A Gaia early DR3 mock stellar catalog: Galactic prior and selection function
Jan Rybizki, Markus Demleitner, Coryn Bailer-Jones, Piero Dal Tio, Tristan Cantat-Gaudin, Morgan Fouesneau, Yang Chen, Rene Andrae, Leo Girardi, Sanjib Sharma
We present a mock stellar catalog, matching in volume, depth and data model the content of the planned Gaia early data release 3 (Gaia EDR3). We have generated our catalog (GeDR3mock) using galaxia, a tool to sample stars from an underlying Milky Way (MW) model or from N-body data. We used an updated Besançon Galactic model together with the latest PARSEC stellar evolutionary tracks, now also including white dwarfs. We added the Magellanic clouds and realistic open clusters with internal rotation. We empirically modelled uncertainties based on Gaia DR2 (GDR2) and scaled them according to the longer baseline in Gaia EDR3. The apparent magnitudes were reddened according to a new selection of 3D extinction maps.
To help with the Gaia selection function we provide all-sky magnitude limit maps in G and BP for a few relevant GDR2 subsets together with the routines to produce these maps for user-defined subsets. We supplement the catalog with photometry and extinctions in non-Gaia bands. The catalog is available in the Virtual Observatory and can be queried just like the actual Gaia EDR3 will be. We highlight a few capabilities of the Astronomy Data Query Language (ADQL) with educative catalog queries. We use the data extracted from those queries to compare GeDR3mock to GDR2, which emphasises the importance of adding observational noise to the mock data. Since the underlying truth, e.g. stellar parameters, is know in GeDR3mock, it can be used to construct priors as well as mock data tests for parameter estimation.
All code, models and data used to produce GeDR3mock are linked and contained in galaxia_wrap, a python package, representing a fast galactic forward model, able to project MW models and N-body data into realistic Gaia observables.
We present a mock catalog of Milky Way stars, matching in volume and depth the content of the Gaia data release 2 (GDR2). We generated our catalog using Galaxia, a tool to sample stars from a Besancon Galactic model, together with a realistic 3D dust extinction map. The catalog mimicks the complete GDR2 data model and contains most of the entries in the Gaia source catalog: 5-parameter astrometry, 3-band photometry, radial velocities, stellar parameters, and associated scaled nominal uncertainty estimates. In addition, we supplemented the catalog with extinctions and photometry for non-Gaia ba…
Context. Although the Gaia catalogue on its own is a very powerful tool, it is the combination of this high-accuracy archive with other archives that will truly open up amazing possibilities for astronomical research. The advanced interoperation of archives is based on cross-matching, leaving the user with the feeling of working with one single data archive. The data retrieval should work not only across data archives but also across wavelength domains. The first step for a seamless access to the data is the computation of the cross-match between Gaia and external surveys. Aims. We describe th…
Aims: An effort has been undertaken to simulate the expected Gaia Catalogue, including the effect of observational errors. A statistical analysis of this simulated Gaia data is performed in order to better understand what can be obtained from the Gaia astrometric mission. This catalogue is used in order to investigate the potential yield in astrometric, photometric and spectroscopic information, and the extent and effect of observational errors on the true Gaia Catalogue. This article is a follow-up to Robin et. al. (2012), where the expected Gaia Catalogue content was reviewed but without the…
The second $Gaia$ Data Release (DR2) contains astrometric and photometric data for more than 1.6 billion objects with mean $Gaia$ $G$ magnitude $<$20.7, including many Young Stellar Objects (YSOs) in different evolutionary stages. In order to explore the YSO population of the Milky Way, we combined the $Gaia$ DR2 database with WISE and Planck measurements and made an all-sky probabilistic catalogue of YSOs using machine learning techniques, such as Support Vector Machines, Random Forests, or Neural Networks. Our input catalogue contains 103 million objects from the DR2xAllWISE cross-match tabl…
Gaia DR2 provides a unique all-sky catalogue of 550'737 variable stars, of which 151'761 are long-period variable (LPV) candidates with G variability amplitudes larger than 0.2 mag (5-95% quantile range). About one-fifth of the LPV candidates are Mira candidates, the majority of the rest are semi-regular variable candidates. For each source, G, BP , and RP photometric time-series are published, together with some LPV-specific attributes for the subset of 89'617 candidates with periods in G longer than 60 days. We describe this first Gaia catalogue of LPV candidates, and present various validat…
