arXiv subjects

L. M. Sarro

Publications and source records attributed to L. M. Sarro.

At least 55 records · Page 3Linked to original sources

arXiv2018

Gaia Data Release 2: Specific characterisation and validation of all-sky Cepheids and RR Lyrae stars

The Gaia second Data Release (DR2) presents a first mapping of full-sky RR Lyrae stars and Cepheids observed by the spacecraft during the initial 22 months of science operations. The Specific Object Study (SOS) pipeline, developed to validate and fully characterise Cepheids and RR Lyrae stars (SOS Cep&RRL) observed by Gaia, has been presented in the documentation and papers accompanying the Gaia first Data Release. Here we describe how the SOS pipeline was modified to allow for processing the Gaia multiband (G, G_BP and G_RP) time series photometry of all-sky candidate variables and produce specific results for confirmed RR Lyrae stars and Cepheids that are published in the DR2 catalogue. The SOS Cep&RRL processing uses tools such as the period-amplitude and the period-luminosity relations in the G band. For the analysis of the Gaia DR2 candidates we also used tools based on the G_BP and G_RP photometry, such as the period-Wesenheit relation in (G,G_RP). Multiband time series photometry and characterisation by the SOS Cep&RRL pipeline are published in Gaia DR2 for 150,359 such variables (9,575 classified as Cepheids and 140,784 as RR Lyrae stars) distributed all over the sky. The sample includes variables in 87 globular clusters and 14 dwarf galaxies. To the best of our knowledge, as of 25 April 2018, variability of 50,570 of these sources (350 Cepheids and 50,220 RR Lyrae stars) is not known in the literature, hence likely they are new discoveries by Gaia. An estimate of the interstellar absorption is published for 54,272 fundamental-mode RR Lyrae stars from a relation based on the G-band amplitude and the pulsation period. Metallicities derived from the Fourier parameters of the light curves are also released for 64,932 RR Lyrae stars and 3,738 fundamental-mode classical Cepheids with period shorter than 6.3 days.

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arXiv2018

Gaia Data Release 2: The first Gaia catalogue of long-period variable candidates

Gaia DR2 provides a unique all-sky catalogue of 550'737 variable stars, of which 151'761 are long-period variable (LPV) candidates with G variability amplitudes larger than 0.2 mag (5-95% quantile range). About one-fifth of the LPV candidates are Mira candidates, the majority of the rest are semi-regular variable candidates. For each source, G, BP , and RP photometric time-series are published, together with some LPV-specific attributes for the subset of 89'617 candidates with periods in G longer than 60 days. We describe this first Gaia catalogue of LPV candidates, and present various validation checks. Various samples of LPVs were used to validate the catalogue: a sample of well-studied very bright LPVs with light curves from the AAVSO that are partly contemporaneous with Gaia light curves, a sample of Gaia LPV candidates with good parallaxes, the ASAS_SN catalogue of LPVs, and the OGLE catalogues of LPVs towards the Magellanic Clouds and the Galactic bulge. The analyses of these samples show a good agreement between Gaia DR2 and literature periods. The same is globally true for bolometric corrections of M-type stars. The main contaminant of our DR2 catalogue comes from young stellar objects (YSOs) in the solar vicinity (within ~1 kpc), although their number in the whole catalogue is only at the percent level. A cautionary note is provided about parallax-dependent LPV attributes published in the catalogue. This first Gaia catalogue of LPVs approximately doubles the number of known LPVs with amplitudes larger than 0.2 mag, despite the conservative candidate selection criteria that prioritise low contamination over high completeness, and despite the limited DR2 time coverage compared to the long periods characteristic of LPVs. It also contains a small set of YSO candidates, which offers the serendipitous opportunity to study these objects at an early stage of the Gaia data releases.

