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Gaia Data Release 2: Summary of the variability processing & analysis results

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 Added by Berry Holl
 Publication date 2018
  fields Physics
and research's language is English




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The Gaia Data Release 2 (DR2): we summarise the processing and results of the identification of variable source candidates of RR Lyrae stars, Cepheids, long period variables (LPVs), rotation modulation (BY Dra-type) stars, delta Scuti & SX Phoenicis stars, and short-timescale variables. In this release we aim to provide useful but not necessarily complete samples of candidates. The processed Gaia data consist of the G, BP, and RP photometry during the first 22 months of operations as well as positions and parallaxes. Various methods from classical statistics, data mining and time series analysis were applied and tailored to the specific properties of Gaia data, as well as various visualisation tools. The DR2 variability release contains: 228904 RR Lyrae stars, 11438 Cepheids, 151761 LPVs, 147535 stars with rotation modulation, 8882 delta Scuti & SX Phoenicis stars, and 3018 short-timescale variables. These results are distributed over a classification and various Specific Object Studies (SOS) tables in the Gaia archive, along with the three-band time series and associated statistics for the underlying 550737 unique sources. We estimate that about half of them are newly identified variables. The variability type completeness varies strongly as function of sky position due to the non-uniform sky coverage and intermediate calibration level of this data. The probabilistic and automated nature of this work implies certain completeness and contamination rates which are quantified so that users can anticipate their effects. This means that even well-known variable sources can be missed or misidentified in the published data. The DR2 variability release only represents a small subset of the processed data. Future releases will include more variable sources and data products; however, DR2 shows the (already) very high quality of the data and great promise for variability studies.



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The Gaia Data Release 2 contains the 1st release of radial velocities complementing the kinematic data of a sample of about 7 million relatively bright, late-type stars. Aims: This paper provides a detailed description of the Gaia spectroscopic data processing pipeline, and of the approach adopted to derive the radial velocities presented in DR2. Methods: The pipeline must perform four main tasks: (i) clean and reduce the spectra observed with the Radial Velocity Spectrometer (RVS); (ii) calibrate the RVS instrument, including wavelength, straylight, line-spread function, bias non-uniformity, and photometric zeropoint; (iii) extract the radial velocities; and (iv) verify the accuracy and precision of the results. The radial velocity of a star is obtained through a fit of the RVS spectrum relative to an appropriate synthetic template spectrum. An additional task of the spectroscopic pipeline was to provide 1st-order estimates of the stellar atmospheric parameters required to select such template spectra. We describe the pipeline features and present the detailed calibration algorithms and software solutions we used to produce the radial velocities published in DR2. Results: The spectroscopic processing pipeline produced median radial velocities for Gaia stars with narrow-band near-IR magnitude Grvs < 12 (i.e. brighter than V~13). Stars identified as double-lined spectroscopic binaries were removed from the pipeline, while variable stars, single-lined, and non-detected double-lined spectroscopic binaries were treated as single stars. The scatter in radial velocity among different observations of a same star, also published in DR2, provides information about radial velocity variability. For the hottest (Teff > 7000 K) and coolest (Teff < 3500 K) stars, the accuracy and precision of the stellar parameter estimates are not sufficient to allow selection of appropriate templates. [Abridged]
124 - M. Roelens , L. Eyer , N. Mowlavi 2018
The Gaia DR2 sample of short-timescale variable candidates results from the investigation of the first 22 months of Gaia photometry for a subsample of sources at the Gaia faint end. For this exercise, we limited ourselves to the case of suspected rapid periodic variability. Our study combines fast-variability detection through variogram analysis, high-frequency search by means of least-squares periodograms, and empirical selection based on the investigation of specific sources seen through the Gaia eyes (e.g. known variables or visually identified objects with peculiar features in their light curves). The progressive definition and validation of this selection criterion also benefited from supplementary ground-based photometric monitoring of a few preliminary candidates, performed at the Flemish Mercator telescope (Canary Islands, Spain) between August and November 2017. We publish a list of 3,018 short-timescale variable candidates, spread throughout the sky, with a false-positive rate up to 10-20% in the Magellanic Clouds, and a more significant but justifiable contamination from longer-period variables between 19% and 50%, depending on the area of the sky. Although its completeness is limited to about 0.05%, this first sample of Gaia short-timescale variables recovers some very interesting known short-period variables, such as post-common envelope binaries or cataclysmic variables, and brings to light some fascinating, newly discovered variable sources. In the perspective of future Gaia data releases, several improvements of the short-timescale variability processing are considered, by enhancing the existing variogram and period-search algorithms or by classifying the identified candidates. Nonetheless, the encouraging outcome of our Gaia DR2 analysis demonstrates the power of this mission for such fast-variability studies, and opens great perspectives for this domain of astrophysics.
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.
The second Gaia data release is based on 22 months of mission data with an average of 0.9 billion individual CCD observations per day. A data volume of this size and granularity requires a robust and reliable but still flexible system to achieve the demanding accuracy and precision constraints that Gaia is capable of delivering. The internal Gaia photometric system was initialised using an iterative process that is solely based on Gaia data. A set of calibrations was derived for the entire Gaia DR2 baseline and then used to produce the final mean source photometry. The photometric catalogue contains 2.5 billion sources comprised of three different grades depending on the availability of colour information and the procedure used to calibrate them: 1.5 billion gold, 144 million silver, and 0.9 billion bronze. These figures reflect the results of the photometric processing; the content of the data release will be different due to the validation and data quality filters applied during the catalogue preparation. The photometric processing pipeline, PhotPipe, implements all the processing and calibration workflows in terms of Map/Reduce jobs based on the Hadoop platform. This is the first example of a processing system for a large astrophysical survey project to make use of these technologies. The improvements in the generation of the integrated G-band fluxes, in the attitude modelling, in the cross-matching, and and in the identification of spurious detections led to a much cleaner input stream for the photometric processing. This, combined with the improvements in the definition of the internal photometric system and calibration flow, produced high-quality photometry. Hadoop proved to be an excellent platform choice for the implementation of PhotPipe in terms of overall performance, scalability, downtime, and manpower required for operations and maintenance.
Gaia DR2 provides a unique all-sky catalogue of 550737 variable stars, of which 151761 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 89617 candidates with periods in G longer than 60 days. We describe this first Gaia catalogue of LPV candidates, and present various validation checks. Various samples of LPVs were used to validate the catalogue: a sample of well-studied very bright LPVs with light curves from the AAVSO that are partly contemporaneous with Gaia light curves, a sample of Gaia LPV candidates with good parallaxes, the ASAS_SN catalogue of LPVs, and the OGLE catalogues of LPVs towards the Magellanic Clouds and the Galactic bulge. The analyses of these samples show a good agreement between Gaia DR2 and literature periods. The same is globally true for bolometric corrections of M-type stars. The main contaminant of our DR2 catalogue comes from young stellar objects (YSOs) in the solar vicinity (within ~1 kpc), although their number in the whole catalogue is only at the percent level. A cautionary note is provided about parallax-dependent LPV attributes published in the catalogue. This first Gaia catalogue of LPVs approximately doubles the number of known LPVs with amplitudes larger than 0.2 mag, despite the conservative candidate selection criteria that prioritise low contamination over high completeness, and despite the limited DR2 time coverage compared to the long periods characteristic of LPVs. It also contains a small set of YSO candidates, which offers the serendipitous opportunity to study these objects at an early stage of the Gaia data releases.
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