M. Riello

The UKIRT Infrared Deep Sky Survey Early Data Release

This paper defines the UKIRT Infrared Deep Sky Survey (UKIDSS) Early Data Release (EDR). UKIDSS is a set of five large near-infrared surveys being undertaken with the United Kingdom Infrared Telescope Wide Field Camera (WFCAM). The programme began in 2005 May and has an expected duration of 7 yr. Each survey uses some or all of the broad-band filter complement ZY JHK. The EDR is the first public release of data to the European Southern Observatory (ESO) community. All worldwide releases occur after a delay of 18 months from the ESO release. The EDR provides a small sample data set, ∼50 deg(2) (about 1 per cent of the whole of UKIDSS), that is a lower limit to the expected quality of future survey data releases. In addition, an EDR+ data set contains all EDR data plus extra data of similar quality, but for areas not observed in all of the required filters (amounting to ∼220 deg(2)). The first large data release, DR1, will occur in mid-2006. We provide details of the observational implementation, the data reduction, the astrometric and photometric calibration and the quality control procedures. We summarize the data coverage and quality (seeing, ellipticity, photometricity, depth) for each survey and give a brief guide to accessing the images and catalogues from the WFCAM Science Archive.

The United Kingdom Infrared Telescope Infrared Deep Sky Survey First Data Release

The First Data Release (DR1) of the UKIRT Infrared Deep Sky Survey (UKIDSS) took place on 2006 July 21. UKIDSS is a set of five large near–infrared surveys, covering a complementary range of areas, depths, and Galactic latitudes. DR1 is the first large release of survey-quality data from UKIDSS and includes 320 deg of multicolour data to (Vega) K = 18, complete (depending on the survey) in three to five bands from the set ZYJHK, together with 4 deg of deep JK data to an average depth K = 21. In addition the release includes a similar quantity of data with incomplete filter coverage. In JHK, in regions of low extinction, the photometric uniformity of the calibration is better than 0.02mag. in each band. The accuracy of the calibration in ZY remains to be quantified, and the same is true of JHK in regions of high extinction. The median image FWHM across the dataset is 0.82. We describe changes since the Early Data Release in the implementation, pipeline and calibration, quality control, and archive procedures. We provide maps of the areas surveyed, and summarise the contents of each of the five surveys in terms of filters, areas, and depths. DR1 marks completion of 7 per cent of the UKIDSS 7-year goals.

Gaia Data Release 1 - The photometric data

Context. This paper presents an overview of the photometric data that are part of the first Gaia data release. Aims. The principles of the processing and the main characteristics of the Gaia photometric data are presented. Methods. The calibration strategy is outlined briefly and the main properties of the resulting photometry are presented. Results. Relations with other broadband photometric systems are provided. The overall precision for the Gaia photometry is shown to be at the milli-magnitude level and has a clear potential to improve further in future releases.

Gaia Data Release 1 - The Cepheid and RR Lyrae star pipeline and its application to the south ecliptic pole region

Context. The European Space Agency spacecraft Gaia is expected to observe about 10 000 Galactic Cepheids and over 100 000 Milky Way RR Lyrae stars (a large fraction of which will be new discoveries), during the five-year nominal lifetime spent scanning the whole sky to a faint limit of G = 20.7 mag, sampling their light variation on average about 70 times. Aims. We present an overview of the Specific Objects Study (SOS) pipeline developed within the Coordination Unit 7 (CU7) of the Data Processing and Analysis Consortium (DPAC), the coordination unit charged with the processing and analysis of variable sources observed by Gaia , to validate and fully characterise Cepheids and RR Lyrae stars observed by the spacecraft. The algorithms developed to classify and extract information such as the pulsation period, mode of pulsation, mean magnitude, peak-to-peak amplitude of the light variation, subclassification in type, multiplicity, secondary periodicities, and light curve Fourier decomposition parameters, as well as physical parameters such as mass, metallicity, reddening, and age (for classical Cepheids) are briefly described. Methods. The full chain of the CU7 pipeline was run on the time series photometry collected by Gaia during 28 days of ecliptic pole scanning law (EPSL) and over a year of nominal scanning law (NSL), starting from the general Variability Detection, general Characterization, proceeding through the global Classification and ending with the detailed checks and typecasting of the SOS for Cepheids and RR Lyrae stars (SOS Cep&RRL). We describe in more detail how the SOS Cep&RRL pipeline was specifically tailored to analyse Gaia ’s G -band photometric time series with a south ecliptic pole (SEP) footprint, which covers an external region of the Large Magellanic Cloud (LMC), and to produce results for confirmed RR Lyrae stars and Cepheids to be published in Gaia Data Release 1 ( Gaia DR1). Results. G -band time series photometry and characterisation by the SOS Cep&RRL pipeline (mean magnitude and pulsation characteristics) are published in Gaia DR1 for a total sample of 3194 variable stars (599 Cepheids and 2595 RR Lyrae stars), of which 386 (43 Cepheids and 343 RR Lyrae stars) are new discoveries by Gaia . All 3194 stars are distributed over an area extending 38 degrees on either side from a point offset from the centre of the LMC by about 3 degrees to the north and 4 degrees to the east. The vast majority are located within the LMC. The published sample also includes a few bright RR Lyrae stars that trace the outer halo of the Milky Way in front of the LMC.