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arXiv2018

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

The Gaia Data Release 2 (DR2): 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, delta Scuti & SX Phoenicis stars, and short-timescale variables. In this release we aim to provide useful but not necessarily complete samples of candidates. The processed Gaia data consist of the G, BP, and RP 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 well as various visualisation tools. The DR2 variability release contains: 228'904 RR Lyrae stars, 11'438 Cepheids, 151'761 LPVs, 147'535 stars with rotation modulation, 8'882 delta Scuti & SX Phoenicis stars, and 3'018 short-timescale variables. These results are distributed over a classification and various Specific Object Studies (SOS) 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 function of sky position due to the non-uniform sky coverage and intermediate calibration level of this data. The probabilistic and automated nature of this work implies certain completeness and contamination rates which are quantified so that users can anticipate their effects. This means that even well-known variable sources can be missed or misidentified in the published data. 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.

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arXiv2018

Gaia Data Release 2: using Gaia parallaxes

The second Gaia data release (GDR2) provides precise five-parameter astrometric data (positions, proper motions and parallaxes) for an unprecedented amount of sources (more than $1.3$ billion, mostly stars). The use of this wealth of astrometric data comes with a specific challenge: how does one properly infer from these data the astrophysical parameters of interest? The main - but not only - focus of this paper is the issue of the estimation of distances from parallaxes, possibly combined with other information. We start with a critical review of the methods traditionally used to obtain distances from parallaxes and their shortcomings. Then we provide guidelines on how to use parallaxes more efficiently to estimate distances by using Bayesian methods. In particular also we show that negative parallaxes, or parallaxes with relatively larger uncertainties still contain valuable information. Finally, we provide examples that show more generally how to use astrometric data for parameter estimation, including the combination of proper motions and parallaxes and the handling of covariances in the uncertainties. The paper contains examples based on simulated Gaia data to illustrate the problems and the solutions proposed. Furthermore, the developments and methods proposed in the paper are linked to a set of tutorials included in the Gaia archive documentation that provide practical examples and a good starting point for the application of the recommendations to actual problems. In all cases the source code for the analysis methods is provided. Our main recommendation is to always treat the derivation of (astro-) physical parameters from astrometric data, in particular when parallaxes are involved, as an inference problem which should preferably be handled with a full Bayesian approach.

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arXiv2018

The seven sisters DANCe IV. Bayesian hierarchical model

Aims. We develop, test and characterise of a new statistical tool (intelligent system) for the sifting and analysis of nearby young open cluster (NYOC) populations. Methods. Using a Bayesian formalism, this statistical tool is able to obtain the posterior distributions of parameters governing the cluster model. It also uses hierarchical bayesian models to establish weakly informative priors, and incorporates the treatment of missing values and non-homogeneous (heteroscedastic) observational uncertainties. Results. From simulations, we estimate that this statistical tool renders kinematic (proper motion) and photometric (luminosity) distributions of the cluster population with a contamination rate of $5.8 \pm 0.2$ %. The luminosity distributions and present day mass function agree with the ones found by Bouy et al. (2015b) on the completeness interval of the survey. At the probability threshold of maximum accuracy, the classifier recovers $\sim$ 90% of Bouy et al. (2015b) candidate members and finds 10% of new ones. Conclusions. A new statistical tool for the analysis of NYOC is introduced, tested and characterised. Its comprehensive modelling of the data properties allows it to get rid of the biases present in previous works. In particular, those resulting from the use of only completely observed (non-missing) data and the assumption of homoskedastic uncertainties. Also, its Bayesian framework allows it to properly propagate observational uncertainties into membership probabilities and cluster velocity and luminosity distributions. Our results are in a general agreement with those from the literature, although we provide the most up-to-date and extended list of candidate members of the Pleiades cluster.

