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Open AccessJournal ArticleDOI

Estimating Distances from Parallaxes. V. Geometric and Photogeometric Distances to 1.47 Billion Stars in Gaia Early Data Release 3

TLDR
In this article, a probabilistic approach to estimating stellar distances using a prior constructed from a three-dimensional model of our Galaxy is presented, which includes interstellar extinction and Gaia's variable magnitude limit.
Abstract
Stellar distances constitute a foundational pillar of astrophysics. The publication of 1.47 billion stellar parallaxes from Gaia is a major contribution to this. Yet despite Gaia's precision, the majority of these stars are so distant or faint that their fractional parallax uncertainties are large, thereby precluding a simple inversion of parallax to provide a distance. Here we take a probabilistic approach to estimating stellar distances that uses a prior constructed from a three-dimensional model of our Galaxy. This model includes interstellar extinction and Gaia's variable magnitude limit. We infer two types of distance. The first, geometric, uses the parallax together with a direction-dependent prior on distance. The second, photogeometric, additionally uses the colour and apparent magnitude of a star, by exploiting the fact that stars of a given colour have a restricted range of probable absolute magnitudes (plus extinction). Tests on simulated data and external validations show that the photogeometric estimates generally have higher accuracy and precision for stars with poor parallaxes. We provide a catalogue of 1.47 billion geometric and 1.35 billion photogeometric distances together with asymmetric uncertainty measures. Our estimates are quantiles of a posterior probability distribution, so they transform invariably and can therefore also be used directly in the distance modulus (5log10(r)-5). The catalogue may be downloaded or queried using ADQL at various sites (see this http URL) where it can also be cross-matched with the Gaia catalogue.

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Journal ArticleDOI

A Comprehensive Measurement of the Local Value of the Hubble Constant with 1 km s<sup>−1</sup> Mpc<sup>−1</sup> Uncertainty from the Hubble Space Telescope and the SH0ES Team

TL;DR: In this paper , Cepheids were measured with the same WFC3 instrument and filters (F555W, F814W and F160W) to negate zeropoint errors.
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The GALAH+ survey: Third data release

TL;DR: In this paper, the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1093/mnras/stab1242
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The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar, and APOGEE-2 Data

TL;DR: The most recent data release from the Sloan Digital Sky Surveys (SDSS-IV) is DR17 as discussed by the authors , which contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey.
Journal ArticleDOI

Measurements of the Hubble Constant: Tensions in Perspective*

TL;DR: In this article, the authors combined several recent calibrations of the Tip of the Red Giant Branch (TRGB) method with the new Gaia Early Data Release 3 (EDR3) data to provide an additional consistency check at a (lower) 5% level of accuracy.
Journal ArticleDOI

A catalogue of white dwarfs in Gaia EDR3

TL;DR: In this paper, a catalogue of white dwarf candidates selected from Gaia early data release three (EDR3) is presented, with several selection criteria in absolute magnitude, colour, and Gaia quality flags to remove objects with unreliable measurements.
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Gaia Data Release 2. Summary of the contents and survey properties

Anthony G. A. Brown, +452 more
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T. Prusti, +624 more
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Journal ArticleDOI

HEALPix -- a Framework for High Resolution Discretization, and Fast Analysis of Data Distributed on the Sphere

TL;DR: The Hierarchical Equal Area iso-Latitude Pixelization (HEALPix) as discussed by the authors is a data structure with an associated library of computational algorithms and visualization software that supports fast scientific applications executable directly on very large volumes of astronomical data and large area surveys in the form of discretized spherical maps.
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