Gaia Eclipsing Binary and Multiple Systems. A study of detectability and classification of eclipsing binaries with Gaia

In the new era of large-scale astronomical surveys, automated methods of analysis and classification of bulk data are a fundamental tool for fast and efficient production of deliverables. This becomes ever more imminent as we enter the Gaia era. We investigate the potential detectability of eclipsing binaries with Gaia using a data set of all Kepler eclipsing binaries sampled with Gaia cadence and folded with the Kepler period. The performance of fitting methods is evaluated with comparison to real Kepler data parameters and a classification scheme is proposed for the potentially detectable sources based on the geometry of the light curve fits. The polynomial chain (polyfit) and two-Gaussian models are used for light curve fitting of the data set. Classification is performed with a combination of the t-SNE (t-distrubuted Stochastic Neighbor Embedding) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithms. We find that approximately 68% of Kepler Eclipsing Binary sources are potentially detectable by Gaia when folded with the Kepler period and propose a classification scheme of the detectable sources based on the morphological type indicative of the light curve, with subclasses that reflect the properties of the fitted model (presence and visibility of eclipses, their width, depth, etc.).Comment: 9 pages, 18 figures, accepted for publication in Astronomy & Astrophysic

Position estimation for a mobile robot using monocular vision and odometry

We describe a localisation system for a robot moving in a known environment . Unlike the currently used methods for industrial robots, our approach does not require any beacons to be installed : the system uses odometry to estimate the vehicle position continuously, and corrects this estimation when necessary by identifying some objects of the environment through vision . These objects, used as landmarks, were previously recorded in a data base . The different parts of the system are presented particularly the way the uncertainty on odometry is updated and how prior knowledge (position estimation and data base) is employed to facilitate landmark identification. 7 cm on xy and I deg on the heading is the typical precision obtained in term of localisation .Nous présentons un système de localisation pour un robot mobile évoluant dans un environnement connu. La méthode, contrairement à celles actuellement utilisées dans l'industrie, ne nécessite pas l'équipement du site en balises : la position du robot est estimée à chaque instant par odométrie, et recalée périodiquement en repérant, à l'aide d'une caméra mobile montée sur le véhicule, des objets de l'environnement jouant le rôle d'amer. Ces objets sont répertoriés dans une base de données constituée au préalable. Les différentes composantes du système sont présentées : nous montrons en particulier comment l'incertitude sur la position du robot évolue avec les erreurs d'odométrie, et comment les connaissances a priori (position estimée, base de données) sont mises à profit pour identifier les amers. La précision typiquement obtenue en matière de localisation est de 7 cm selon xy et 1 deg en cap

A new method to identify subclasses among AGB stars using Gaia and 2MASS photometry

Aims: We explore the wealth of high quality photometric data provided by data release 2 of the Gaia mission for long period variables (LPVs) in the Large Magellanic Cloud. Our goal is to identify stars of various types and masses along the Asymptotic Giant Branch. Methods: For this endeavour, we developed a new multi-band approach combining Wesenheit functions W_{RP,BP-RP} and W_{K_s,J-K_s} in the Gaia BP, RP and 2MASS J, K_s spectral ranges, respectively, and use a new diagram (W_{RP,BP-RP}-W_{K_s,J-K_s}) versus K_s to distinguish between different kinds of stars in our sample of LPVs. We used stellar population synthesis models to validate our approach. Results:We demonstrate the ability of the new diagram to discriminate between O-rich and C-rich objects, and to identify low-mass, intermediate-mass and massive O-rich red giants, as well as extreme C-rich stars. Stellar evolution and population synthesis models guide the interpretation of the results, highlighting the diagnostic power of the new tool to discriminate between stellar initial masses, chemical properties and evolutionary stages.Comment: accepted for publication in A&A Letters; 7 figures, 2 appendice

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 devel- oped to classify and extract information such as the pulsation period, mode of pulsation, mean magnitude, peak-to-peak amplitude of the light variation, sub-classification in type, multiplicity, secondary periodicities, light curve Fourier decomposition parameters, as well as physical parameters such as mass, metallicity, reddening and, for classical Cepheids, age, 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 Characterisation, 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 characterization by the SOS Cep&RRL pipeline (mean magnitude and pulsation char- acteristics) are published in 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 Data Release 2. Rotational modulation in late-type dwarfs

