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Journal ArticleDOI

Estimating distances from parallaxes IV: Distances to 1.33 billion stars in Gaia Data Release 2

TL;DR: In this paper, the authors used a weak distance prior that varies smoothly as a function of Galactic longitude and latitude according to a Galaxy model to infer distances to essentially all 1.33 billion stars with parallaxes published in the second Gaia data release.
Abstract: For the vast majority of stars in the second Gaia data release, reliable distances cannot be obtained by inverting the parallax. A correct inference procedure must instead be used to account for the nonlinearity of the transformation and the asymmetry of the resulting probability distribution. Here we infer distances to essentially all 1.33 billion stars with parallaxes published in the second \gaia\ data release. This is done using a weak distance prior that varies smoothly as a function of Galactic longitude and latitude according to a Galaxy model. The irreducible uncertainty in the distance estimate is characterized by the lower and upper bounds of an asymmetric confidence interval. Although more precise distances can be estimated for a subset of the stars using additional data (such as photometry), our goal is to provide purely geometric distance estimates, independent of assumptions about the physical properties of, or interstellar extinction towards, individual stars. We analyse the characteristics of the catalogue and validate it using clusters. The catalogue can be queried on the Gaia archive using ADQL at this http URL and downloaded from this http URL .
Citations
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Journal ArticleDOI
TL;DR: 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.

645 citations


Cites background from "Estimating distances from parallaxe..."

  • ...…2015; Astraatmadja & BailerJones 2016a) (hereafter papers I and II), and applied it to estimate distances for 2 million stars in the first Gaia data release (Astraatmadja & Bailer-Jones 2016b) (paper III) and 1.33 billion stars in the second Gaia data release (Bailer-Jones et al. 2018) (paper IV)....

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  • ...Our prior is built using a sophisticated model of the Galaxy that includes 3D extinction, but it will not be perfect....

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  • ...Galactic spatial distribution Figure 21 shows the projected distribution of stars in EDR3 in the Galaxy using our distance estimates....

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  • ...S R ] 9 D ec 2 02 0 vary with direction in the Galaxy (Bailer-Jones et al. 2018)....

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  • ...Here we take a probabilistic approach to estimating stellar distances that uses a prior constructed from a three-dimensional model of our Galaxy....

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Journal ArticleDOI
TL;DR: In this paper, the capabilities of the open-knowledge software instrument Modules for Experiments in Stellar Astrophysics (MESA) have been updated to improve numerical energy conservation capabilities, including during mass changes.
Abstract: We update the capabilities of the open-knowledge software instrument Modules for Experiments in Stellar Astrophysics (MESA). RSP is a new functionality in MESAstar that models the nonlinear radial stellar pulsations that characterize RR Lyrae, Cepheids, and other classes of variable stars. We significantly enhance numerical energy conservation capabilities, including during mass changes. For example, this enables calculations through the He flash that conserve energy to better than 0.001%. To improve the modeling of rotating stars in MESA, we introduce a new approach to modifying the pressure and temperature equations of stellar structure, as well as a formulation of the projection effects of gravity darkening. A new scheme for tracking convective boundaries yields reliable values of the convective core mass and allows the natural emergence of adiabatic semiconvection regions during both core hydrogen- and helium-burning phases. We quantify the parallel performance of MESA on current-generation multicore architectures and demonstrate improvements in the computational efficiency of radiative levitation. We report updates to the equation of state and nuclear reaction physics modules. We briefly discuss the current treatment of fallback in core-collapse supernova models and the thermodynamic evolution of supernova explosions. We close by discussing the new MESA Testhub software infrastructure to enhance source code development.

601 citations


Cites background from "Estimating distances from parallaxe..."

  • ...…billion stars, begins the process of converting the spectrophotometric measurements to distances, proper motions, luminosities, effective temperatures, surface gravities, and elemental compositions (Gaia Collaboration et al. 2018a; Bailer-Jones et al. 2018; Lindegren et al. 2018; Luri et al. 2018)....

