arXiv subjects

G. Jevardat de Fombelle

Publications and source records attributed to G. Jevardat de Fombelle.

At least 19 recordsLinked to original sources

arXiv2026

Gaia method paper: an algorithm to detect flare events in Gaia time-series

The third Gaia data release (GDR3) includes the gdr3_rotmod catalogue of 474026 stars with variability that is attributed to magnetic activity analogous to that observed in the Sun, arising from rotational modulation induced by spots and faculae. These stars are therefore expected to exhibit flaring activity driven by magnetic reconnection processes. We aim to demonstrate that stellar flares can be reliably identified and characterised in the sparsely sampled \gaia\ photometric time series. We developed and validated a dedicated flare-detection pipeline that exploits the simultaneous multi-band photometry in the $G$, $G_{\rm BP}$, and $G_{\rm RP}$ bands. The algorithm identifies outliers associated with a concurrent increase in brightness and blueing of the stellar colour, and applies consistency criteria to distinguish genuine flare events from instrumental or calibration artefacts. Applying this method to the gdr3_rotmod catalogue, we detect 3217 flares occurring on 2818 stars out of 474026 analysed sources. All events are provided in a dedicated catalogue together with their photometric amplitudes. For a subset of 348 flares, we estimate an effective temperature using a black-body approximation, and we identify 29 hyper-flares with amplitudes $A(G)\ge0.75$ mag, which occur preferentially in M dwarfs. Despite the sparse temporal sampling of Gaia, our results demonstrate that its multi-band photometry and spectrophotometric information enable the robust detection of flares and the basic characterisation of their properties across an all-sky stellar sample. This work establishes the methodological foundation for future Gaia flare catalogues and provides a homogeneous, complementary view of stellar flaring activity alongside high-cadence missions such as Kepler and TESS.

astro-ph.SR↗

arXiv2025

The Variable Universe with the Gaia mission and AI methods

The Gaia mission has observed over 2 billion stars repeatedly across the entire sky over 10 years, revealing the many astronomical objects that vary on human timescales from seconds to years. Its repeated astrometric, photometric, spectrophotometric and spectroscopic measurements create an unprecedented dataset to probe the variable celestial sources down to G ~ 21 mag. To extract meaningful results from these many time series for so many sources, we have used machine learning techniques for crossmatching, variability detection, and variability classification. This approach has now led to the largest catalogue of classified variable sources ever produced over the entire celestial sphere.

astro-ph.IM↗

arXiv2025

Learning novel representations of variable sources from multi-modal $\textit{Gaia}$ data via autoencoders

Gaia Data Release 3 (DR3) published for the first time epoch photometry, BP/RP (XP) low-resolution mean spectra, and supervised classification results for millions of variable sources. This extensive dataset offers a unique opportunity to study their variability by combining multiple Gaia data products. In preparation for DR4, we propose and evaluate a machine learning methodology capable of ingesting multiple Gaia data products to achieve an unsupervised classification of stellar and quasar variability. A dataset of 4 million Gaia DR3 sources is used to train three variational autoencoders (VAE), which are artificial neural networks (ANNs) designed for data compression and generation. One VAE is trained on Gaia XP low-resolution spectra, another on a novel approach based on the distribution of magnitude differences in the Gaia G band, and the third on folded Gaia G band light curves. Each Gaia source is compressed into 15 numbers, representing the coordinates in a 15-dimensional latent space generated by combining the outputs of these three models. The learned latent representation produced by the ANN effectively distinguishes between the main variability classes present in Gaia DR3, as demonstrated through both supervised and unsupervised classification analysis of the latent space. The results highlight a strong synergy between light curves and low-resolution spectral data, emphasising the benefits of combining the different Gaia data products. A two-dimensional projection of the latent variables reveals numerous overdensities, most of which strongly correlate with astrophysical properties, showing the potential of this latent space for astrophysical discovery. We show that the properties of our novel latent representation make it highly valuable for variability analysis tasks, including classification, clustering and outlier detection.

