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Showing papers by "D. Garabato published in 2018"


Journal ArticleDOI
TL;DR: In this article, the power of the Gaia DR2 in studying many fine structures of the Hertzsprung-Russell diagram (HRD) was highlighted, depending in particular on stellar population selections.
Abstract: We highlight the power of the Gaia DR2 in studying many fine structures of the Hertzsprung-Russell diagram (HRD). Gaia allows us to present many different HRDs, depending in particular on stellar population selections. We do not aim here for completeness in terms of types of stars or stellar evolutionary aspects. Instead, we have chosen several illustrative examples. We describe some of the selections that can be made in Gaia DR2 to highlight the main structures of the Gaia HRDs. We select both field and cluster (open and globular) stars, compare the observations with previous classifications and with stellar evolutionary tracks, and we present variations of the Gaia HRD with age, metallicity, and kinematics. Late stages of stellar evolution such as hot subdwarfs, post-AGB stars, planetary nebulae, and white dwarfs are also analysed, as well as low-mass brown dwarf objects. The Gaia HRDs are unprecedented in both precision and coverage of the various Milky Way stellar populations and stellar evolutionary phases. Many fine structures of the HRDs are presented. The clear split of the white dwarf sequence into hydrogen and helium white dwarfs is presented for the first time in an HRD. The relation between kinematics and the HRD is nicely illustrated. Two different populations in a classical kinematic selection of the halo are unambiguously identified in the HRD. Membership and mean parameters for a selected list of open clusters are provided. They allow drawing very detailed cluster sequences, highlighting fine structures, and providing extremely precise empirical isochrones that will lead to more insight in stellar physics. Gaia DR2 demonstrates the potential of combining precise astrometry and photometry for large samples for studies in stellar evolution and stellar population and opens an entire new area for HRD-based studies.

782 citations


Journal ArticleDOI
Federica Spoto1, Federica Spoto2, Paolo Tanga2, Francois Mignard2  +498 moreInstitutions (86)
TL;DR: In this paper, the authors describe the processing of the Gaia DR2 data, and describe the criteria used to select the sample published in Gaia DR 2, and explore the data set to assess its quality.
Abstract: Context. The Gaia spacecraft of the European Space Agency (ESA) has been securing observations of solar system objects (SSOs) since the beginning of its operations. Data Release 2 (DR2) contains the observations of a selected sample of 14,099 SSOs. These asteroids have been already identified and have been numbered by the Minor Planet Center repository. Positions are provided for each Gaia observation at CCD level. As additional information, complementary to astrometry, the apparent brightness of SSOs in the unfiltered G band is also provided for selected observations.Aims. We explain the processing of SSO data, and describe the criteria we used to select the sample published in Gaia DR2. We then explore the data set to assess its quality.Methods. To exploit the main data product for the solar system in Gaia DR2, which is the epoch astrometry of asteroids, it is necessary to take into account the unusual properties of the uncertainty, as the position information is nearly one-dimensional. When this aspect is handled appropriately, an orbit fit can be obtained with post-fit residuals that are overall consistent with the a-priori error model that was used to define individual values of the astrometric uncertainty. The role of both random and systematic errors is described. The distribution of residuals allowed us to identify possible contaminants in the data set (such as stars). Photometry in the G band was compared to computed values from reference asteroid shapes and to the flux registered at the corresponding epochs by the red and blue photometers (RP and BP).Results. The overall astrometric performance is close to the expectations, with an optimal range of brightness G ~ 12 − 17. In this range, the typical transit-level accuracy is well below 1 mas. For fainter asteroids, the growing photon noise deteriorates the performance. Asteroids brighter than G ~ 12 are affected by a lower performance of the processing of their signals. The dramatic improvement brought by Gaia DR2 astrometry of SSOs is demonstrated by comparisons to the archive data and by preliminary tests on the detection of subtle non-gravitational effects.