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arXiv2018

The Seven Sisters DANCe III: Projected spatial distribution

Methods. We compute Bayesian evidences and Bayes Factors for a set of variations of the classical radial models by King (1962), Elson et al. (1987) and Lauer et al. (1995). The variations incorporate different degrees of model freedom and complexity, amongst which we include biaxial (elliptical) symmetry, and luminosity segregation. As a by-product of the model comparison, we obtain posterior distributions and maximum a posteriori estimates for each set of model parameters. Results. We find that the model comparison results depend on the spatial extent of the region used for the analysis. For a circle of 11.5 parsecs around the cluster centre (the most homogeneous and complete region), we find no compelling reason to abandon Kings model, although the Generalised King model, introduced in this work, has slightly better fitting properties. Furthermore, we find strong evidence against radially symmetric models when compared to the elliptic extensions. Finally, we find that including mass segregation in the form of luminosity segregation in the J band, is strongly supported in all our models. Conclusions. We have put the question of the projected spatial distribution of the Pleiades cluster on a solid probabilistic framework, and inferred its properties using the most exhaustive and least contaminated list of Pleiades candidate members available to date. Our results suggest however that this sample may still lack about 20% of the expected number of cluster members. Therefore, this study should be revised when the completeness and homogeneity of the data can be extended beyond the 11.5 parsecs limit. Such study will allow a more precise determination of the Pleiades spatial distribution, its tidal radius, ellipticity, number of objects and total mass.

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arXiv2017

Gaia Data Release 1. Testing the parallaxes with local Cepheids and RR Lyrae stars

Parallaxes for 331 classical Cepheids, 31 Type II Cepheids and 364 RR Lyrae stars in common between Gaia and the Hipparcos and Tycho-2 catalogues are published in Gaia Data Release 1 (DR1) as part of the Tycho-Gaia Astrometric Solution (TGAS). In order to test these first parallax measurements of the primary standard candles of the cosmological distance ladder, that involve astrometry collected by Gaia during the initial 14 months of science operation, we compared them with literature estimates and derived new period-luminosity ($PL$), period-Wesenheit ($PW$) relations for classical and Type II Cepheids and infrared $PL$, $PL$-metallicity ($PLZ$) and optical luminosity-metallicity ($M_V$-[Fe/H]) relations for the RR Lyrae stars, with zero points based on TGAS. The new relations were computed using multi-band ($V,I,J,K_{\mathrm{s}},W_{1}$) photometry and spectroscopic metal abundances available in the literature, and applying three alternative approaches: (i) by linear least squares fitting the absolute magnitudes inferred from direct transformation of the TGAS parallaxes, (ii) by adopting astrometric-based luminosities, and (iii) using a Bayesian fitting approach. TGAS parallaxes bring a significant added value to the previous Hipparcos estimates. The relations presented in this paper represent first Gaia-calibrated relations and form a "work-in-progress" milestone report in the wait for Gaia-only parallaxes of which a first solution will become available with Gaia's Data Release 2 (DR2) in 2018.

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arXiv2017

The Gaia Ultracool Dwarf Sample. I. Known L and T dwarfs and the first Gaia data release

We identify and investigate known ultracool stars and brown dwarfs that are being observed or indirectly constrained by the Gaia mission. These objects will be the core of the Gaia ultracool dwarf sample composed of all dwarfs later than M7 that Gaia will provide direct or indirect information on. We match known L and T dwarfs to the Gaia first data release, the Two Micron All Sky Survey and the Wide-field Infrared Survey Explorer AllWISE survey and examine the Gaia and infrared colours, along with proper motions, to improve spectral typing, identify outliers and find mismatches. There are 321 L and T dwarfs observed directly in the Gaia first data release, of which 10 are later than L7. This represents 45 % of all the known LT dwarfs with estimated Gaia G magnitudes brighter than 20.3 mag. We determine proper motions for the 321 objects from Gaia and the Two Micron All Sky Survey positions. Combining the Gaia and infrared magnitudes provides useful diagnostic diagrams for the determination of L and T dwarf physical parameters. We then search the Tycho-Gaia astrometric solution Gaia first data release subset to find any objects with common proper motions to known L and T dwarfs and a high probability of being related. We find 15 new candidate common proper motion systems.

