We present an evaluation of the performance of an automated classification of the Hipparcos periodic variable stars into 26 types. The sub-sample with the most reliable variability types available in ...the literature is used to train supervised algorithms to characterize the type dependencies on a number of attributes. The most useful attributes evaluated with the random forest methodology include, in decreasing order of importance, the period, the amplitude, the V−I colour index, the absolute magnitude, the residual around the folded light-curve model, the magnitude distribution skewness and the amplitude of the second harmonic of the Fourier series model relative to that of the fundamental frequency. Random forests and a multi-stage scheme involving Bayesian network and Gaussian mixture methods lead to statistically equivalent results. In standard 10-fold cross-validation (CV) experiments, the rate of correct classification is between 90 and 100 per cent, depending on the variability type. The main mis-classification cases, up to a rate of about 10 per cent, arise due to confusion between SPB and ACV blue variables and between eclipsing binaries, ellipsoidal variables and other variability types. Our training set and the predicted types for the other Hipparcos periodic stars are available online.
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 Lanzafame, A. C.; Distefano, E.; Messina, S. ...
Astronomy and astrophysics (Berlin),
08/2018, Letnik:
616
Journal Article
Recenzirano
Odprti dostop
Context. Amongst the ≈5 × 105 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, GBP, and GRP) 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 (GBP − GRP) 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.
Gaia Data Release 2 Clementini, G.; Ripepi, V.; Molinaro, R. ...
Astronomy and astrophysics (Berlin),
02/2019, Letnik:
622
Journal Article
Recenzirano
Odprti dostop
Context. 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. Aims. The ...Specific Objects 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 multi-band (G, GBP, and GRP) 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. Methods. 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 GBP and GRP photometry, such as the period–Wesenheit relation in (G, GRP). Results. Multi-band time-series photometry and characterisation by the SOS Cep&RRL pipeline are published in Gaia DR2 for 150 359 such variables (9575 classified as Cepheids and 140 784 as RR Lyrae stars) distributed throughout the sky. The sample includes variables in 87 globular clusters and 14 dwarf galaxies (the Magellanic Clouds, 5 classical and 7 ultra-faint dwarfs). To the best of our knowledge, as of 25 April 2018, the variability of 50 570 of these sources (350 Cepheids and 50 220 RR Lyrae stars) has not been reported before in the literature, therefore they are likely 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 3738 fundamental-mode classical Cepheids with periods shorter than 6.3 days.
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.
Gaia Data Release 2 Roelens, M.; Eyer, L.; Mowlavi, N. ...
Astronomy and astrophysics (Berlin),
12/2018, Letnik:
620
Journal Article
Recenzirano
Odprti dostop
Aims. We describe the methods used and the analysis performed in the frame of the Gaia data processing activities to produce the Gaia Data Release 2 (DR2) sample candidates with short-timescale ...variability together with associated parameters. Methods. The Gaia DR2 sample of candidates with short-timescale variability results from the investigation of the first 22 months of Gaia G per-CCD, GBP, and GRP photometry for a subsample of sources at the Gaia faint end (G ~ 16.5−20 mag). For this first short-timescale variability search exploiting Gaia data, we limited ourselves to the case of suspected rapid periodic variability. Our study combines fast-variability detection through variogram analysis, a high-frequency search by means of least-squares periodograms, and an empirical selection based on the investigation of specific sources seen through the Gaia eyes (e.g., known variables or visually identified objects with peculiar features in their light curves). The progressive definition, improvement, and validation of this selection criterion also benefited from supplementary ground-based photometric monitoring of a few tens of preliminary candidates with short-timescale variability, performed at the Flemish Mercator telescope in La Palma (Canary Islands, Spain) between August and November 2017. Results. As part of Gaia DR2, we publish a list of 3018 candidates with short-timescale variability, spread throughout the sky, with a false-positive rate of up to 10–20% in the Magellanic Clouds, and a more significant but justifiable contamination from longer-period variables between 19% and 50%, depending on the area of the sky. Although its completeness is limited to about 0.05%, this first sample of Gaia short-timescale variables recovers some very interesting known short-period variables, such as post-common envelope binaries or cataclysmic variables, and brings to light some fascinating, newly discovered variable sources. In the perspective of future Gaia data releases, several improvements of the short-timescale variability processing are considered, by enhancing the existing variogram and period-search algorithms or by classifying the identified variability candidates. Nonetheless, the encouraging outcome of our Gaia DR2 analysis demonstrates the power of this mission for such fast-variability studies, and opens great perspectives for this domain of astrophysics.