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Journal ArticleDOI
TL;DR: In this article, a list of members and cluster parameters for as many clusters as possible was established, making use of Gaia data alone, and an unsupervised membership assignment code, UPMASK, was applied to the Gaia DR2 data contained within the fields of those clusters.
Abstract: Context. Open clusters are convenient probes of the structure and history of the Galactic disk. They are also fundamental to stellar evolution studies. The second Gaia data release contains precise astrometry at the submilliarcsecond level and homogeneous photometry at the mmag level, that can be used to characterise a large number of clusters over the entire sky.Aims. In this study we aim to establish a list of members and derive mean parameters, in particular distances, for as many clusters as possible, making use of Gaia data alone.Methods. We compiled a list of thousands of known or putative clusters from the literature. We then applied an unsupervised membership assignment code, UPMASK, to the Gaia DR2 data contained within the fields of those clusters.Results. We obtained a list of members and cluster parameters for 1229 clusters. As expected, the youngest clusters are seen to be tightly distributed near the Galactic plane and to trace the spiral arms of the Milky Way, while older objects are more uniformly distributed, deviate further from the plane, and tend to be located at larger Galactocentric distances. Thanks to the quality of Gaia DR2 astrometry, the fully homogeneous parameters derived in this study are the most precise to date. Furthermore, we report on the serendipitous discovery of 60 new open clusters in the fields analysed during this study.

594 citations

Journal ArticleDOI
TL;DR: In this article, the authors describe the catalogs assembled and the algorithms used to populate the revised TESS Input Catalog (TIC), based on the incorporation of the Gaia second data release.
Abstract: We describe the catalogs assembled and the algorithms used to populate the revised TESS Input Catalog (TIC), based on the incorporation of the Gaia second data release. We also describe a revised ranking system for prioritizing stars for 2-minute cadence observations, and assemble a revised Candidate Target List (CTL) using that ranking. The TIC is available on the Mikulski Archive for Space Telescopes (MAST) server, and an enhanced CTL is available through the Filtergraph data visualization portal system at the URL this http URL.

535 citations

Journal ArticleDOI

411 citations

References
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Journal ArticleDOI
TL;DR: In this article, the power of the Gaia DR2 in studying many fine structures of the Hertzsprung-Russell diagram (HRD) was highlighted, depending in particular on stellar population selections.
Abstract: We highlight the power of the Gaia DR2 in studying many fine structures of the Hertzsprung-Russell diagram (HRD). Gaia allows us to present many different HRDs, depending in particular on stellar population selections. We do not aim here for completeness in terms of types of stars or stellar evolutionary aspects. Instead, we have chosen several illustrative examples. We describe some of the selections that can be made in Gaia DR2 to highlight the main structures of the Gaia HRDs. We select both field and cluster (open and globular) stars, compare the observations with previous classifications and with stellar evolutionary tracks, and we present variations of the Gaia HRD with age, metallicity, and kinematics. Late stages of stellar evolution such as hot subdwarfs, post-AGB stars, planetary nebulae, and white dwarfs are also analysed, as well as low-mass brown dwarf objects. The Gaia HRDs are unprecedented in both precision and coverage of the various Milky Way stellar populations and stellar evolutionary phases. Many fine structures of the HRDs are presented. The clear split of the white dwarf sequence into hydrogen and helium white dwarfs is presented for the first time in an HRD. The relation between kinematics and the HRD is nicely illustrated. Two different populations in a classical kinematic selection of the halo are unambiguously identified in the HRD. Membership and mean parameters for a selected list of open clusters are provided. They allow drawing very detailed cluster sequences, highlighting fine structures, and providing extremely precise empirical isochrones that will lead to more insight in stellar physics. Gaia DR2 demonstrates the potential of combining precise astrometry and photometry for large samples for studies in stellar evolution and stellar population and opens an entire new area for HRD-based studies.

782 citations

Journal ArticleDOI
TL;DR: Gaia DR2 as mentioned in this paper is the second Gaia data release, consisting of astrometry, photometry, radial velocities, and information on astrophysical parameters and variability, for sources brighter than magnitude 21.
Abstract: We present the second Gaia data release, Gaia DR2, consisting of astrometry, photometry, radial velocities, and information on astrophysical parameters and variability, for sources brighter than magnitude 21. In addition epoch astrometry and photometry are provided for a modest sample of minor planets in the solar system. A summary of the contents of Gaia DR2 is presented, accompanied by a discussion on the differences with respect to Gaia DR1 and an overview of the main limitations which are still present in the survey. Recommendations are made on the responsible use of Gaia DR2 results. Gaia DR2 contains celestial positions and the apparent brightness in G for approximately 1.7 billion sources. For 1.3 billion of those sources, parallaxes and proper motions are in addition available. The sample of sources for which variability information is provided is expanded to 0.5 million stars. This data release contains four new elements: broad-band colour information in the form of the apparent brightness in the $G_\mathrm{BP}$ (330--680 nm) and $G_\mathrm{RP}$ (630--1050 nm) bands is available for 1.4 billion sources; median radial velocities for some 7 million sources are presented; for between 77 and 161 million sources estimates are provided of the stellar effective temperature, extinction, reddening, and radius and luminosity; and for a pre-selected list of 14000 minor planets in the solar system epoch astrometry and photometry are presented. Finally, Gaia DR2 also represents a new materialisation of the celestial reference frame in the optical, the Gaia-CRF2, which is the first optical reference frame based solely on extragalactic sources. There are notable changes in the photometric system and the catalogue source list with respect to Gaia DR1, and we stress the need to consider the two data releases as independent.