584 citations


Journal ArticleDOI
Amina Helmi1, F. van Leeuwen2, Paul J. McMillan3, Davide Massari1  +481 moreInstitutions (82)
TL;DR: In this paper, the second data release of the Gaia mission and its power for constraining many different aspects of the dynamics of the satellites of the Milky Way is demonstrated. But the accuracy of the errors, statistical and systematic, are relatively well understood.
Abstract: Context. Aims: The goal of this paper is to demonstrate the outstanding quality of the second data release of the Gaia mission and its power for constraining many different aspects of the dynamics of the satellites of the Milky Way. We focus here on determining the proper motions of 75 Galactic globular clusters, nine dwarf spheroidal galaxies, one ultra-faint system, and the Large and Small Magellanic Clouds. Methods: Using data extracted from the Gaia archive, we derived the proper motions and parallaxes for these systems, as well as their uncertainties. We demonstrate that the errors, statistical and systematic, are relatively well understood. We integrated the orbits of these objects in three different Galactic potentials, and characterised their properties. We present the derived proper motions, space velocities, and characteristic orbital parameters in various tables to facilitate their use by the astronomical community. Results: Our limited and straightforward analyses have allowed us for example to (i) determine absolute and very precise proper motions for globular clusters; (ii) detect clear rotation signatures in the proper motions of at least five globular clusters; (iii) show that the satellites of the Milky Way are all on high-inclination orbits, but that they do not share a single plane of motion; (iv) derive a lower limit for the mass of the Milky Way of 9.1-2.6+6.2 × 1011 M⊙ based on the assumption that the Leo I dwarf spheroidal is bound; (v) derive a rotation curve for the Large Magellanic Cloud based solely on proper motions that is competitive with line-of-sight velocity curves, now using many orders of magnitude more sources; and (vi) unveil the dynamical effect of the bar on the motions of stars in the Large Magellanic Cloud. Conclusions: All these results highlight the incredible power of the Gaia astrometric mission, and in particular of its second data release.

581 citations


Journal ArticleDOI
17 Sep 2018
TL;DR: This work proposes a method, based on Self-Organized Maps, which combine numerical and categorical features, to ease communication network data analysis, and has explored the possibility of using different sources of data.
Abstract: In these days, organizations rely on the availability and security of their communication networks to perform daily operations As a result, network data must be analyzed in order to provide an adequate level of security and to detect anomalies or malfunctions in the systems Due to the increase of devices connected to these networks, the complexity to analyze data related to its communications also grows We propose a method, based on Self-Organized Maps, which combine numerical and categorical features, to ease communication network data analysis Also, we have explored the possibility of using different sources of data

4 citations


Journal ArticleDOI
03 May 2018-Sensors
TL;DR: A parallel, scalable, and optimized design for self-organized maps (SOM) is proposed in order to analyze massive data gathered by the spectrophotometric sensor of the European Space Agency (ESA) Gaia spacecraft, although it could be extrapolated to other domains.
Abstract: Analyzing huge amounts of data becomes essential in the era of Big Data, where databases are populated with hundreds of Gigabytes that must be processed to extract knowledge. Hence, classical algorithms must be adapted towards distributed computing methodologies that leverage the underlying computational power of these platforms. Here, a parallel, scalable, and optimized design for self-organized maps (SOM) is proposed in order to analyze massive data gathered by the spectrophotometric sensor of the European Space Agency (ESA) Gaia spacecraft, although it could be extrapolated to other domains. The performance comparison between the sequential implementation and the distributed ones based on Apache Hadoop and Apache Spark is an important part of the work, as well as the detailed analysis of the proposed optimizations. Finally, a domain-specific visualization tool to explore astronomical SOMs is presented.

4 citations



Amina Helmi, F.E. van Leeuwen, P. J. Mc Millan, Davide Massari  +442 moreInstitutions (43)
01 Apr 2018
TL;DR: In this article, the authors present lists of possible members of each of the objects (75 globular clusters, 9 dwarf spheroidal galaxies, the Bootes I UFD, the LMC and SMC).
Abstract: The files contains lists of possible members of each of the objects (75 globular clusters, 9 dwarf spheroidal galaxies, the Bootes I UFD, the LMC and SMC). The stars in these lists have been selected and used to determine the astrometric parameters of the corresponding objects following either the procedures described in Sec. 2.1 (for the clusters and dwarfs) or in Sec. 2.2 (for the LMC and SMC). The first column is the "source_id" as given by Gaia, the ra and declination of the star in degrees, and its G-band magnitude (known as "photgmean_mag" in the Gaia archive). (2 data files).

1 citations