Gaia Data Release 2 Mowlavi, N.; Lecoeur-Taïbi, I.; Lebzelter, T. ...
Astronomy and astrophysics (Berlin),
10/2018, Letnik:
618
Journal Article
Recenzirano
Odprti dostop
Context. Gaia Data Release 2 (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, GBP, and GRP 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. Aims. We describe this first Gaia catalogue of LPV candidates, give an overview of its content, and present various validation checks. Methods. Various samples of LPVs were used to validate the catalogue: a sample of well-studied very bright LPVs with light curves from the American Association of Variable Star Observers that are partly contemporaneous with Gaia light curves, a sample of Gaia LPV candidates with good parallaxes, the All-Sky Automated Survey for Supernovae catalogue of LPVs, and the Optical Gravitational Lensing Experiment (OGLE) catalogues of LPVs towards the Magellanic Clouds and the Galactic bulge. Results. 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. Conclusions. 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.
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 2 Clementini, G.; Ripepi, V.; Molinaro, R. ...
Astronomy and astrophysics (Berlin),
02/2019, Letnik:
622
Journal Article
Recenzirano
Odprti dostop
Context.
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.
Aims.
The ...Specific Objects 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
multi-band (
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.
Methods.
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
).
Results.
Multi-band time-series photometry and characterisation by the SOS Cep&RRL pipeline are published in
Gaia
DR2 for 150 359 such variables (9575 classified as Cepheids and 140 784 as RR Lyrae stars) distributed throughout the sky. The sample includes variables in 87 globular clusters and 14 dwarf galaxies (the Magellanic Clouds, 5 classical and 7 ultra-faint dwarfs). To the best of our knowledge, as of 25 April 2018, the variability of 50 570 of these sources (350 Cepheids and 50 220 RR Lyrae stars) has not been reported before in the literature, therefore they are likely 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 3738 fundamental-mode classical Cepheids with periods shorter than 6.3 days.
Gaia Data Release 3 Lebzelter, T.; Mowlavi, N.; Lecoeur-Taibi, I. ...
Astronomy and astrophysics (Berlin),
06/2023, Letnik:
674
Journal Article
Recenzirano
Odprti dostop
Context.
The third
Gaia
Data Release covers 34 months of data and includes the second
Gaia
catalogue of long-period variables (LPVs), with
G
variability amplitudes larger than 0.1 mag (5–95% quantile ...range).
Aims.
The paper describes the production and content of the second
Gaia
catalogue of LPVs and the methods we used to compute the published variability parameters and identify C-star candidates.
Methods.
We applied various filtering criteria to minimise contamination from variable star types other than LPVs. The period and amplitude of the detected variability were derived from model fits to the
G
-band light curve wherever possible. C stars were identified using their molecular signature in the low-resolution RP spectra.
Results.
The catalogue contains 1 720 558 LPV candidates, including 392 240 stars with published periods (ranging from 35 to ∼1000 days) and 546 468 stars classified as C-star candidates. Comparison with literature data (OGLE and ASAS-SN) leads to an estimated completeness of 80%. The recovery rate is about 90% for the most regular stars (typically miras) and 60% for SRVs and irregular stars. At the same time, the number of known LPVs is increased by a factor of 6 with respect to literature data for amplitudes larger than 0.1 mag in
G
, and the contamination is estimated to be below 2%. Our C-star classification, based on solid theoretical arguments, is consistent with spectroscopically identified C stars in the literature. Caution must be taken in crowded regions, however, where the signal-ro-noise ratio of the RP spectra can become very low, or if the source is reddened by some kind of extinction. The quality and potential of the catalogue are illustrated by presenting and discussing LPVs in the solar neighbourhood, in globular clusters, and in galaxies of the Local Group.
Conclusions.
This is the largest all-sky LPVs catalogue to date. The photometric depth reaches
G
= 20 mag. This is a unique dataset for research into the late stages of stellar evolution.
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