F. Gran

Variable stars in the VVV globular clusters. I. 2MASS-GC 02 and Terzan 10

The VISTA Variables in the V?a L?ctea (VVV) ESO Public Survey is opening a new window to study inner Galactic globular clusters (GCs) using their variable stars. These GCs have been neglected in the past due to the difficulties caused by the presence of elevated extinction and high field stellar densities in their lines of sight. However, the discovery and study of any present variables in these clusters, especially RR Lyrae stars, can help to greatly improve the accuracy of their physical parameters. It can also help to shed some light on the questions raised by the intriguing Oosterhoff dichotomy in the Galactic GC system. In a series of papers we plan to explore variable stars in the GCs falling inside the field of the VVV survey. In this first paper, we search for and study the variables present in two highly reddened, moderately metal-poor, faint, inner Galactic GCs: 2MASS-GC 02 and Terzan 10. We report the discovery of sizable populations of RR Lyrae stars in both GCs. We use near-infrared period?luminosity relations to determine the color excess of each RR Lyrae star, from which we obtain both accurate distances to the GCs and the ratios of the selective-to-total extinction in their directions. We find the extinction toward both clusters to be elevated, non-standard, and highly differential. We also find both clusters to be closer to the Galactic center than previously thought, with Terzan 10 being on the far side of the Galactic bulge. Finally, we discuss their Oosterhoff properties, and conclude that both clusters stand out from the dichotomy followed by most Galactic GCs.

The VVV Templates Project Towards an automated classification of VVV light-curves - I. Building a database of stellar variability in the near-infrared

Context. The Vista Variables in the Via Lactea (VVV) ESO Public Survey is a variability survey of the Milky Way bulge and an adjacent section of the disk carried out from 2010 on ESO Visible and Infrared Survey Telescope for Astronomy (VISTA). The VVV survey will eventually deliver a deep near-IR atlas with photometry and positions in five passbands (ZY JHKS) and a catalogue of 1−10 million variable point sources – mostly unknown – that require classifications. Aims. The main goal of the VVV Templates Project, which we introduce in this work, is to develop and test the machine-learning algorithms for the automated classification of the VVV light-curves. As VVV is the first massive, multi-epoch survey of stellar variability in the near-IR, the template light-curves that are required for training the classification algorithms are not available. In the first paper of the series we describe the construction of this comprehensive database of infrared stellar variability. Methods. First, we performed a systematic search in the literature and public data archives; second, we coordinated a worldwide observational campaign; and third, we exploited the VVV variability database itself on (optically) well-known stars to gather high-quality infrared light-curves of several hundreds of variable stars. Results. We have now collected a significant (and still increasing) number of infrared template light-curves. This database will be used as a training-set for the machine-learning algorithms that will automatically classify the light-curves produced by VVV. The results of such an automated classification will be covered in forthcoming papers of the series.Context. The Vista Variables in the Via Lactea (VVV) ESO Public Survey is a variability survey of the Milky Way bulge and an adjacent section of the disk carried out from 2010 on ESO Visible and Infrared Survey Telescope for Astronomy (VISTA). The VVV survey will eventually deliver a deep near-IR atlas with photometry and positions in five passbands (ZYJHKS) and a catalogue of 1−10 million variable point sources – mostly unknown – that require classifications. Aims. The main goal of the VVV Templates Project, which we introduce in this work, is to develop and test the machine-learning algorithms for the automated classification of the VVV light-curves. As VVV is the first massive, multi-epoch survey of stellar variability in the near-IR, the template light-curves that are required for training the classification algorithms are not available. In the first paper of the series we describe the construction of this comprehensive database of infrared stellar variability. Methods. First, we performed a systematic search in the literature and public data archives; second, we coordinated a worldwide observational campaign; and third, we exploited the VVV variability database itself on (optically) well-known stars to gather high-quality infrared light-curves of several hundreds of variable stars. Results. We have now collected a significant (and still increasing) number of infrared template light-curves. This database will be used as a training-set for the machine-learning algorithms that will automatically classify the light-curves produced by VVV. The results of such an automated classification will be covered in forthcoming papers of the series.

