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Register a new userEstimating distances from parallaxes. V: Geometric and photogeometric distances to 1.47 billion stars in Gaia Early Data Release 3
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Authors
C. A. L. Bailer-Jones
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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 Gaias 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 Gaias 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 http://www.mpia.de/homes/calj/gedr3_distances.html) where it can also be cross-matched with the Gaia catalogue.
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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 http://gea.esac.esa.int/archive/ and downloaded from http://www.mpia.de/~calj/gdr2_distances.html .
We infer distances and their asymmetric uncertainties for two million stars using the parallaxes published in the Gaia DR1 (GDR1) catalogue. We do this with two distance priors: A minimalist, isotropic prior assuming an exponentially decreasing space density with increasing distance, and an anisotropic prior derived from the observability of stars in a Milky Way model. We validate our results by comparing our distance estimates for 105 Cepheids which have more precise, independently estimated distances. For this sample we find that the Milky Way prior performs better (the RMS of the scaled residuals is 0.40) than the exponentially decreasing space density prior (RMS is 0.57), although for distances beyond 2 kpc the Milky Way prior performs worse, with a bias in the scaled residuals of -0.36 (vs. -0.07 for the exponentially decreasing space density prior). We do not attempt to include the photometric data in GDR1 due to the lack of reliable colour information. Our distance catalogue is available at http://www.mpia.de/homes/calj/tgas distances/main.html as well as at CDS. This should only be used to give individual distances. Combining data or testing models should be done with the original parallaxes, and attention paid to correlated and systematic uncertainties.
We produce a clean and well-characterised catalogue of objects within 100,pc of the Sun from the G Early Data Release 3. We characterise the catalogue through comparisons to the full data release, external catalogues, and simulations. We carry out a first analysis of the science that is possible with this sample to demonstrate its potential and best practices for its use. The selection of objects within 100,pc from the full catalogue used selected training sets, machine-learning procedures, astrometric quantities, and solution quality indicators to determine a probability that the astrometric solution is reliable. The training set construction exploited the astrometric data, quality flags, and external photometry. For all candidates we calculated distance posterior probability densities using Bayesian procedures and mock catalogues to define priors. Any object with reliable astrometry and a non-zero probability of being within 100,pc is included in the catalogue. We have produced a catalogue of NFINAL objects that we estimate contains at least 92% of stars of stellar type M9 within 100,pc of the Sun. We estimate that 9% of the stars in this catalogue probably lie outside 100,pc, but when the distance probability function is used, a correct treatment of this contamination is possible. We produced luminosity functions with a high signal-to-noise ratio for the main-sequence stars, giants, and white dwarfs. We examined in detail the Hyades cluster, the white dwarf population, and wide-binary systems and produced candidate lists for all three samples. We detected local manifestations of several streams, superclusters, and halo objects, in which we identified 12 members of G Enceladus. We present the first direct parallaxes of five objects in multiple systems within 10,pc of the Sun.
We consider the parallaxes of sixteen cataclysmic variables and related objects that are included in the TGAS catalogue, which is part of the Gaia first data release, and compare these with previous parallax measurements. The parallax of the dwarf nova SS Cyg is consistent with the parallax determination made using the VLBI, but with only one of the analyses of the HST Fine Guidance Sensor (FGS) observations of this system. In contrast, the Gaia parallaxes of V603 Aql and RR Pic are broadly consistent, but less precise than the HST/FGS measurements. The Gaia parallaxes of IX Vel, V3885 Sgr, and AE Aqr are consistent with, but much more accurate than the Hipparcos measurements. We take the derived Gaia distances and find that absolute magnitudes of outbursting systems show a weak correlation with orbital period. For systems with measured X-ray fluxes we find that the X-ray luminosity is a clear indicator of whether the accretion disc is in the hot and ionised or cool and neutral state. We also find evidence for the X-ray emission of both low and high state discs correlating with orbital period, and hence the long-term average accretion rate. The inferred mass accretion rates for the nova-like variables and dwarf novae are compared with the critical mass accretion rate predicted by the Disk Instability Model. While we find agreement to be good for most systems there appears to be some uncertainty in the system parameters of SS Cyg. Our results illustrate how future Gaia data releases will be an extremely valuable resource in mapping the evolution of cataclysmic variables.
Ultracompact binaries with orbital periods less than a few hours will dominate the gravitational wave signal in the mHz regime. Until recently, 10 systems were expected have a predicted gravitational wave signal strong enough to be detectable by the Laser Interferometer Space Antenna (LISA), the so-called `verification binaries. System parameters, including distances, are needed to provide an accurate prediction of the expected gravitational wave strength to be measured by LISA. Using parallaxes from {sl Gaia} Data Release 2 we calculate signal-to-noise ratios (SNR) for $approx$50 verification binary candidates. We find that 11 binaries reach a SNR$geq$20, two further binaries reaching a SNR$geq$5 and three more systems are expected to have a SNR$approx$5 after four years integration with LISA. For these 16 systems we present predictions of the gravitational wave amplitude ($mathcal{A}$) and parameter uncertainties from Fisher information matrix on the amplitude ($mathcal{A}$) and inclination ($iota$).
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