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arXiv2023

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

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 (RV) in DR4, this Focused Product Release (FPR) provides RV time series for a selection of LPVs with high-quality observations. We describe the production and content of the Gaia catalog of LPV RV time series, and the methods used to compute variability parameters published in the Gaia FPR. Starting from the DR3 LPVs catalog, we applied filters to construct a sample of sources with high-quality RV measurements. We modeled their RV and photometric time series to derive their periods and amplitudes, and further refined the sample by requiring compatibility between the RV period and at least one of the $G$, $G_{\rm BP}$, or $G_{\rm RP}$ photometric periods. The catalog includes RV time series and variability parameters for 9\,614 sources in the magnitude range $6\lesssim G/{\rm mag}\lesssim 14$, including a flagged top-quality subsample of 6\,093 stars whose RV periods are fully compatible with the values derived from the $G$, $G_{\rm BP}$, and $G_{\rm RP}$ photometric time series. The RV time series contain a mean of 24 measurements per source taken unevenly over a duration of about three years. We identify the great most sources (88%) as genuine LPVs, with about half of them showing a pulsation period and the other half displaying a long secondary period. The remaining 12% consists of candidate ellipsoidal binaries. Quality checks against RVs available in the literature show excellent agreement. We provide illustrative examples and cautionary remarks. The publication of RV time series for almost 10\,000 LPVs 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 (abridged)

astro-ph.SR↗

arXiv2023

Gaia Data Release 3: Gaia scan-angle dependent signals and spurious periods

Context: Gaia DR3 time series data may contain spurious signals related to the time-dependent scan angle. Aims: We aim to explain the origin of scan-angle dependent signals and how they can lead to spurious periods, provide statistics to identify them in the data, and suggest how to deal with them in Gaia DR3 data and in future releases. Methods: Using real Gaia data, alongside numerical and analytical models, we visualise and explain the features observed in the data. Results: We demonstrated with Gaia data that source structure (multiplicity or extendedness) or pollution from close-by bright objects can cause biases in the image parameter determination from which photometric, astrometric and (indirectly) radial velocity time series are derived. These biases are a function of the time-dependent scan direction of the instrument and thus can introduce scan-angle dependent signals, which in turn can result in specific spurious periodic signals. Numerical simulations qualitatively reproduce the general structure observed in the spurious period and spatial distribution of photometry and astrometry. A variety of statistics allows for identification of affected sources. Conclusions: The origin of the scan-angle dependent signals and subsequent spurious periods is well-understood and is in majority caused by fixed-orientation optical pairs with separation <0.5" (amongst which binaries with P>>5y) and (cores of) distant galaxies. Though the majority of sources with affected derived parameters have been filtered out from the Gaia archive, there remain Gaia DR3 data that should be treated with care (e.g. gaia_source was untouched). Finally, the various statistics discussed in the paper can not only be used to identify and filter affected sources, but alternatively reveal new information about them not available through other means, especially in terms of binarity on sub-arcsecond scale.

astro-ph.IM↗

arXiv2022

Gaia Data Release 3. The first Gaia catalogue of eclipsing binary candidates

We present the first Gaia catalogue of eclipsing binary candidates released in Gaia DR3, describe its content, provide tips for its usage, estimate its quality, and show illustrative samples. The catalogue contains 2,184,477 sources with G magnitudes up to 20 mag. Candidate selection is based on the results of variable object classification performed within the Gaia Data Processing and Analysis Consortium, further filtered using eclipsing binary-tailored criteria based on the G light curves. To find the orbital period, a large ensemble of trial periods is first acquired using three distinct period search methods applied to the cleaned G light curve. The G light curve is then modelled with up-to two Gaussians and a cosine for each trial period. The best combination of orbital period and geometric model is finally selected using Bayesian model comparison based on the BIC. A global ranking metric is provided to rank the quality of the chosen model between sources. The catalogue is restricted to orbital periods larger than 0.2 days. About 530,000 of the candidates are classified as eclipsing binaries in the literature as well, out of ~600,000 available crossmatches, and 93% of them have published periods compatible with the Gaia periods. Catalogue completeness is estimated to be between 25% and 50%, depending on the sky region, relative to the OGLE4 catalogues of eclipsing binaries towards the Galactic Bulge and the Magellanic Clouds. The analysis of an illustrative sample of ~400,000 candidates with significant parallaxes shows properties in the observational HR diagram as expected for eclipsing binaries. The subsequent analysis of a sub-sample of detached bright candidates provides further hints for the exploitation of the catalogue. The orbital periods, light curve model parameters, and global rankings are all published in the catalogue with their related uncertainties where applicable.