Bulge RR Lyrae stars in the VVV tile b201

1 Instituto de Astrofisica, Pontificia Universidad Catolica de Chile, Vicuna Mackenna 4860, Casilla 306, Santiago, Chile e-mail: fgran@astro.puc.cl 2 Millennium Institute of Astrophysics (MAS), Santiago, Chile 3 Departamento de Ciencias Fisicas, Universidad Andres Bello, Republica 220, Santiago, Chile 4 Vatican Observatory, 00120 Vatican City State, Italy 5 Universidade Federal de Sergipe, Departamento de Fisica, Av. Marechal Rondon s/n, 49100-000 Sao Cristovao, SE, Brazil 6 Jordell Bank Centre for Astrophysics, Alan Turing Building, Manchester, M13 9PL, UK

DISCOVERY OF RR LYRAE STARS IN THE NUCLEAR BULGE OF THE MILKY WAY

Galactic nuclei, such as that of the Milky Way, are extreme regions with high stellar densities, and in most cases, the hosts of a supermassive black hole. One of the scenarios proposed for the formation of the Galactic nucleus is merging of primordial globular clusters. An implication of this model is that this region should host stars that are characteristically found in old Milky Way globular clusters. RR Lyrae stars are primary distance indicators, well known representatives of old and metal-poor stellar populations, and therefore are regularly found in globular clusters. Here we report the discovery of a dozen RR Lyrae type ab stars in the vicinity of the Galactic center, i.e., in the so-called nuclear stellar bulge of the Milky Way. This discovery provides the first direct observational evidence that the Galactic nuclear stellar bulge contains ancient stars (>10 Gyr old). Based on this we conclude that merging globular clusters likely contributed to the build-up of the high stellar density in the nuclear stellar bulge of the Milky Way.

A machine learned classifier for RR Lyrae in the VVV survey

Variable stars of RR Lyrae type are a prime tool with which to obtain distances to old stellar populations in the Milky Way. One of the main aims of the Vista Variables in the Via Lactea (VVV) near-infrared survey is to use them to map the structure of the Galactic Bulge. Owing to the large number of expected sources, this requires an automated mechanism for selecting RR Lyrae, and particularly those of the more easily recognized type ab (i.e., fundamental-mode pulsators), from the 10 6 −10 7 variables expected in the VVV survey area. In this work we describe a supervised machine-learned classifier constructed for assigning a score to a K s -band VVV light curve that indicates its likelihood of being ab -type RR Lyrae. We describe the key steps in the construction of the classifier, which were the choice of features, training set, selection of aperture, and family of classifiers. We find that the AdaBoost family of classifiers give consistently the best performance for our problem, and obtain a classifier based on the AdaBoost algorithm that achieves a harmonic mean between false positives and false negatives of ≈7% for typical VVV light-curve sets. This performance is estimated using cross-validation and through the comparison to two independent datasets that were classified by human experts.

FSR 1716: A New Milky Way Globular Cluster Confirmed Using VVV RR Lyrae Stars

We use deep multi-epoch near-IR images of the VISTA Variables in the Via Lactea (VVV) Survey to search for RR Lyrae stars toward the Southern Galactic plane. Here, we report the discovery of a group of RR Lyrae stars close together in VVV tile d025. Inspection of the VVV images and PSF photometry reveals that most of these stars are likely to belong to a globular cluster that matches the position of the previously known star cluster FSR 1716. The stellar density map of the field yields a >100? detection for this candidate globular cluster that is centered at equatorial coordinates R.A. J2000 = 16:10:30.0, decl. J2000 = ?53:44:56 and galactic coordinates l = 329.77812, b = ?1.59227. The color–magnitude diagram of this object reveals a well-populated red giant branch, with a prominent red clump at K s = 13.35 ± 0.05, and J ? K s = 1.30 ± 0.05. We present the cluster RR Lyrae positions, magnitudes, colors, periods, and amplitudes. The presence of RR Lyrae indicates an old globular cluster, with an age >10 Gyr. We classify this object as an Oosterhoff type I globular cluster, based on the mean period of its RR Lyrae type ab,

Proper motions in the VVV Survey: Results for more than 15 million stars across NGC 6544

\langle P\rangle =0.540

The Orbit of the New Milky Way Globular Cluster FSR1716 = VVV-GC05

days, and argue that this is a relatively metal-poor cluster with [Fe/H] = ?1.5 ± 0.4 dex. The mean extinction and reddening for this cluster are

The VVV Survey RR Lyrae Population in the Galactic Center Region

{A}_{{K}_{s}}=0.38\pm 0.02

Pulsating stars in ω Centauri. Near-IR properties and period-luminosity relations

and E(J ? K s ) = 0.72 ± 0.02 mag, respectively, as measured from the RR Lyrae colors and the near-IR color–magnitude diagram. We also measure the cluster distance using the RR Lyrae type ab stars. The cluster mean distance modulus is (m ? M)0 = 14.38 ± 0.03 mag, implying a distance D = 7.5 ± 0.2 kpc and a Galactocentric distance R G = 4.3 kpc.