Context. Amongst the ≈5 × 10e+05 sources identified as variable stars in Gaia Data Release 2 (DR2), 26% are rotational modulation variable candidates of the BY Dra class. Gaia DR2 provides their multi-band (G, G_BP, and G_RP) photometric time series collected by the European Space Agency spacecraft Gaia during the first 22 months of operations as well as the essential parameters related to their flux modulation induced by surface inhomogeneities and rotation. Aims: We developed methods to identify the BY Dra variable candidates and to infer their variability parameters. Methods: BY Dra candidates were pre-selected from their position in the Hertzsprung-Russel diagram, built from Gaia parallaxes, G magnitudes, and (G_BP - G_RP) colours. Since the time evolution of the stellar active region can disrupt the coherence of the signal, segments not much longer than their expected evolution timescale were extracted from the entire photometric time series, and period search algorithms were applied to each segment. For the Gaia DR2, we selected sources with similar periods in at least two segments as candidate BY Dra variables. Results were further filtered considering the time-series phase coverage and the expected approximate light-curve shape. Results: Gaia DR2 includes rotational periods and modulation amplitudes of 147 535 BY Dra candidates. The data unveil the existence of two populations with distinctive period and amplitude distributions. The sample covers 38% of the whole sky when divided into bins (HEALPix) of ≈0.84 square degrees, and we estimate that this represents 0.7-5% of all BY Dra stars potentially detectable with Gaia. Conclusions: The preliminary data contained in Gaia DR2 illustrate the vast and unique information that the mission is going to provide on stellar rotation and magnetic activity. This information, complemented by the exquisite Gaia parallaxes, proper motions, and astrophysical parameters, is opening new and unique perspectives for our understanding of the evolution of stellar angular momentum and dynamo action

<i>Gaia</i> Data Release 1. Summary of the astrometric, photometric, and survey properties

Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR-Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr−1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr−1. For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data

Gaia Focused Product Release: Radial velocity time series of long-period variables

Context: The third Gaia Data Release (DR3) provided photometric time series of more than 2 million long-period variable (LPV) candidates. Anticipating the publication of full radial-velocity data planned with Data Release 4, this Focused Product Release (FPR) provides radial-velocity time series for a selection of LPV candidates with high-quality observations. // Aims: We describe the production and content of the Gaia catalog of LPV radial-velocity time series, and the methods used to compute the variability parameters published as part of the Gaia FPR. // Methods: Starting from the DR3 catalog of LPV candidates, we applied several filters to construct a sample of sources with high-quality radial-velocity measurements. We modeled their radial-velocity and photometric time series to derive their periods and amplitudes, and further refined the sample by requiring compatibility between the radial-velocity period and at least one of the G, GBP, or GRP photometric periods. // Results: The catalog includes radial-velocity time series and variability parameters for 9614 sources in the magnitude range 6 ≲ G/mag ≲ 14, including a flagged top-quality subsample of 6093 stars whose radial-velocity periods are fully compatible with the values derived from the G, GBP, and GRP photometric time series. The radial-velocity time series contain a mean of 24 measurements per source taken unevenly over a duration of about three years. We identify the great majority of the sources (88%) as genuine LPV candidates, with about half of them showing a pulsation period and the other half displaying a long secondary period. The remaining 12% of the catalog consists of candidate ellipsoidal binaries. Quality checks against radial velocities available in the literature show excellent agreement. We provide some illustrative examples and cautionary remarks. // Conclusions: The publication of radial-velocity time series for almost ten thousand LPV candidates constitutes, by far, the largest such database available to date in the literature. The availability of simultaneous photometric measurements gives a unique added value to the Gaia catalog

Gaia Focused Product Release: A catalogue of sources around quasars to search for strongly lensed quasars

Context. Strongly lensed quasars are fundamental sources for cosmology. The Gaia space mission covers the entire sky with the unprecedented resolution of $0.18$" in the optical, making it an ideal instrument to search for gravitational lenses down to the limiting magnitude of 21. Nevertheless, the previous Gaia Data Releases are known to be incomplete for small angular separations such as those expected for most lenses. Aims. We present the Data Processing and Analysis Consortium GravLens pipeline, which was built to analyse all Gaia detections around quasars and to cluster them into sources, thus producing a catalogue of secondary sources around each quasar. We analysed the resulting catalogue to produce scores that indicate source configurations that are compatible with strongly lensed quasars. Methods. GravLens uses the DBSCAN unsupervised clustering algorithm to detect sources around quasars. The resulting catalogue of multiplets is then analysed with several methods to identify potential gravitational lenses. We developed and applied an outlier scoring method, a comparison between the average BP and RP spectra of the components, and we also used an extremely randomised tree algorithm. These methods produce scores to identify the most probable configurations and to establish a list of lens candidates. Results. We analysed the environment of 3 760 032 quasars. A total of 4 760 920 sources, including the quasars, were found within 6" of the quasar positions. This list is given in the Gaia archive. In 87\% of cases, the quasar remains a single source, and in 501 385 cases neighbouring sources were detected. We propose a list of 381 lensed candidates, of which we identified 49 as the most promising. Beyond these candidates, the associate tables in this Focused Product Release allow the entire community to explore the unique Gaia data for strong lensing studies further.Comment: 35 pages, 60 figures, accepted for publication by Astronomy and Astrophysic