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arXiv2022

Gaia Data Release 3: Microlensing Events from All Over the Sky

Context: One of the rarest types of variability is the phenomenon of gravitational microlensing, a transient brightening of a background star due to an intervening lensing object. Microlensing is a powerful tool in studying the invisible or otherwise undetectable populations in the Milky Way, including planets and black holes. Aims: We describe the first Gaia catalogue of microlensing event candidates, give an overview of its content and discuss its validation. Methods: The catalogue of Gaia microlensing events is composed by analysing the light curves of around 2 billion sources of Gaia Data Release 3 from all over the sky covering 34 months between 2014 and 2017. Results: We present 363 Gaia microlensing events and discuss their properties. Ninety events were never reported before and were not discovered by other surveys. The contamination of the catalogue is assessed to 0.6-1.7%.

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arXiv2022

Gaia Data Release 3: The second Gaia catalogue of Long-Period Variable candidates

The third Gaia Data Release, covering 34 months of data, includes the second Gaia catalogue of long-period variables (LPVs), with G variability amplitudes larger than 0.1 mag (5-95% quantile range). The paper describes the production and content of this catalogue, and the methods used to compute the published variability parameters and identify C-star candidates. We applied various filtering criteria to minimise contamination by other kinds of variables. The variability parameters, period and amplitude, were derived from model fits to the G-band light curves, wherever possible. C stars were identified using their molecular signature in the low-resolution RP spectra. The catalogue contains 1 720 558 LPV candidates, including 392 240 stars with published periods (ranging from 35 to1000 days) and 546 468 stars classified as C-stars candidates. Comparison with literature data (OGLE and ASAS-SN) leads to an estimated 80% of completeness. The recovery rate is about 90% for the most regular stars (typically Miras) and 60% for semi-regular and irregular ones. At the same time, the number of known LPVs is increased by a large factor with respect to the literature data, especially in crowded regions, and the contamination is estimated to be below two percents. Our C-star classification, based on solid theoretical arguments, is consistent with spectroscopically identified C stars in the literature. Caution must however be taken if the S/N ratio is small, in crowded regions 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. This is the largest all-sky catalogue of LPVs to date with a photometric depth down to G=20 mag, providing a unique data set for research on late stages of stellar evolution.

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arXiv2022

Gaia Data Release 3: Summary of the content and survey properties

We present the third data release of the European Space Agency's Gaia mission, GDR3. The GDR3 catalogue is the outcome of the processing of raw data collected with the Gaia instruments during the first 34 months of the mission by the Gaia Data Processing and Analysis Consortium. The GDR3 catalogue contains the same source list, celestial positions, proper motions, parallaxes, and broad band photometry in the G, G$_{BP}$, and G$_{RP}$ pass-bands already present in the Early Third Data Release. GDR3 introduces an impressive wealth of new data products. More than 33 million objects in the ranges $G_{rvs} < 14$ and $3100 <T_{eff} <14500 $, have new determinations of their mean radial velocities based on data collected by Gaia. We provide G$_{rvs}$ magnitudes for most sources with radial velocities, and a line broadening parameter is listed for a subset of these. Mean Gaia spectra are made available to the community. The GDR3 catalogue includes about 1 million mean spectra from the radial velocity spectrometer, and about 220 million low-resolution blue and red prism photometer BPRP mean spectra. The results of the analysis of epoch photometry are provided for some 10 million sources across 24 variability types. GDR3 includes astrophysical parameters and source class probabilities for about 470 million and 1500 million sources, respectively, including stars, galaxies, and quasars. Orbital elements and trend parameters are provided for some $800\,000$ astrometric, spectroscopic and eclipsing binaries. More than $150\,000$ Solar System objects, including new discoveries, with preliminary orbital solutions and individual epoch observations are part of this release. Reflectance spectra derived from the epoch BPRP spectral data are published for about 60\,000 asteroids. Finally, an additional data set is provided, namely the Gaia Andromeda Photometric Survey (abridged)

astro-ph.GA↗

arXiv2022

Gaia Data Release 3: Cross-match of Gaia sources with variable objects from the literature