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arXiv2017

Gaia Data Release 1: The variability processing & analysis and its application to the south ecliptic pole region

The ESA Gaia mission provides a unique time-domain survey for more than one billion sources brighter than G=20.7 mag. Gaia offers the unprecedented opportunity to study variability phenomena in the Universe thanks to multi-epoch G-magnitude photometry in addition to astrometry, blue and red spectro-photometry, and spectroscopy. Within the Gaia Consortium, Coordination Unit 7 has the responsibility to detect variable objects, classify them, derive characteristic parameters for specific variability classes, and provide global descriptions of variable phenomena. We describe the variability processing and analysis that we plan to apply to the successive data releases, and we present its application to the G-band photometry results of the first 14 months of Gaia operations that comprises 28 days of Ecliptic Pole Scanning Law and 13 months of Nominal Scanning Law. Out of the 694 million, all-sky, sources that have calibrated G-band photometry in this first stage of the mission, about 2.3 million sources that have at least 20 observations are located within 38 degrees from the South Ecliptic Pole. We detect about 14% of them as variable candidates, among which the automated classification identified 9347 Cepheid and RR Lyrae candidates. Additional visual inspections and selection criteria led to the publication of 3194 Cepheid and RR Lyrae stars, described in Clementini et al. (2016). Under the restrictive conditions for DR1, the completenesses of Cepheids and RR Lyrae stars are estimated at 67% and 58%, respectively, numbers that will significantly increase with subsequent Gaia data releases. Data processing within the Gaia Consortium is iterative, the quality of the data and the results being improved at each iteration. The results presented in this article show a glimpse of the exceptional harvest that is to be expected from the Gaia mission for variability phenomena. [abridged]

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arXiv2016

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

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.

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arXiv2016

Orion revisited III. The Orion Belt population

This paper continues our study of the foreground population to the Orion molecular clouds. The goal is to characterize the foreground population north of NGC 1981 and to investigate the star formation history in the large Orion star-forming region. We focus on a region covering about 25 square degrees, centered on the $ε$ Orionis supergiant (HD 37128, B0\,Ia) and covering the Orion Belt asterism. We used a combination of optical (SDSS) and near-infrared (2MASS) data, informed by X-ray (\textit{XMM-Newton}) and mid-infrared (WISE) data, to construct a suite of color-color and color-magnitude diagrams for all available sources. We then applied a new statistical multiband technique to isolate a previously unknown stellar population in this region. We identify a rich and well-defined stellar population in the surveyed region that has about 2\,000 objects that are mostly M stars. We infer the age for this new population to be at least 5\, Myr and likely $\sim10$\,Myr and estimate a total of about 2\,500 members, assuming a normal IMF. This new population, which we call the Orion Belt population, is essentially extinction-free, disk-free, and its spatial distribution is roughly centered near $ε$ Ori, although substructure is clearly present. The Orion Belt population is likely the low-mass counterpart to the Ori OB Ib subgroup. Although our results do not rule out Blaauw's sequential star formation scenario for Orion, we argue that the recently proposed blue streams scenario provides a better framework on which one can explain the Orion star formation region as a whole. We speculate that the Orion Belt population could represent the evolved counterpart of an Orion nebula-like cluster.

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arXiv2016

The seven sisters DANCe.II. Proper motions and the lithium-rotation-activity connection for G and K Pleiads

Stellar clusters are open windows to understand stellar evolution. Specifically, the change with time and the dependence on mass of different stellar properties. As such, they are our laboratories where different theories can be tested. We try to understand the origin of the connection between lithium depletion in F, G and K stars, rotation and activity, in particular in the Pleiades open cluster. We have collected all the relevant data in the literature, including information regarding rotation period, binarity and activity, and cross-matched with proper motions, multi-wavelength photometry and membership probability from the DANCe database. In order to avoid biases, only Pleiades single members with probabilities larger than p=0.75 have been included in the discussion. Results. The analysis confirms that there is a strong link between activity, rotation and the lithium equivalent width excess, specially for the range Lum(bol) = 0.5-0.2 Lsun (about K2-K7 spectral types or 0.75-0.95 Msun). It is not possible to disentangle these effects but we cannot exclude that the observed lithium overabundance is partially an observational effect due to enhanced activity, due to a large coverage by stellar spots induced by high rotation rates. Since a bona fide lithium enhancement is present in young, fast rotators, both activity and rotation should play a role in the lithium problem.

