imaging or wave-front sensing. Conventional techniques require multiple i.i.d. data and perform poorly in the presence of high noise or large…

Data Analysis, Statistics and Probability · Physics 2017-10-11 Casey J. Pellizzari , Mark F. Spencer , Charles A. Bouman

We address the problem of recovering a signal (up to global phase) from its short-time Fourier transform (STFT) magnitude measurements. This problem arises in several applications, including optical imaging and speech processing. In this…

Information Theory · Computer Science 2015-10-06 Tamir Bendory , Yonina C. Eldar

This paper proposes a new Bayesian strategy for the smooth estimation of altimetric parameters. The altimetric signal is assumed to be corrupted by a thermal and speckle noise distributed according to an independent and non identically…

Applications · Statistics 2016-04-20 Abderrahim Halimi , Corinne Mailhes , Jean-Yves Tourneret , Hichem Snoussi

This paper presents a novel approach for estimating the modes of an observed non-stationary mixture signal. A link is first established between the short-time Fourier transform and the sparse sampling theory, where the observations are…

Numerical Analysis · Mathematics 2022-12-23 Quentin Legros , Dominique Fourer

We study the problem of recovering the phase from magnitude measurements; specifically, we wish to reconstruct a complex-valued signal x of C^n about which we have phaseless samples of the form y_r = |< a_r,x >|^2, r = 1,2,...,m (knowledge…

Information Theory · Computer Science 2016-11-17 Emmanuel Candes , Xiaodong Li , Mahdi Soltanolkotabi

Topological phases of matter have sparked an immense amount of activity in recent decades. Topological materials are classified by topological invariants that act as a non-local order parameter for any symmetry and condition. As a result,…

Materials Science · Physics 2020-12-08 Oded Zilberberg