We present a cross-calibration of Hipparcos and Gaia EDR3 intended to identify astrometrically accelerating stars and to fit orbits to stars with faint, massive companions. The resulting catalog, the EDR3 edition of the Hipparcos-Gaia Catalog of Accelerations (HGCA), provides three proper motions with calibrated uncertainties on the EDR3 reference frame: the Hipparcos proper motion, the Gaia EDR3 proper motion, and the long-term proper motion given by the difference in position between Hipparcos and Gaia EDR3. Our approach is similar to that for the Gaia DR2 edition of the HGCA, but offers a f…
This paper presents a cross-calibrated catalog of Hipparcos and Gaia astrometry to enable their use in measuring changes in proper motion, i.e., accelerations in the plane of the sky. The final catalog adopts the reference frame of the second Gaia data release (DR2) and locally cross-calibrates both the scaled Hipparcos-Gaia DR2 positional differences and the Hipparcos proper motions themselves to this frame. This gives three nearly independent proper motion measurements per star, with the scaled positional difference usually being the most precise. We find that a linear combination of the two…
XP-TEAL: Gaia XP Tool for Emission and Absorption Lines II. Gaia-HELIX catalogue of H$α$ emitters in Gaia BP/RP spectra
Institut d’Estudis Espacials de Catalunya (IEEC)（加泰罗尼亚空间研究所）；Institut de Ciències del Cosmos (ICCUB), Universitat de Barcelona (UB)（巴塞罗那宇宙科学研究所，巴塞罗那大学）；Departament de Física Quàntica i Astrofísica (FQA), Universitat de Barcelona (UB)（量子物理与天体物理学系，巴塞罗那大学）
Detecting and Characterizing Companions with a Calibrated Gaia DR2, DR3, and Hipparcos Catalog (G23H)
NRC Herzberg Astronomy and Astrophysics（国家研究委员会赫茨伯格天文学与天体物理学研究所）；Department of Physics and Astronomy, University of Victoria（维多利亚大学物理与天文系）；Heising-Simons Foundation（海辛-西蒙斯基金会）；Department of Earth, Planetary, and Space Sciences, University of California, Los Angeles（加州大学洛杉矶分校地球、行星与空间科学系）；Department of Physics, University of California, Santa Barbara（加州大学圣塔芭芭拉分校物理系）；Department of Astronomy & Astrophysics, University of California, San Diego（加州大学圣地亚哥分校天文与天体物理学系）；Department of Astronomy, New Mexico State University（新墨西哥州立大学天文系）
We extend the SDSS Stripe 82 Standard Stars Catalog with post-2007 SDSS imaging data. This improved version lists averaged SDSS ugriz photometry for nearly a million stars brighter than r~22 mag. With 2-3x more measurements per star, random errors are 1.4-1.7x smaller than in the original catalog, and about 3x smaller than for individual SDSS runs. Random errors in the new catalog are ~< 0.01 mag for stars brighter than 20.0, 21.0, 21.0, 20.5, and 19.0 mag in u, g, r, i, and z-bands, respectively. We achieve this error threshold by using the Gaia Early Data Release 3 (EDR3) Gmag photometry to …
Although the Gaia catalogue on its own will be a very powerful tool, it is the combination of this highly accurate archive with other archives that will truly open up amazing possibilities for astronomical research. The advanced interoperation of archives is based on cross-matching, leaving the user with the feeling of working with one single data archive. The data retrieval should work not only across data archives, but also across wavelength domains. The first step for seamless data access is the computation of the cross-match between Gaia and external surveys. The matching of astronomical c…
Interpreting and modelling astronomical catalogues requires an understanding of the catalogues' completeness or selection function: objects of what properties had a chance to end up in the catalogue. Here we set out to empirically quantify the completeness of the overall Gaia DR3 catalogue. This task is not straightforward because Gaia is the all-sky optical survey with the highest angular resolution to date and no consistent ``ground truth'' exists to allow direct comparisons. However, well-characterised deeper imaging enables an empirical assessment of Gaia's $G$-band completeness across par…
When we perform probabilistic inferences with the Gaia Mission data, we technically require a likelihood function, or a probability of the (raw-ish) data as a function of stellar (astrometric and photometric) properties. Unfortunately, we aren't (at present) given access to the Gaia data directly; we are only given a Catalog of derived astrometric properties for the stars. How do we perform probabilistic inferences in this context? The answer - implicit in many publications - is that we should look at the Gaia Catalog as containing the parameters of a likelihood function, or a probability of t…
Canadian Institute for Theoretical Astrophysics（加拿大理论天体物理研究所）；University of Toronto（多伦多大学）
Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification. In this paper we use one-class classifiers to learn the properties of an observed catalog of clusters of galaxies from ROSAT and to pick clusters from mock simulations that resemble the observed ROSAT catalog. We show how this method can be used to study the cross-correlations o…
We have developed a general statistical procedure for analysis of 2D and 3D finite patterns, which is applied to the data from recently released Gaia-ESA catalogue DR2. The 2D analysis clearly confirms our former results on the presence of binaries in the former DR1 catalogue. Our main objective is the statistical 3D analysis of DR2. For this, it is essential that the DR2 catalogue includes parallaxes and data on the proper motion. The analysis allows us to determine for each pair of stars the probability that it is the binary star. This probability is represented by the function \b{eta}(Δ) de…
