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Light Detection and Ranging (LiDAR) sensors have become a de-facto sensor for many robot state estimation tasks, spurring development of many LiDAR Odometry (LO) methods in recent years. While some smoothing-based LO methods have been…

Robotics · Computer Science 2025-10-14 Easton R. Potokar , Taylor Pool , Daniel McGann , Michael Kaess

We consider the problem of recovering signals from their power spectral density. This is a classical problem referred to in literature as the phase retrieval problem, and is of paramount importance in many fields of applied sciences. In…

Information Theory · Computer Science 2013-11-12 Kishore Jaganathan , Samet Oymak , Babak Hassibi

We present the gas-phase oxygen abundance (O/H) for a sample of 131 star-forming galaxies at intermediate redshifts ($0.2<z<1.0$). The sample selection, the spectroscopic observations (mainly with VLT/FORS) and associated data reduction,…

Fourier decomposition is a well established technique used in stellar pulsation. However the quality of reconstructed light curves using this method is reduced when the observed data have uneven phase coverage. We use simulated annealing…

In this paper, we study the number of measurements required to recover a sparse signal in ${\mathbb C}^M$ with $L$ non-zero coefficients from compressed samples in the presence of noise. For a number of different recovery criteria, we prove…

Information Theory · Computer Science 2007-11-05 Mehmet Akçakaya , Vahid Tarokh

Inspired by significant real-life applications, in particular, sparse phase retrieval and sparse pulsation frequency detection in Asteroseismology, we investigate a general framework for compressed sensing, where the measurements are…

Numerical Analysis · Mathematics 2017-09-04 Martin Ehler , Massimo Fornasier , Juliane Sigl

Images captured in challenging environments--such as nighttime, smoke, rainy weather, and underwater--often suffer from significant degradation, resulting in a substantial loss of visual quality. The effective restoration of these degraded…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Wenfeng Huang , Guoan Xu , Wenjing Jia , Stuart Perry , Guangwei Gao

We simulate the performance of a gravitational wave interferometer in the Dual Recycling (DR) configuration, as will be used for systems like Advanced-LIGO. Our grid-based simulation program models complex interferometric detectors with…

Astrophysics · Physics 2015-06-24 Brett Bochner

We present results of the first survey of high-redshift (<z> ~ 2.3) OVI absorption systems along parallel lines of sight toward two lensed QSOs. After a careful and well-defined search, we find ten intervening OVI systems. Within the…

Astrophysics · Physics 2009-11-13 S. Lopez , S. Ellison , S. D'Odorico , T. -S. Kim

We address the problem of recovering signals from samples taken at their rate of innovation. Our only assumption is that the sampling system is such that the parameters defining the signal can be stably determined from the samples, a…

Information Theory · Computer Science 2015-05-28 Tomer Michaeli , Yonina C. Eldar

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

We present a modified approach to laser optical-feedback cavity-enhanced absorption spectroscopy. The technique involves continuously scanning the length of a high-finesse cavity to periodically lock a diode laser to the cavity resonance,…

Optics · Physics 2024-09-04 Christopher A. Curwen , Mathieu Fradet , Ryan M. Briggs

This paper considers the problem of recovering a group sparse signal matrix $\mathbf{Y} = [\mathbf{y}_1, \cdots, \mathbf{y}_L]$ from sparsely corrupted measurements $\mathbf{M} = [\mathbf{A}_{(1)}\mathbf{y}_{1}, \cdots,…

Information Theory · Computer Science 2016-06-14 Xiaohan Wei , Qing Ling , Zhu Han

Using the statistics of pixel optical depths, we compare HI, CIV and CIII absorption in a set of six high quality z ~ 3-4 quasar absorption spectra to that in spectra drawn from two different state-of-the-art cosmological simulations that…

Astrophysics · Physics 2009-11-10 Anthony Aguirre , Joop Schaye , Lars Hernquist , Scott Kay , Volker Springel , Tom Theuns

We use high resolution Eulerian hydrodynamics simulations to study kinematic properties of the low ionization species in damped Ly-alpha systems at redshift z=3. Our adaptive mesh refinement simulations include most key ingredients relevant…

Astrophysics · Physics 2009-11-13 Alexei O. Razoumov , Michael L. Norman , Jason X. Prochaska , Arthur M. Wolfe

We present the results of the light curve model fitting technique applied to optical and near-infrared photometric data for a sample of 18 Classical Cepheids (11 fundamentals and 7 first overtones) in the Large Magellanic Cloud (LMC). We…

The paper illustrates an application of the Resampling approach [2] for the estimation of the aircraft circulation plan reliability. Resampling is an intensive computer statistical method, which can be used effectively in the case of small…

Applications · Statistics 2013-05-14 Maxim Fioshin

Accreting black holes are thought to swallow matter in the form of a disk and a hot cloud of plasma that glows brightly in X-rays, known as the corona. The X-ray emitting region is far too small to be directly imaged, but rapid variability…

High Energy Astrophysical Phenomena · Physics 2026-04-02 Bei You , Wei Yu , Adam Ingram , Barbara De Marco , Jin-Lu Qu , Zong-Hong Zhu , Andrea Santangelo , Sai-En Xu

We present a method for extracting the expected cosmological 21-cm signal from the epoch of reionization, taking into account contaminating radiations and random instrumental noise. The method is based on the maximum a-posteriori…

Astrophysics · Physics 2008-12-21 Liron Gleser , Adi Nusser , Andrew J. Benson

Probabilistic classifiers output confidence scores along with their predictions, and these confidence scores should be calibrated, i.e., they should reflect the reliability of the prediction. Confidence scores that minimize standard metrics…

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