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arXiv2015

The Seven Sisters DANCe. I. Empirical isochrones, Luminosity and Mass Functions of the Pleiades cluster

The DANCe survey provides photometric and astrometric (position and proper motion) measurements for approximately 2 millions unique sources in a region encompassing $\approx$80deg$^{2}$ centered around the Pleiades cluster. We aim at deriving a complete census of the Pleiades, and measure the mass and luminosity function of the cluster. Using the probabilistic selection method described in Sarro+2014, we identify high probability members in the DANCe ($i\ge$14mag) and Tycho-2 ($V\lesssim$12mag) catalogues, and study the properties of the cluster over the corresponding luminosity range. We find a total of 2109 high probability members, of which 812 are new, making it the most extensive and complete census of the cluster to date. The luminosity and mass functions of the cluster are computed from the most massive members down to $\approx$0.025M$_{\odot}$. The size, sensitivity and quality of the sample result in the most precise luminosity and mass functions observed to date for a cluster. Our census supersedes previous studies of the Pleiades cluster populations, both in terms of sensitivity and accuracy.

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arXiv2015

Messier 35 (NGC2168) DANCe I. Membership, proper motions and multi-wavelength photometry

We aim at identifying the cluster's members by deriving membership probabilities for the sources within 1 degree of the cluster's center, going further away than equivalent previous studies. We measure accurate proper motions and multi-wavelength (optical and near-infrared) photometry using ground based archival images of the cluster. We use these measurements to compute membership probabilities. The list of candidate members from Barrado+2001 is used as training set to identify the cluster's locus in a multi-dimensional space made of proper motions, luminosities and colors. The final catalog includes 338892 sources with multi-wavelength photometry. Approximately half (194452) were detected at more than two epochs and we measured their proper motion and used it to derive membership probability. A total of 4349 candidate members with membership probabilities greater than 50% are found in this sample in the luminosity range between 10 and 22mag. The slow proper motion of the cluster and the overlap of its sequence with the field and background sequences in almost all color-magnitude and color-color diagrams complicate the analysis and the contamination level is expected to be significant. Our study nevertheless provides a coherent and quantitative membership analysis of Messier 35 based on a large fraction of the best ground-based data sets obtained over the past 18 years. As such, it represents a valuable input for follow-up studies using in particular the Kepler K2 photometric time series.

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arXiv2014

Orion revisited. II. The foreground population to Orion A

Following the recent discovery of a large population of young stars in front of the Orion Nebula, we carried out an observational campaign with the DECam wide-field camera covering ~10~deg^2 centered on NGC 1980 to confirm, probe the extent of, and characterize this foreground population of pre-main-sequence stars. We confirm the presence of a large foreground population towards the Orion A cloud. This population contains several distinct subgroups, including NGC1980 and NGC1981, and stretches across several degrees in front of the Orion A cloud. By comparing the location of their sequence in various color-magnitude diagrams with other clusters, we found a distance and an age of 380pc and 5~10Myr, in good agreement with previous estimates. Our final sample includes 2123 candidate members and is complete from below the hydrogen-burning limit to about 0.3Msun, where the data start to be limited by saturation. Extrapolating the mass function to the high masses, we estimate a total number of ~2600 members in the surveyed region. We confirm the presence of a rich, contiguous, and essentially coeval population of about 2600 foreground stars in front of the Orion A cloud, loosely clustered around NGC1980, NGC1981, and a new group in the foreground of the OMC-2/3. For the area of the cloud surveyed, this result implies that there are more young stars in the foreground population than young stars inside the cloud. Assuming a normal initial mass function, we estimate that between one to a few supernovae must have exploded in the foreground population in the past few million years, close to the surface of Orion A, which might be responsible, together with stellar winds, for the structure and star formation activity in these clouds. This long-overlooked foreground stellar population is of great significance, calling for a revision of the star formation history in this region of the Galaxy.