Recent works have made strong efforts to produce standardised photometry in RGB bands. For this purpose, we carefully defined the transmissivity curves of RGB bands and defined a set of standard sources using the photometric information present in Gaia EDR3. This work aims not only to significantly increase the number and accuracy of RGB standards but also to provide, for the first time, reliable uncertainty estimates using the BP and RP spectrophotometry published in Gaia DR3 instead of their integrated photometry to predict RGB photometry. Furthermore, this method allows including calibrated…
We introduce the Theoretical Astrophysical Observatory (TAO), an online virtual laboratory that houses mock observations of galaxy survey data. Such mocks have become an integral part of the modern analysis pipeline. However, building them requires an expert knowledge of galaxy modelling and simulation techniques, significant investment in software development, and access to high performance computing. These requirements make it difficult for a small research team or individual to quickly build a mock catalogue suited to their needs. To address this TAO offers access to multiple cosmological s…
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 systemat…
Astrometric positions of moving objects in the Solar System have been measured using a variety of star catalogs in the past. Previous work has shown that systematic errors in star catalogs can affect the accuracy of astrometric observations. That, in turn, can influence the resulting orbit fits for minor planets. In order to quantify these systematic errors, we compare the positions and proper motion of stellar sources in the most utilized star catalogs to the second release of the Gaia star catalog. The accuracy of Gaia astrometry allows us to unambiguously identify local biases and derive a …
TOPCAT, and its command line counterpart STILTS, are powerful tools for working with large source catalogues. ESA's Gaia mission, most recently with its second data release, is producing source catalogues of unprecedented quality for more than a billion sources. This paper presents some examples of how TOPCAT and STILTS can be used for analysis of Gaia data.
The Chandra-Gaia Catalog of Counterparts: Resolving ambiguous Gaia matches to X-ray sources in the Chandra Source Catalog using Machine Learning
Center for Astrophysics Harvard \& Smithsonian, 60 Garden St, Cambridge MA 02138, USA；Harvard John A. Paulson School of Engineering；Universidad del Rosario, School of Engineering, Science；The NSF AI Institute for Artificial Intelligence；New York University, Courant Institute, 60 5th Avenue, New York NY, USA；Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213；New College of Florida, 5800 Bayshore Road, Sarasota, FL 34243, USA；Astrophysics Laboratory, 3251 Hanover St, Palo Alto, CA 94304, USA
Effects of long-term atmospheric change were looked for in photometry employing the Gemini North and South twin Multi-Object Spectrograph (GMOS-N and GMOS-S) archival data. The whole GMOS imaging database, beginning from 2003, was compared against the all-sky Gaia object catalog, yielding ~10^6 Sloan r'-filter samples, ending in 2021. These were combined with reported sky and meteorological conditions, versus a simple model of the atmosphere plus cloud together with simulated throughputs. One exceptionally extincted episode in 2009 is seen, as is a trend (similar at both sites) of about 2 mmag…
A Gaia-linked High-purity QSO Candidate Catalog in Selected Fields with Extinction-binned Calibration and Spectrum-informed Training
National Astronomical Observatories, Chinese Academy of Sciences（中国科学院国家天文台）；University of Chinese Academy of Sciences（中国科学院大学）；Shanghai Astronomical Observatory, Chinese Academy of Sciences（中国科学院上海天文台）；National Astronomical Data Center（国家天文数据中心）
An analysis of the source position differences between VLBI-based ICRF and $Gaia$-CRF catalogues is a key step in assessing their systematic errors and determining their mutual orientation. One of the main factors that limits the accuracy of determination of the orientation parameters between two frames is the impact of outliers. To mitigate this effect, a new method is proposed based on pixelization data over the equal-area cells, followed by median filtering of the data in each cell. After this, a new data set is formed, consisting of data points near-uniformly distributed over the sphere. T…
We introduce a method for constructing end-to-end mock galaxy catalogues using a semi-analytical model of galaxy formation, applied to the halo merger trees extracted from a cosmological N-body simulation. The mocks that we construct are lightcone catalogues, in which a galaxy is placed according to the epoch at which it first enters the past lightcone of the observer, and incorporate the evolution of galaxy properties with cosmic time. We determine the position between the snapshot outputs at which a galaxy enters the observer's lightcone by interpolation. As an application, we consider the e…
