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Related papers: Empirical Uncertainty Estimators for Astrometry fr…

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Published analyses of very long baseline interferometry (VLBI) data for the sources included in the third International Celestial Reference Frame (ICRF3) catalog have revealed object-specific, excess astrometric variability and…

Astrophysics of Galaxies · Physics 2024-11-27 Valeri V. Makarov , Phil Cigan , David Gordon , Megan C. Johnson , Christopher DiLullo , Sébastien Lambert

In this paper, progress in improving the coordinates uncertainty of extragalactic radio sources derived from astrometric and geodetic VLBI observations is investigated. For this purpose, 30 catalogs of radio source positions computed in…

Instrumentation and Methods for Astrophysics · Physics 2025-12-05 Zinovy Malkin

In recent years, arrays of radio antennas operating in the MHz regime have shown great potential as detectors in astroparticle physics. In particular, they fulfill an important role in the indirect detection of ultra-high energy cosmic…

Instrumentation and Methods for Astrophysics · Physics 2023-08-17 Max Büsken , Tomáš Fodran , Tim Huege

Accurate alignment of the radio and optical celestial reference frames requires detailed understanding of physical factors that may cause offsets between the positions of the same object measured in different spectral bands. Opacity in…

Astrophysics · Physics 2008-07-21 Y. Y. Kovalev , A. P. Lobanov , A. B. Pushkarev , J. A. Zensus

A new list of physical characteristics of 3914 astrometric radio sources, including all 717 ICRF-Ext.2 sources, observed during IVS and NRAO VCS sessions have been compiled. The list includes source type, redshift and visual magnitude (if…

Cosmology and Nongalactic Astrophysics · Physics 2016-09-06 Zinovy Malkin , Oleg Titov

In this second part of our two-part paper, we provide a detailed, frequentist framework for propagating uncertainties within our multivariate linear least squares model. This permits us to quantify the impact of uncertainties in…

Applications · Statistics 2019-08-09 Pranay Seshadri , Andrew Duncan , Duncan Simpson , George Thorne , Geoffrey Parks

The Cosmic Radio Dipole is of fundamental interest to cosmology. Recent studies revealed open questions about the nature of the observed Cosmic Radio Dipole. We use simulated source count maps to test a linear and a quadratic estimator for…

Cosmology and Nongalactic Astrophysics · Physics 2021-12-07 Thilo M. Siewert , Matthias Schmidt-Rubart , Dominik J. Schwarz

State-of-the-art lidar place recognition models exhibit unreliable performance when tested on environments different from their training dataset, which limits their use in complex and evolving environments. To address this issue, we…

Computer Vision and Pattern Recognition · Computer Science 2023-07-13 Keita Mason , Joshua Knights , Milad Ramezani , Peyman Moghadam , Dimity Miller

Uncertainty quantification is a key part of astronomy and physics; scientific researchers attempt to model both statistical and systematic uncertainties in their data as best as possible, often using a Bayesian framework. Decisions might…

Instrumentation and Methods for Astrophysics · Physics 2022-07-29 Peter Hatfield

The International Celestial Reference Frame (ICRF, Ma et al. 1998) is currently the best realization of a quasi-inertial reference system. It is based on more than 10 years of cumulated geodetic and astrometric VLBI observations of compact…

Astrophysics · Physics 2007-05-23 S. B. Lambert , S. Bouquillon , C. Le Poncin-Lafitte , C. Barache , J. Souchay

USNO-B is an all-sky catalog that presents positions, proper motions, magnitudes in various optical passbands, and star/galaxy estimators for 1,042,618,261 objects derived from 3,643,201,733 separate observations. The data were obtained…

Uncertainty quantification is a critical missing component in radio interferometric imaging that will only become increasingly important as the big-data era of radio interferometry emerges. Since radio interferometric imaging requires…

Instrumentation and Methods for Astrophysics · Physics 2018-09-12 Xiaohao Cai , Marcelo Pereyra , Jason D. McEwen

Understanding sources of uncertainty is fundamental to trustworthy three-dimensional scene modeling. While recent advances in neural radiance fields (NeRFs) achieve impressive accuracy in scene reconstruction and novel view synthesis, the…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Ruxiao Duan , Alex Wong

Image-based environment perception is an important component especially for driver assistance systems or autonomous driving. In this scope, modern neuronal networks are used to identify multiple objects as well as the according position and…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Fabian Küppers

Precise astrometric and photometric measurements of celestial point sources are fundamental to modern astronomy. These measurements, used to determine object positions, motions, and fluxes, are based on observational models that have…

Instrumentation and Methods for Astrophysics · Physics 2025-12-05 Sebastián Espinosa , Rene A. Mendez , Jorge F. Silva , Marcos Orchard

Correlations between planetary and stellar properties, particularly age, can provide insight on planetary formation and evolution processes. However, the underlying source of such trends can be unclear, and measurement uncertainties and…

Earth and Planetary Astrophysics · Physics 2022-03-30 Emily D. Safsten , Rebekah I. Dawson

Distribution shift is an important concern in deep image classification, produced either by corruption of the source images, or a complete change, with the solution involving domain adaptation. While the primary goal is to improve accuracy…

Machine Learning · Statistics 2021-10-19 Tiago Salvador , Vikram Voleti , Alexander Iannantuono , Adam Oberman

In most star formation history (SFH) measurements, the reported uncertainties are those due to effects whose sizes can be readily measured: Poisson noise, adopted distance and extinction, and binning choices in the solution itself. However,…

Instrumentation and Methods for Astrophysics · Physics 2015-06-04 Andrew E. Dolphin

Estimating how uncertain an AI system is in its predictions is important to improve the safety of such systems. Uncertainty in predictive can result from uncertainty in model parameters, irreducible data uncertainty and uncertainty due to…

Machine Learning · Statistics 2018-12-03 Andrey Malinin , Mark Gales

The determination of chemical abundances from stellar spectra is considered a mature field of astrophysics. Digital spectra of stars are recorded and processed with standard techniques, much like samples in the biological sciences.…

Astrophysics · Physics 2007-05-23 C. Allende Prieto