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arXiv2014

Cluster membership probabilities from proper motions and multiwavelength photometric catalogues: I. Method and application to the Pleiades cluster

We present a new technique designed to take full advantage of the high dimensionality (photometric, astrometric, temporal) of the DANCe survey to derive self-consistent and robust membership probabilities of the Pleiades cluster. We aim at developing a methodology to infer membership probabilities to the Pleiades cluster from the DANCe multidimensional astro-photometric data set in a consistent way throughout the entire derivation. The determination of the membership probabilities has to be applicable to censored data and must incorporate the measurement uncertainties into the inference procedure. We use Bayes' theorem and a curvilinear forward model for the likelihood of the measurements of cluster members in the colour-magnitude space, to infer posterior membership probabilities. The distribution of the cluster members proper motions and the distribution of contaminants in the full multidimensional astro-photometric space is modelled with a mixture-of-Gaussians likelihood. We analyse several representation spaces composed of the proper motions plus a subset of the available magnitudes and colour indices. We select two prominent representation spaces composed of variables selected using feature relevance determination techniques based in Random Forests, and analyse the resulting samples of high probability candidates. We consistently find lists of high probability (p > 0.9975) candidates with $\approx$ 1000 sources, 4 to 5 times more than obtained in the most recent astro-photometric studies of the cluster. The methodology presented here is ready for application in data sets that include more dimensions, such as radial and/or rotational velocities, spectral indices and variability.

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arXiv2013

The Gaia astrophysical parameters inference system (Apsis). Pre-launch description

The Gaia satellite will survey the entire celestial sphere down to 20th magnitude, obtaining astrometry, photometry, and low resolution spectrophotometry on one billion astronomical sources, plus radial velocities for over one hundred million stars. Its main objective is to take a census of the stellar content of our Galaxy, with the goal of revealing its formation and evolution. Gaia's unique feature is the measurement of parallaxes and proper motions with hitherto unparalleled accuracy for many objects. As a survey, the physical properties of most of these objects are unknown. Here we describe the data analysis system put together by the Gaia consortium to classify these objects and to infer their astrophysical properties using the satellite's data. This system covers single stars, (unresolved) binary stars, quasars, and galaxies, all covering a wide parameter space. Multiple methods are used for many types of stars, producing multiple results for the end user according to different models and assumptions. Prior to its application to real Gaia data the accuracy of these methods cannot be assessed definitively. But as an example of the current performance, we can attain internal accuracies (RMS residuals) on F,G,K,M dwarfs and giants at G=15 (V=15-17) for a wide range of metallicites and interstellar extinctions of around 100K in effective temperature (Teff), 0.1mag in extinction (A0), 0.2dex in metallicity ([Fe/H]), and 0.25dex in surface gravity (logg). The accuracy is a strong function of the parameters themselves, varying by a factor of more than two up or down over this parameter range. After its launch in November 2013, Gaia will nominally observe for five years, during which the system we describe will continue to evolve in light of experience with the real data.

astro-ph.IM↗

arXiv2013

Automated classification of Hipparcos unsolved variables

We present an automated classification of stars exhibiting periodic, non-periodic and irregular light variations. The Hipparcos catalogue of unsolved variables is employed to complement the training set of periodic variables of Dubath et al. with irregular and non-periodic representatives, leading to 3881 sources in total which describe 24 variability types. The attributes employed to characterize light-curve features are selected according to their relevance for classification. Classifier models are produced with random forests and a multistage methodology based on Bayesian networks, achieving overall misclassification rates under 12 per cent. Both classifiers are applied to predict variability types for 6051 Hipparcos variables associated with uncertain or missing types in the literature.

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