Data Processing And Analysis Consortium Research Articles

Multiple Stellar Populations of Globular Clusters from Homogeneous Ca–CN–CH–NH Photometry. VII. Metal-poor Populations in 47 Tucanae (NGC 104)* * Based on observations made with the Cerro Tololo Inter-American Observatory (CTIO) 1 m telescope, which is operated by the SMARTS consortium. † †This work presents results from the European Space Agency space mission Gaia. Gaia data are being processed by the

We present new large field-of-view (∼1°×1°) Ca-CN photometry of the prototypical metal-rich globular cluster 47 Tucanae (NGC 104). Our results are the following. (1) The populational number ratios of the red giant branch (RGB) and red horizontal branch (RHB) are in excellent agreement: n(CN-w):n(CN-s) = 30:70 (±1–2), where the CN-w and CN-s stand for the CN-weak and CN-strong populations, respectively. Both the CN-s RGB and RHB populations are more centrally concentrated than those of CN-w populations are. (2) Our photometric metallicities of individual RGB stars in each population can be well described by bimodal distributions with two metallicity peaks, [Fe/H] ∼−0.72 and −0.92 dex, where the metal-poor components occupy ∼13% of the total RGB stars. The metal-poor populations are more significantly centrally concentrated than the metal-rich populations, showing a similar result that we found in M3. (3) The RGB bump V magnitudes of individual populations indicate that there is no difference in the helium abundance between the two metal-poor populations, while the helium enhancement of ΔY ∼0.02–0.03 is required between the the two metal-rich populations. (4) The RHB morphology of 47 Tuc appears to support our idea of the bimodal metallicity distribution of the cluster. We suggest that 47 Tuc could be another example of merger remnants of two globular clusters, similar to M3 and M22.

A Galaxy Up Close [Space Astronomy

IT WAS AN early Christmas for astronomers all over the world when the Gaia Data Processing and Analysis Consortium (DPAC) released a new batch of data from the European Space Agency's astrometry mission called Gaia on 3 December 2020.

Gaia Data Release 2

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.

The Gaia mission status

AbstractGaia is an ESA cornerstone mission conducting a full sky survey over its 5 year operational period. Gaia performs astrometric, photometric and spectroscopic measurements. The data processing is entrusted to scientists and engineers who have formed the Gaia Data Processing and Analysis Consortium (DPAC). The photometric science alerts started in 2014. The first intermediate data release (Gaia DR1) took place 14 September 2016 and it has been extensively used by the community. Gaia DR2 is scheduled for April 2018. Gaia is expected to be able to continue observations roughly for another 5 years after the nominal phase. The procedure to grant funding for the extension period has been initiated. In case funding is granted, the total operational time of Gaia may be 10 years.

TheGaiamission

Gaia is a cornerstone mission in the science programme of the European Space Agency (ESA). The spacecraft construction was approved in 2006, following a study in which the original interferometric concept was changed to a direct-imaging approach. Both the spacecraft and the payload were built by European industry. The involvement of the scientific community focusses on data processing for which the international Gaia Data Processing and Analysis Consortium (DPAC) was selected in 2007. Gaia was launched on 19 December 2013 and arrived at its operating point, the second Lagrange point of the Sun-Earth-Moon system, a few weeks later. The commissioning of the spacecraft and payload was completed on 19 July 2014. The nominal five-year mission started with four weeks of special, ecliptic-pole scanning and subsequently transferred into full-sky scanning mode. We recall the scientific goals of Gaia and give a description of the as-built spacecraft that is currently (mid-2016) being operated to achieve these goals. We pay special attention to the payload module, the performance of which is closely related to the scientific performance of the mission. We provide a summary of the commissioning activities and findings, followed by a description of the routine operational mode. We summarise scientific performance estimates on the basis of in-orbit operations. Several intermediate Gaia data releases are planned and the data can be retrieved from the Gaia Archive, which is available through the Gaia home page at http://www.cosmos.esa.int/gaia.

