Galactic Archeology with RAVE and TGAS

AbstractThe 5th RAVE data release is based on 520,781 spectra (R ≈ 7500 in the CaT region at 8410 - 8795Å) of 457,588 unique stars. RAVE DR5 provides radial velocities, stellar parameters and individual abundances for up to seven elements and distances found using isochrones for a considerable subset of these objects. In particular, RAVE DR5 has 255,922 stellar observations that also have parallaxes and proper motions from the Tycho-Gaia astrometric solution (TGAS) in Gaia DR1. The combination of RAVE and TGAS thus provides the currently largest overlap of spectroscopic and space-based astrometric data and thus can serve as a formidable preview of what Gaia is going to deliver in coming data releases. Basic properties of the RAVE+TGAS survey and its derived data products are presented as well as first applications w.r.t wave-like patterns in the disk structure. An outlook to the 6th RAVE data release is given.

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Astrometric surveys in the Gaia era

Proceedings of the International Astronomical Union ◽

10.1017/s1743921317005889 ◽

2017 ◽

Vol 12 (S330) ◽

pp. 49-58

Author(s):

Norbert Zacharias

Keyword(s):

Reference Frame ◽

Wide Field ◽

Proper Motions ◽

Gaia Dr1 ◽

Data Release ◽

Optical Reference ◽

Trigonometric Parallaxes ◽

Astrometric Data ◽

Interim Period

AbstractThe Gaia first data release (DR1) already provides an almost error free optical reference frame on the milli-arcsecond (mas) level allowing significantly better calibration of ground-based astrometric data than ever before. Gaia DR1 provides positions, proper motions and trigonometric parallaxes for just over 2 million stars in the Tycho-2 catalog. For over 1.1 billion additional stars DR1 gives positions. Proper motions for these, mainly fainter stars (G ≥ 11.5) are currently provided by several new projects which combine earlier epoch ground-based observations with Gaia DR1 positions. These data are very helpful in the interim period but will become obsolete with the second Gaia data release (DR2) expected in April 2018. The era of traditional, ground-based, wide-field astrometry with the goal to provide accurate reference stars has come to an end. Future ground-based astrometry will fill in some gaps (very bright stars, observations needed at many or specific epochs) and mainly will go fainter than the Gaia limit, like the PanSTARRS and the upcoming LSST surveys.

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Gaia Data Release 2

Astronomy and Astrophysics ◽

10.1051/0004-6361/201833051 ◽

2018 ◽

Vol 616 ◽

pp. A1 ◽

Cited By ~ 3220

Author(s):

◽

A. G. A. Brown ◽

A. Vallenari ◽

T. Prusti ◽

J. H. J. de Bruijne ◽

...

Keyword(s):

Solar System ◽

Reference Frame ◽

Broad Band ◽

Radial Velocities ◽

Minor Planets ◽

Major Advance ◽

Photometric System ◽

Proper Motions ◽

Apparent Brightness ◽

Data Release

Context. 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. Aims. 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. Methods. The raw data collected with the Gaia instruments during the first 22 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into this second data release, which represents a major advance with respect to Gaia DR1 in terms of completeness, performance, and richness of the data products. 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 GBP (330–680 nm) and GRP (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 14 000 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. Conclusions. Gaia DR2 represents a major achievement for the Gaia mission, delivering on the long standing promise to provide parallaxes and proper motions for over 1 billion stars, and representing a first step in the availability of complementary radial velocity and source astrophysical information for a sample of stars in the Gaia survey which covers a very substantial fraction of the volume of our galaxy.

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Gaia Data Release 2

Astronomy and Astrophysics ◽

10.1051/0004-6361/201833273 ◽

2019 ◽

Vol 622 ◽

pp. A205 ◽

Cited By ~ 66

Author(s):

D. Katz ◽

P. Sartoretti ◽

M. Cropper ◽

P. Panuzzo ◽

G. M. Seabroke ◽

...

Keyword(s):

Radial Velocity ◽

Effective Temperature ◽

Radial Velocities ◽

Positive Trend ◽

Full Dataset ◽

Data Release ◽

Astrometric Data

Context. For Gaia DR2, 280 million spectra collected by the Radial Velocity Spectrometer instrument on board Gaia were processed, and median radial velocities were derived for 9.8 million sources brighter than GRVS = 12 mag. Aims. This paper describes the validation and properties of the median radial velocities published in Gaia DR2. Methods. Quality tests and filters were applied to select those of the 9.8 million radial velocities that have the quality to be published in Gaia DR2. The accuracy of the selected sample was assessed with respect to ground-based catalogues. Its precision was estimated using both ground-based catalogues and the distribution of the Gaia radial velocity uncertainties. Results. Gaia DR2 contains median radial velocities for 7 224 631 stars, with Teff in the range [3550, 6900] K, which successfully passed the quality tests. The published median radial velocities provide a full-sky coverage and are complete with respect to the astrometric data to within 77.2% (for G ≤ 12.5 mag). The median radial velocity residuals with respect to the ground-based surveys vary from one catalogue to another, but do not exceed a few 100 m s−1. In addition, the Gaia radial velocities show a positive trend as a function of magnitude, which starts around GRVS ~ 9 mag and reaches about + 500 m s−1 at GRVS = 11.75 mag. The origin of the trend is under investigation, with the aim to correct for it in Gaia DR3. The overall precision, estimated from the median of the Gaia radial velocity uncertainties, is 1.05 km s−1. The radial velocity precision is a function of many parameters, in particular, the magnitude and effective temperature. For bright stars, GRVS ∈ [4, 8] mag, the precision, estimated using the full dataset, is in the range 220–350 m s−1, which is about three to five times more precise than the pre-launch specification of 1 km s−1. At the faint end, GRVS = 11.75 mag, the precisions for Teff = 5000 and 6500 K are 1.4 and 3.7 km s−1, respectively.

