Gaia Data Release 2

Abstract

Context. 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. Aims. We aim to describe the input data, the treatment of blue photometer/red photometer (BP/RP) low-resolution spectra required to produce the integrated GBP and GRP fluxes, the process used to establish the internal Gaia photometric system, and finally, the generation of the mean source photometry from the calibrated epoch data for Gaia DR2. Methods. 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. Results. 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.

GaiaData Release 1

“…The typical uncertainties quoted on the mean value of G range from a milli-magnitude or better at the bright end (G 13), to about 0.03 mag at the survey limit. The details of the photometric data set, including the data processing and validation of the results is described in van Leeuwen et al (2016), Carrasco et al (2016), Riello et al (2016), Evans et al (2016). 3.…”

“…We stress that the above description of the data processing for Gaia DR1 is mainly illustrative and not intended as a complete description of all the simplifications that were introduced to enable a timely first Gaia data release. For details on the actual processing for Gaia DR1 refer to Fabricius et al (2016) (pre-processing and source list creation), van Leeuwen et al (2016), Carrasco et al (2016), Riello et al (2016) (photometric processing), Eyer et al (2016) (variable star processing), and Lindegren et al (2016) (astrometric processing). In particular the latter paper contains an extensive description of the known problems introduced by the preliminary astrometric processing.…”

Characterizing K2 Candidate Planetary Systems Orbiting Low-mass Stars. IV. Updated Properties for 86 Cool Dwarfs Observed during Campaigns 1–17

“…This paper is focused on the characterization of the second set of stars observed by our program: 172 candidate cool dwarfs identified as possible planet host stars based on data acquired during K2 campaigns 1-17. We characterize these stars using a combination of archival photometry, new spectroscopic observations obtained by our team, and recently released astrometric data from Gaia DR2 (Gaia Collaboration et al 2018b,a;Cropper et al 2018;Evans et al 2018;Hambly et al 2018;Luri et al 2018;Mignard et al 2018;Riello et al 2018;Sartoretti et al 2018;Soubiran et al 2018). In Section 2, we describe our target sample.…”

A Search for Transiting Planets in the Globular Cluster M4 with K2: Candidates and Occurrence Limits

“…The stellar radii and masses were determined from the PARSEC stellar evolution models (Marigo et al 2017), obtained through the CMD v3.2 web interface 2 , this time making direct use of the Gaia DR2 G magnitudes and using the bolometric corrections for the Gaia band- Color-magnitude diagram for objects in our analysis with a cluster membership probability >99%. The photometric data are taken from Gaia DR2 (Gaia Collaboration et al 2018; Riello et al 2018). The horizontal dashed line shows our magnitude cut for objects considered in our occurrence rate calculation, with objects below the line being included.…”

“…Note-All of these stars are proper motion cluster members (Wallace 2018). a The identifier by which the object is known in this work, the same as in Wallace et al d Gaia G magnitude from Gaia DR2 (Riello et al 2018).…”