GaiaData Release 1

We present an overview of the Specific Objects Study (SOS) pipeline developed within the Coordination Unit 7 (CU7) of the Gaia 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. We describe how the SOS for Cepheids and RR Lyrae stars (SOS Cep&RRL) 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). G-band time-series photometry and characterization by the SOS Cep&RRL pipeline (mean magnitude and pulsation characteristics) are published in Gaia Data Release 1 (Gaia DR1) for a total sample of 3,194 variable stars, 599 Cepheids and 2,595 RR Lyrae stars, of which 386 (43 Cepheids and 343 RR Lyrae stars) are new discoveries by Gaia. All 3,194 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, but not all, 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: switching “ON” the transient discovery machine

The Gaia Photometric Science Alerts (GSA) group is the Gaia Data Processing and Analysis Consortium (DPAC) unit responsible for releasing alerts on Gaia transient candidates from a daily flow of initially reduced data. In preparation for obtaining the rates for different transient families with Gaia , one of the main goals of GSA is to reliably identify and characterize the candidates. In this article, we describe the simulations used to understand and predict possible selection effects and the techniques used to identify the nature of the transient alerts provided by Gaia.

The Gaia Object Generator (GOG)

Gaia, a cornerstone ESA mission, will produce a three-dimensional map of our Galaxy. It was launched in December 2013, and it is expected to provide an important improvement in our understanding of the structure, composition and evolution of the Galaxy. During its five years of data collection, Gaia is expected to transmit to Earth some 150 terabytes of raw data, producing a catalogue of some 109 individual objects. After on-ground processing the full catalogue is expected to be in the range of one to two petabytes of data. Preparation for the explotation of this huge amount of data is essential, and work is being undertaken to model the expected output of Gaia in order to predict the content of the Gaia catalogue and to facilitate the production of tools required to effectively analyse the data. Therefore, the Gaia Data Processing and Analysis Consortium (DPAC) has developed a set of simulators, including a simulator called the Gaia Object Generator (GOG), which simulates the end of mission and the epoch transit catalogues, including observational errors. In 2014, CU2 has delivered a GOG end of mission catalogue, containing the potential single star observable population (with G < 20 mag) using the Gaia Universe Model, showing the effect of the observational errors. The GOG catalogue is actively used inside CU9, which is responsible for providing access to the Gaia data to the scientific community through the Gaia archive. GOG has a direct impact in the Gaia real catalogue production, as the simulated Gaia data will be used to detect false-positives and a biased data set to validate that problems can been found. Moreover, GOG simulations will be used also to test the software which will maintain and preserve all the versions of the catalogue, and to become familiar with working with such a large and rich dataset.

The Variability Processing and Analysis of the Gaia mission

We present the variability processing and analysis that is foreseen for the Gaia mission within Coordination Unit 7 (CU7) of the Gaia Data Processing and Analysis Consortium (DPAC). A top level description of the tasks is given.

An approach to the analysis of SDSS spectroscopic outliers based on self-organizing maps

Aims. A new method is applied to the segmentation, and further analysis of the outliers resulting from the classification of astronomical objects in large databases is discussed. The method is being used in the framework of the Gaia satellite DPAC (Data Processing and Analysis Consortium) activities to prepare automated software tools that will be used to derive basic astrophysical information that is to be included in Gaia final archive. Methods. Our algorithm has been tested by means of simulated Gaia spectrophotometry, which is based on SDSS observations and theoretical spectral libraries covering a wide sample of astronomical objects. Self-Organizing Maps (SOM) networks are used to organize the information in clusters of objects, as homogeneous as possible, according to their spectral energy distributions (SED), and to project them onto a 2-D grid where the data structure can be visualized. Results. We demonstrate the usefulness of the method by analyzing the spectra that were rejected by the SDSS spectroscopic classification pipeline and thus classified as "UNKNOWN". Firstly, our method can help to distinguish between astrophysical objects and instrumental artifacts. Additionally, the application of our algorithm to SDSS objects of unknown nature has allowed us to identify classes of objects of similar astrophysical nature. In addition, the method allows for the potential discovery of hundreds of novel objects, such as white dwarfs and quasars. Therefore, the proposed method is shown to be very promising for data exploration and knowledge discovery in very large astronomical databases, such as the upcoming Gaia mission.