Gaia Data Release 1 - Principles of the photometric calibration of the G band

Context. Gaia is an ESA cornerstone mission launched on 19 December 2013 aiming to obtain the most complete and precise 3D map of our Galaxy by observing more than one billion sources. This paper is part of a series of documents explaining the data processing and its results for Gaia Data Release 1, focussing on the G band photometry. Aims. This paper describes the calibration model of the Gaia photometric passband for Gaia Data Release 1. Methods. The overall principle of splitting the process into internal and external calibrations is outlined. In the internal calibration, a self-consistent photometric system is generated. Then, the external calibration provides the link to the absolute photometric flux scales. Results. The Gaia photometric calibration pipeline explained here was applied to the first data release with good results. Details are given of the various calibration elements including the mathematical formulation of the models used and of the extraction and preparation of the required input parameters (e.g. colour terms). The external calibration in this first release provides the absolute zero point and photometric transformations from the Gaia G passband to other common photometric systems. Conclusions. This paper describes the photometric calibration implemented for the first Gaia data release and the instrumental effects taken into account. For this first release no aperture losses, radiation damage, and other second-order effects have not yet been implemented in the calibration.

Gaia Data Release 2. Photometric content and validation

This work presents results from the European Space Agency (ESA) space mission Gaia. Gaia data are being processed by the Gaia Data Processing and Analysis Consortium (DPAC). Funding for the DPAC is provided by national institutions, in particular the institutions participating in the Gaia MultiLateral Agreement (MLA). The Gaia mission website is https://www.cosmos.esa.int/gaia. The Gaia Archive website is http://gea.esac.esa.int/archive/. This work has been supported by the United Kingdom Rutherford Appleton Laboratory, the United Kingdom Science and Technology Facilities Council (STFC) through grant ST/L006553/1, and the United Kingdom Space Agency (UKSA) through grant ST/N000641/1. This work was supported by the MINECO (Spanish Ministry of Economy) through grant ESP2016-80079-C2-1-R (MINECO/FEDER, UE) and ESP2014-55996-C2-1-R (MINECO/FEDER, UE) and MDM-2014-0369 of ICCUB (Unidad de Excelencia “Maria de Maeztu”). This work was supported by the Italian funding agencies Agenzia Spaziale Italiana (ASI) through grants I/037/08/0, I/058/10/0, 2014-025- R.0, and 2014- 025-R.1.2015 to INAF and contracts I/008/10/0 and 2013/030/I.0 to ALTEC S.p.A and Istituto Nazionale di Astrofisica (INAF). This research has made use of the APASS database, located at the AAVSO web site. Funding for APASS has been provided by the Robert Martin Ayers Sciences Fund. We thank A. Vallenari for supplying us with spectra for the validation of the external flux calibration and passband determination

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

Context. The Gaia Data Release 2 (DR2) contains more than half a million sources that are identified as variable stars. Aims: 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, δ Scuti and SX Phoenicis stars, and short-timescale variables. In this release we aim to provide useful but not necessarily complete samples of candidates. Methods: The processed Gaia data consist of the G, GBP, and GRP 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 were various visualisation tools to interpret the data. Results: The DR2 variability release contains 228 904 RR Lyrae stars, 11 438 Cepheids, 151 761 LPVs, 147 535 stars with rotation modulation, 8882 δ Scuti and SX Phoenicis stars, and 3018 short-timescale variables. These results are distributed over a classification and various Specific Object Studies tables in the Gaia archive, along with the three-band time series and associated statistics for the underlying 550 737 unique sources. We estimate that about half of them are newly identified variables. The variability type completeness varies strongly as a function of sky position as a result of the non-uniform sky coverage and intermediate calibration level of these data. The probabilistic and automated nature of this work implies certain completeness and contamination rates that are quantified so that users can anticipate their effects. Thismeans that even well-known variable sources can be missed or misidentified in the published data. Conclusions: 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.

Gaia Data Release 2. Processing of the photometric data

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.

Data Management at Gaia Data Processing Centers

Gaia is a European Space Agency mission that will deal with large volumes of data that have to be processed at, and transferred between, different data processing centers (DPCs) in Europe. Managing the data and the associated databases will be a significant challenge. This paper presents the different data management configurations that have been evaluated at the Gaia DPCs in order to cope with the requirements of Gaia’s complex data handling.

Gaia Data Release 2. Short-timescale variability processing and analysis

Aims: We describe the methods used and the analysis performed in the frame of the Gaia data processing activities to produce the Gaia Data Release 2 (DR2) sample candidates with short-timescale variability together with associated parameters. Methods: The Gaia DR2 sample of candidates with short-timescale variability results from the investigation of the first 22 months of Gaia G per-CCD, GBP, and GRP photometry for a subsample of sources at the Gaia faint end (G 16.5-20 mag). For this first short-timescale variability search exploiting Gaia data, we limited ourselves to the case of suspected rapid periodic variability. Our study combines fast-variability detection through variogram analysis, a high-frequency search by means of least-squares periodograms, and an 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, improvement, and validation of this selection criterion also benefited from supplementary ground-based photometric monitoring of a few tens of preliminary candidates with short-timescale variability, performed at the Flemish Mercator telescope in La Palma (Canary Islands, Spain) between August and November 2017. Results: As part of Gaia DR2, we publish a list of 3018 candidates with short-timescale variability, spread throughout the sky, with a false-positive rate of 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 variability 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.