Abstract
We propose a robust principal component analysis framework for the exploitation of multiband photometric measurements in large surveys. Period search results are improved using the ...time-series of the first principal component due to its optimized signal-to-noise ratio. The presence of correlated excess variations in the multivariate time-series enables the detection of weaker variability. Furthermore, the direction of the largest variance differs for certain types of variable stars. This can be used as an efficient attribute for classification. The application of the method to a subsample of Sloan Digital Sky Survey Stripe 82 data yielded 132 high-amplitude δ Scuti variables. We also found 129 new RR Lyrae variables, complementary to the catalogue of Sesar et al., extending the halo area mapped by Stripe 82 RR Lyrae stars towards the Galactic bulge. The sample also comprises 25 multiperiodic or Blazhko RR Lyrae stars.
Context. The advent of large scale multi-epoch surveys raises the need for automated light curve (LC) processing. This is particularly true for eclipsing binaries (EBs), which form one of the most ...populated types of variable objects. The Gaia mission, launched at the end of 2013, is expected to detect of the order of few million EBs over a five-year mission. Aims. We present an automated procedure to characterize EBs based on the geometric morphology of their LCs with two aims: first to study an ensemble of EBs on a statistical ground without the need to model the binary system, and second to enable the automated identification of EBs that display atypical LCs. Methods. We modeled the folded LC geometry of EBs using up to two Gaussian functions for the eclipses and a cosine function for any ellipsoidal-like variability that may be present between the eclipses. The procedure is applied to the OGLE-III data set of EBs in the Large Magellanic Cloud (LMC) as a proof of concept. The Bayesian information criterion is used to select the best model among models containing various combinations of those components, as well as to estimate the significance of the components. Results. Based on the two-Gaussian models, EBs with atypical LC geometries are successfully identified in two diagrams, using the Abbe values of the original and residual folded LCs, and the reduced χ2. Cleaning the data set from the atypical cases and further filtering out LCs that contain non-significant eclipse candidates, the ensemble of EBs can be studied on a statistical ground using the two-Gaussian model parameters. For illustrative purposes, we present the distribution of projected eccentricities as a function of orbital period for the OGLE-III set of EBs in the LMC, as well as the distribution of their primary versus secondary eclipse widths.
Gaia Data Release 3 Lanzafame, A. C.; Brugaletta, E.; Frémat, Y. ...
Astronomy and astrophysics (Berlin),
06/2023, Letnik:
674
Journal Article
Recenzirano
Odprti dostop
Context.
The
Gaia
Radial Velocity Spectrometer (RVS) provides the unique opportunity of a spectroscopic analysis of millions of stars at medium resolution (
λ
/Δ
λ
∼ 11 500) in the near-infrared ...(845−872 nm). This wavelength range includes the Ca
II
infrared triplet (IRT) at 850.03, 854.44, and 866.45 nm, which is a good indicator of magnetic activity in the chromosphere of late–type stars.
Aims.
Here we present the method devised for inferring the
Gaia
stellar activity index from the analysis of the Ca
II
IRT in the RVS spectrum, together with its scientific validation.
Methods.
The
Gaia
stellar activity index is derived from the Ca
II
IRT excess equivalent width with respect to a reference spectrum, taking the projected rotational velocity (
v
sin
i
) into account. We performed scientific validation of the
Gaia
stellar activity index by deriving a
R
′
IRT
index, which is largely independent of the photospheric parameters, and considering the correlation with the
R
′
HK
index for a sample of stars. A sample of well-studied pre-main-sequence (PMS) stars is considered to identify the regime in which the
Gaia
stellar activity index may be affected by mass accretion. The position of these stars in the colour–magnitude diagram and the correlation with the amplitude of the photometric rotational modulation is also scrutinised.
Results.Gaia
DR3 contains a stellar activity index derived from the Ca
II
IRT for some 2 × 10
6
stars in the Galaxy. This represents a ‘gold mine’ for studies on stellar magnetic activity and mass accretion in the solar vicinity. Three regimes of the chromospheric stellar activity are identified, confirming suggestions made by previous authors based on much smaller
R
′
HK
datasets. The highest stellar activity regime is associated with PMS stars and RS CVn systems, in which activity is enhanced by tidal interaction. Some evidence of a bimodal distribution in main sequence (MS) stars with
T
eff
≳ 5000 K is also found, which defines the two other regimes, without a clear gap in between. Stars with 3500 K ≲
T
eff
≲ 5000 K are found to be either very active PMS stars or active MS stars with a unimodal distribution in chromospheric activity. A dramatic change in the activity distribution is found for
T
eff
≲ 3500 K, with a dominance of low activity stars close to the transition between partially- and fully convective stars and a rise in activity down into the fully convective regime.
Gaia Data Release 3 Recio-Blanco, A.; de Laverny, P.; Palicio, P. A. ...
Astronomy and astrophysics (Berlin),
06/2023, Letnik:
674
Journal Article
Recenzirano
Odprti dostop
Context.
The chemo-physical parametrisation of stellar spectra is essential for understanding the nature and evolution of stars and of Galactic stellar populations. A worldwide observational effort ...from the ground has provided, in one century, an extremely heterogeneous collection of chemical abundances for about two million stars in total, with fragmentary sky coverage.
Aims.
This situation is revolutionised by the
Gaia
third data release (DR3), which contains the parametrisation of Radial Velocity Spectrometer (RVS) data performed by the General Stellar Parametriser-spectroscopy, GSP-Spec, module. Here we describe the parametrisation of the first 34 months of
Gaia
RVS observations.
Methods.