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Gaia Data Release 2

Astronomy and Astrophysics ◽

10.1051/0004-6361/201832964 ◽

2018 ◽

Vol 616 ◽

pp. A9 ◽

Cited By ~ 350

Author(s):

X. Luri ◽

A. G. A. Brown ◽

L. M. Sarro ◽

F. Arenou ◽

C. A. L. Bailer-Jones ◽

...

Keyword(s):

Statistical Treatment ◽

Physical Parameters ◽

Proper Motions ◽

Inference Problem ◽

Starting Point ◽

Data Release ◽

Other Information ◽

Good Starting Point ◽

Astrometric Data ◽

Specific Challenge

Context. The second Gaia data release (Gaia DR2) provides precise five-parameter astrometric data (positions, proper motions, and parallaxes) for an unprecedented number of sources (more than 1.3 billion, mostly stars). This new wealth of data will enable the undertaking of statistical analysis of many astrophysical problems that were previously infeasible for lack of reliable astrometry, and in particular because of the lack of parallaxes. However, the use of this wealth of astrometric data comes with a specific challenge: how can the astrophysical parameters of interest be properly inferred from these data? Aims. The main focus of this paper, but not the only focus, 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 we also show that negative parallaxes, or parallaxes with relatively large 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. Methods. 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. Results. 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. Conclusions. Gaia will provide fundamental data for many fields of astronomy. Further data releases will provide more data, and more precise data. Nevertheless, to fully use the potential it will always be necessary to pay careful attention to the statistical treatment of parallaxes and proper motions. The purpose of this paper is to help astronomers find the correct approach.

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The relation between velocity dispersions and chemical abundances in RAVE giants

Proceedings of the International Astronomical Union ◽

10.1017/s1743921317005944 ◽

2017 ◽

Vol 12 (S330) ◽

pp. 259-260

Author(s):

Rodolfo Smiljanic ◽

Rafael Silva de Souza

Keyword(s):

Stellar Population ◽

Velocity Dispersion ◽

Bayesian Framework ◽

Radial Velocities ◽

Proper Motions ◽

Chemical Abundances ◽

Gaia Dr1 ◽

Velocity Dispersions ◽

Kinematic Properties ◽

Robust Result

AbstractWe developed a Bayesian framework to determine in a robust way the relation between velocity dispersions and chemical abundances in a sample of stars. Our modelling takes into account the uncertainties in the chemical and kinematic properties. We make use of RAVE DR5 radial velocities and abundances together with Gaia DR1 proper motions and parallaxes (when possible, otherwise UCAC4 data is used). We found that, in general, the velocity dispersions increase with decreasing [Fe/H] and increasing [Mg/Fe]. A possible decrease in velocity dispersion for stars with high [Mg/Fe] is a property of a negligible fraction of stars and hardly a robust result. At low [Fe/H] and high [Mg/Fe] the sample is incomplete, affected by biases, and likely not representative of the underlying stellar population.

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Magellanic Clouds Proper Motion and Rotation with Gaia DR1

Proceedings of the International Astronomical Union ◽

10.1017/s1743921317005580 ◽

2017 ◽

Vol 12 (S330) ◽

pp. 249-250

Author(s):

J. Sahlmann ◽

R. van der Marel

Keyword(s):

Proper Motion ◽

Stellar Population ◽

External Validation ◽

Magellanic Clouds ◽

Data Sets ◽

Proper Motions ◽

Gaia Dr1 ◽

Data Release ◽

Motion Measurements ◽

Similar Accuracy

AbstractWe used the Gaia data release 1 to study the proper motion fields of the Large and Small Magellanic Clouds (LMC, SMC) on the basis of the Tycho-Gaia Astrometric Solution (van der Marel & Sahlmann 2016). The Gaia LMC and SMC proper motions have similar accuracy and agree to within the uncertainties with existing HST proper motion measurements. Since Gaia probes the young stellar population and uses different methods with different systematics, this provides an external validation of both data sets and their underlying approaches.

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Catalogue reduction techniques

International Astronomical Union Colloquium ◽

10.1017/s0252921100074340 ◽

1978 ◽

Vol 48 ◽

pp. 389-390 ◽

Cited By ~ 1

Author(s):

Chr. de Vegt

Keyword(s):

Adjustment Process ◽

Proper Motions ◽

Measuring Process ◽

Aerial Photogrammetry ◽

Reduction Techniques ◽

Observational Technique ◽

The Common ◽

Astrometric Data

AbstractReduction techniques as applied to astrometric data material tend to split up traditionally into at least two different classes according to the observational technique used, namely transit circle observations and photographic observations. Although it is not realized fully in practice at present, the application of a blockadjustment technique for all kind of catalogue reductions is suggested. The term blockadjustment shall denote in this context the common adjustment of the principal unknowns which are the positions, proper motions and certain reduction parameters modelling the systematic properties of the observational process. Especially for old epoch catalogue data we frequently meet the situation that no independent detailed information on the telescope properties and other instrumental parameters, describing for example the measuring process, is available from special calibration observations or measurements; therefore the adjustment process should be highly self-calibrating, that means: all necessary information has to be extracted from the catalogue data themselves. Successful applications of this concept have been made already in the field of aerial photogrammetry.

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