Chemical tagging with Gaia-ESO Survey and Gaia-RVS data

AbstractWe present a new method devoted to chemical tagging for Galactic Archeology. In the context of the Gaia-ESO Survey (GES) and the Gaia Data Processing and Analysis Consortium (DPAC), we aim at preparing the Gaia-Radial Velocity Spectrograph analysis, which will provide ~ 2×106 spectra covering the IR CaII triplet domain (R ~ 11 500), with sufficient SNR to perform chemical tagging. Our method will be integrated in the Gaia DPAC Apsis pipeline (CU8, Astrophysical Parameters) and we test it with GES GIRAFFE spectra (MEDUSA mode, HR10 &amp; HR21) deriving abundances of MgI in 168 stars.

Australian Participation in the Gaia Follow-up Network for Solar System Objects

AbstractThe Gaia satellite, planned for launch by the European Space Agency (ESA) in 2013, is the next-generation astrometry mission following Hipparcos. Gaia’s primary science goal is to determine the kinematics, chemical structure, and evolution of the Milky Way Galaxy. In addition to this core science goal, the Gaia space mission is expected to discover thousands of Solar System objects. Because of orbital constraints, Gaia will only have a limited opportunity for astrometric follow-up of these discoveries. In 2010, the Gaia Data Processing and Analysis Consortium (DPAC) initiated a program to identify ground-based optical telescopes for a Gaia follow-up network for Solar System Objects to perform the following critical tasks: confirmation of discovery, identification of body, object tracking to constrain orbits. To date, this network comprises 37 observing sites (representing 53 instruments). The Zadko Telescope, located in Western Australia, was highlighted as an important network node because of its southern location, longitude, and automated scheduling system. We describe the first follow-up tests using the fast moving Potentially Hazardous Asteroid 2005 YU55 as the target.

Science performance of Gaia, ESA’s space-astrometry mission

Gaia is the next astrometry mission of the European Space Agency (ESA), following up on the success of the Hipparcos mission. With a focal plane containing 106 CCD detectors, Gaia will survey the entire sky and repeatedly observe the brightest 1,000 million objects, down to 20th magnitude, during its 5-year lifetime. Gaia's science data comprises absolute astrometry, broad-band photometry, and low-resolution spectro-photometry. Spectroscopic data with a resolving power of 11,500 will be obtained for the brightest 150 million sources, down to 17th magnitude. The thermo-mechanical stability of the spacecraft, combined with the selection of the L2 Lissajous point of the Sun-Earth/Moon system for operations, allows stellar parallaxes to be measured with standard errors less than 10 micro-arcsecond (muas) for stars brighter than 12th magnitude, 25 muas for stars at 15th magnitude, and 300 muas at magnitude 20. Photometric standard errors are in the milli-magnitude regime. The spectroscopic data allows the measurement of radial velocities with errors of 15 km/s at magnitude 17. Gaia's primary science goal is to unravel the kinematical, dynamical, and chemical structure and evolution of the Milky Way. In addition, Gaia's data will touch many other areas of science, e.g., stellar physics, solar-system bodies, fundamental physics, and exo-planets. The Gaia spacecraft is currently in the qualification and production phase. With a launch in 2013, the final catalogue is expected in 2021. The science community in Europe, organised in the Data Processing and Analysis Consortium (DPAC), is responsible for the processing of the data.