GSP-Spec estimates the chemo-physical parameters from combined RVS spectra of single stars, without additional inputs from astrometric, photometric, or spectro-photometric BP/RP data. The main analysis workflow described here, MatisseGauguin, is based on projection and optimisation methods and provides the stellar atmospheric parameters; the individual chemical abundances of N, Mg, Si, S, Ca, Ti, Cr, Fe
I
, Fe
II
, Ni, Zr, Ce and Nd; the differential equivalent width of a cyanogen line; and the parameters of a diffuse interstellar band (DIB) feature. Another workflow, based on an artificial neural network (ANN) and referred to with the same acronym, provides a second set of atmospheric parameters that are useful for classification control. For both workflows, we implement a detailed quality flag chain considering different error sources.
Results.
With about 5.6 million stars, the
Gaia
DR3 GSP-Spec all-sky catalogue is the largest compilation of stellar chemo-physical parameters ever published and the first one from space data. Internal and external biases have been studied taking into account the implemented flags. In some cases, simple calibrations with low degree polynomials are suggested. The homogeneity and quality of the estimated parameters enables chemo-dynamical studies of Galactic stellar populations, interstellar extinction studies from individual spectra, and clear constraints on stellar evolution models. We highly recommend that users adopt the provided quality flags for scientific exploitation.
Conclusions.
The
Gaia
DR3 GSP-Spec catalogue is a major step in the scientific exploration of Milky Way stellar populations. It will be followed by increasingly large and higher quality catalogues in future data releases, confirming the
Gaia
promise of a new Galactic vision.
Gaia Data Release 3 Eyer, L.; Audard, M.; Holl, B. ...
Astronomy and astrophysics (Berlin),
06/2023, Letnik:
674
Journal Article
Recenzirano
Odprti dostop
Context.
Gaia
has been in operations since 2014, and two full data releases (DR) have been delivered so far: DR1 in 2016 and DR2 in 2018. The third
Gaia
data release expands from the early data ...release (EDR3) in 2020, which contained the five-parameter astrometric solution and mean photometry for 1.8 billion sources by providing 34 months of multi-epoch observations that allowed us to systematically probe, characterise, and classify variable celestial phenomena.
Aims.
We present a summary of the variability processing and analysis of the photometric and spectroscopic time series of 1.8 billion sources carried out for
Gaia
DR3.
Methods.
We used statistical and machine learning methods to characterise and classify the variable sources. Training sets were built from a global revision of major published variable star catalogues. For a subset of classes, specific detailed studies were conducted to confirm their class membership and to derive parameters that are adapted to the peculiarity of the considered class.
Results.
In total, 10.5 million objects are identified as variable in
Gaia
DR3 and have associated time series in
G
,
G
BP
, and
G
RP
and, in some cases, radial velocity time series. The DR3 variable sources subdivide into 9.5 million variable stars and 1 million active galactic nuclei or ‘quasars’. In addition, supervised classification identified 2.5 million galaxies thanks to spurious variability induced by the extent of these objects. The variability analysis output in the DR3 archive amounts to 17 tables, containing a total of 365 parameters. We publish 35 types and subtypes of variable objects. For 11 variable types, additional specific object parameters are published. Here, we provide an overview of the estimated completeness and contamination of most variability classes.
Conclusions.
Thanks to
Gaia
, we present the largest whole-sky variability analysis based on coherent photometric, astrometric, and spectroscopic data. Future
Gaia
data releases will more than double the span of time series and the number of observations, allowing the publication of an even richer catalogue.
Gaia Data Release 1 Clementini, G; Ripepi, V; Leccia, S ...
Astronomy and astrophysics (Berlin),
11/2016, Letnik:
595
Journal Article
Recenzirano
Odprti dostop
Context. The European Space Agency spacecraft Gaia is expected to observe about 10000 Galactic Cepheids and over 100000 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 developed to classify and extract information such as the pulsation period, mode of pulsation, mean magnitude, peak-to-peak amplitude of the light variation, subclassification in type, multiplicity, secondary periodicities, and light curve Fourier decomposition parameters, as well as physical parameters such as mass, metallicity, reddening, and age (for classical Cepheids) 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 Characterization, 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 characterisation by the SOS Cep&RRL pipeline (mean magnitude and pulsation characteristics) are published in Gaia DR1 for a total sample of 3194 variable stars (599 Cepheids and 2595 RR Lyrae stars), of which 386 (43 Cepheids and 343 RR Lyrae stars) are new discoveries by Gaia. All 3194 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 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.
Abstract
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.
Gaia Data Release 2 Holl, B.; Audard, M.; Nienartowicz, K. ...
Astronomy and astrophysics (Berlin),
10/2018, Letnik:
618
Journal Article
Recenzirano
Odprti dostop
Context.
The
Gaia
Data Release 2 (DR2) contains more than half a million sources that are identified as variable stars.
Aims.
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,
δ
Scuti and SX Phoenicis stars, and short-timescale variables. In this release we aim to provide useful but not necessarily complete samples of candidates.
Methods.
The processed
Gaia
data consist of the
G
,
G
BP
, and
G
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 were various visualisation tools to interpret the data.
Results.
The DR2 variability release contains 228 904 RR Lyrae stars, 11 438 Cepheids, 151 761 LPVs, 147 535 stars with rotation modulation, 8882
δ
Scuti and SX Phoenicis stars, and 3018 short-timescale variables. These results are distributed over a classification and various Specific Object Studies 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 a function of sky position as a result of the non-uniform sky coverage and intermediate calibration level of these data. The probabilistic and automated nature of this work implies certain completeness and contamination rates that are quantified so that users can anticipate their effects. Thismeans that even well-known variable sources can be missed or misidentified in the published data.
Conclusions.
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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