761 citations

Journal ArticleDOI
TL;DR: The second Gaia data release (DR2) contains very precise astrometric and photometric properties for more than one billion sources, astrophysical parameters for dozens of millions, radial velocities for millions, variability information for half a million of stellar sources and orbits for thousands of solar system objects as discussed by the authors.
Abstract: The second Gaia data release (DR2), contains very precise astrometric and photometric properties for more than one billion sources, astrophysical parameters for dozens of millions, radial velocities for millions, variability information for half a million of stellar sources and orbits for thousands of solar system objects. Before the Catalogue publication, these data have undergone dedicated validation processes. The goal of this paper is to describe the validation results in terms of completeness, accuracy and precision of the various Gaia DR2 data. The validation processes include a systematic analysis of the Catalogue content to detect anomalies, either individual errors or statistical properties, using statistical analysis, and comparisons to external data or to models. Although the astrometric, photometric and spectroscopic data are of unprecedented quality and quantity, it is shown that the data cannot be used without a dedicated attention to the limitations described here, in the Catalogue documentation and in accompanying papers. A particular emphasis is put on the caveats for the statistical use of the data in scientific exploitation.

653 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigate the properties and performance of various prior assumptions and examine their implications, and demonstrate that a simple prior which decreases asymptotically to zero at infinite distance has good performance, accommodates nonpositive parallaxes, and does not require a bias correction.
Abstract: Astrometric surveys such as Gaia and LSST will measure parallaxes for hundreds of millions of stars. Yet they will not measure a single distance. Rather, a distance must be estimated from a parallax. In this didactic article, I show that doing this is not trivial once the fractional parallax error is larger than about 20%, which will be the case for about 80% of stars in the Gaia catalog. Estimating distances is an inference problem in which the use of prior assumptions is unavoidable. I investigate the properties and performance of various priors and examine their implications. A supposed uninformative uniform prior in distance is shown to give very poor distance estimates (large bias and variance). Any prior with a sharp cut-off at some distance has similar problems. The choice of prior depends on the information one has available—and is willing to use—concerning, e.g., the survey and the Galaxy. I demonstrate that a simple prior which decreases asymptotically to zero at infinite distance has good performance, accommodates nonpositive parallaxes, and does not require a bias correction.

443 citations

Journal ArticleDOI
TL;DR: The main recommendation is to always treat the derivation of (astro-)physical parameters from astrometric data, in particular when parallaxes are involved, as an inference problem which should preferably be handled with a full Bayesian approach.
Abstract: The second Gaia data release (GDR2) provides precise five-parameter astrometric data (positions, proper motions and parallaxes) for an unprecedented amount of sources (more than $1.3$ billion, mostly stars). The use of this wealth of astrometric data comes with a specific challenge: how does one properly infer from these data the astrophysical parameters of interest? The main - but not only - focus of this paper is the issue of the estimation of distances from parallaxes, possibly combined with other information. We start with a critical review of the methods traditionally used to obtain distances from parallaxes and their shortcomings. Then we provide guidelines on how to use parallaxes more efficiently to estimate distances by using Bayesian methods. In particular also we show that negative parallaxes, or parallaxes with relatively larger uncertainties still contain valuable information. Finally, we provide examples that show more generally how to use astrometric data for parameter estimation, including the combination of proper motions and parallaxes and the handling of covariances in the uncertainties. The paper contains examples based on simulated Gaia data to illustrate the problems and the solutions proposed. Furthermore, the developments and methods proposed in the paper are linked to a set of tutorials included in the Gaia archive documentation that provide practical examples and a good starting point for the application of the recommendations to actual problems. In all cases the source code for the analysis methods is provided. Our main recommendation is to always treat the derivation of (astro-) physical parameters from astrometric data, in particular when parallaxes are involved, as an inference problem which should preferably be handled with a full Bayesian approach.

383 citations


"Estimating distances from parallaxe..." refers background or result in this paper

  • ...A tutorial by one of us (CBJ) describing a simple approach to this can be found in Luri et al. (2018)....

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  • ...Going from a parallax to a distance is also a non-trivial issue, as has been described in several previous works (see Luri et al. 2018 for a recent discussion)....

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  • ...The inverse parallax is known to be a biased and very noisy estimator (e.g. Bailer-Jones 2015; Luri et al. 2018) which tends to overestimates the true distance....

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