The representation of asteroid shapes: A test for the inversion of Gaia photometry

It is common practice nowadays to derive spins and 3D shapes of asteroids from the inversion of photometric light curves. However, this method requires, in general, a good number of photometric points and dedicated observing sessions. On the other hand, the photometric observations carried out by the Gaia mission will be sparse and their number relatively small.For this reason, a multi-parametric shape described by a large number of elementary facets cannot probably be derived from Gaia data alone. Therefore, the Data Processing and Analysis Consortium (DPAC), implemented a simpler solution as an unattended data reduction pipeline, which relies on three axial ellipsoids for the shape representation.However, overall accuracy of such triaxial shape solutions has to be assessed. How adequate is an ellipsoidal approximation to represent the overall properties of an irregular body? Which error is made on the volume in comparison to a more accurate model with irregular shape?To answer these questions, we have implemented numerical procedures for comparing ellipsoids to more complex and irregular shapes, and we performed a full simulation of the photometric signal from these objects, using both shape representations. Implementing the same software algorithm that will be used for the analysis of Gaia asteroid photometry, rotation period, spin axis orientation and ellipsoidal shape were derived from simulated observations of selected Main Belt asteroids assuming a geometric scattering model (work is in progress for more complex scattering models).Finally, these simulated Gaia results were compared to check the relevance of the ellipsoidal solution in comparison to multi-parametric shapes. We found that the ellipsoids by photometry inversion are closely similar to the best-fitting ellipsoids of the simulated complex shapes and that the error on the asteroid volume (relative to a complex shape) is generally low, usually around 10%.

Gaia spectroscopy: processing, performances and scientific returns

During the five years of the mission, the Gaia spectrograph, the Radial Velocity Spectrometer (RVS) will repeatedly survey the celestial sphere down to magnitude V ~ 17-18. This talk presents: (i) the system which is currently developed within the Gaia Data Processing and Analysis Consortium (DPAC) to reduce and calibrate the spectra and to derive the radial and rotational velocities, (ii) the RVS expected performances and (iii) scientific returns.

Global Sphere Reconstruction in the Astrometric Verification Unit

The Gaia space satellite will perform absolute astrometry, aiming at the definition of a global astrometric reference frame at visual wavelengths. Within this reference system, it will be very difficult to identify possible errors in the measurements or in the data reduction process that brings about the definition of the final catalogue. The Gaia Data Processing and Analysis Consortium (DPAC) has established an Astrometric Verification Unit (AVU) to verify crucial steps in the baseline data processing chain and report on any significant difference. This process is essential in order to guarantee a high quality catalogue to the larger scientific community. We describe here the global sphere reconstruction (GSR) component of AVU hosted by the Italian data processing centre at Torino (DPCT).

Global astrometric sphere reconstruction in Gaia: challenges and first results of the Verification Unit

AbstractGaia will estimate the astrometric and physical data of approximately one billion objects. The core of this process, the global sphere reconstruction, is represented by the reduction of a subset of these objects, which will constitute the largest and most precise catalog of absolute astrometry in the history of Astronomy, and will put General Relativity to test by estimating the PPN parameter γ with unprecedented accuracy. As the Hipparcos mission showed, and as it is natural for all kind of absolute measurements, possible errors in the data reduction can hardly be identified at the end of the processing, and can lead to systematic errors in all the works which will use these results. In order to avoid such kind of problems, a Verification Unit was established by the Gaia Data Processing and Analysis Consortium (DPAC). One of its jobs is to implement and perform an independent global sphere reconstruction, parallel to the baseline one, to compare the two results, and to report any significant difference.

Gaia Data Flow System (GDFS) Project: the UK's contribution to Gaia data processing

AbstractGaia is an ESA cornerstone mission which will observe some billion stars in the galaxy enabling micro-arcsec astrometric catalogues to be constructed. In addition Gaia will produce high quality photometric and spectroscopic catalogues.The data processing tasks are large and complex. A European consortium has been formed - the Gaia Data Processing and Analysis Consortium (DPAC). This paper describes the form of the UK Gaia Data Flow System Project contribution to the DPAC.