Context. In the current ever increasing data volumes of astronomical surveys, automated methods are essential. Objects of known classes from the literature are necessary for training supervised machine learning algorithms, as well as for verification/validation of their results. Aims.The primary goal of this work is to provide a comprehensive data set of known variable objects from the literature cross-matched with \textit{Gaia}~DR3 sources, including a large number of both variability types and representatives, in order to cover as much as possible sky regions and magnitude ranges relevant to each class. In addition, non-variable objects from selected surveys are targeted to probe their variability in \textit{Gaia} and possible use as standards. This data set can be the base for a training set applicable in variability detection, classification, and validation. MethodsA statistical method that employed both astrometry (position and proper motion) and photometry (mean magnitude) was applied to selected literature catalogues in order to identify the correct counterparts of the known objects in the \textit{Gaia} data. The cross-match strategy was adapted to the properties of each catalogue and the verification of results excluded dubious matches. Results.Our catalogue gathers 7\,841\,723 \textit{Gaia} sources among which 1.2~million non-variable objects and 1.7~million galaxies, in addition to 4.9~million variable sources representing over 100~variability (sub)types. Conclusions.This data set served the requirements of \textit{Gaia}'s variability pipeline for its third data release (DR3), from classifier training to result validation, and it is expected to be a useful resource for the scientific community that is interested in the analysis of variability in the \textit{Gaia} data and other surveys.

astro-ph.IM↗

arXiv2022

Gaia DR3: Specific processing and validation of all-sky RR Lyrae and Cepheid stars -- The RR Lyrae sample

Gaia DR3 publishes a catalogue of full-sky RR Lyrae stars (RRLs) observed during the initial 34 months of science operations, that were processed through the Specific Object Study (SOS) pipeline for Cepheids and RRLs (SOS Cep&RRL) observed by Gaia. The SOS Cep&RRL validation of DR3 candidate RRLs relies on tools that include the Period (P) G-amplitude diagram and the P-phi21 and -phi31 parameters of the G light curve Fourier decomposition, based on a sample of bona fide known RRLs (Gold Sample). The SOS processing led to a catalogue of 271779 RRLs listed in the vari_rrlyrae table of DR3. By dropping sources that clearly are contaminants, or have an uncertain classification we produce the final catalogue of SOS-confirmed DR3 RRLs containing 270905 sources (174947 fundamental mode, 93952 first overtone and 2006 double-mode RRLs) confirmed and fully characterised by the SOS Cep&RRL pipeline. They are distributed all over the sky, including 95 globular clusters and 25 Milky Way companions. RVS time series radial velocities are also published for 1096 RRLs and 799 Cepheids. Of the 270905 DR3 RRLs, 200294 are already known in the literature and 70611 are, to the best of our knowledge, new discoveries by Gaia. An estimate of the interstellar absorption is published for 142660 fundamental-mode RRLs from a relation based on the G-band amplitude and the pulsation period. Metallicities derived from the Periods and the phi31 Fourier parameters of the G-light curves are also released for 133559 RRLs. The final Gaia DR3 catalogue of confirmed RRLs almost doubles the DR2 RRLs catalogue. An increase of statistical significance, a better characterization of the RRLs pulsational and astrophysical parameters, and the improved astrometry published with Gaia EDR3, make the SOS Cep&RRL DR3 sample, the largest, most homogeneous and parameter-rich catalogue of All-Sky RRLs published so far.

astro-ph.SR↗

arXiv2022

Gaia DR3: Specific processing and validation of all-sky RR Lyrae and Cepheid stars -- The Cepheid sample

Context. Cepheids are pulsating stars that play a crucial role in several astrophysical contexts. Among the different types, the Classical Cepheids are fundamental tools for the calibration of the extragalactic distance ladder. They are also powerful stellar population tracers in the context of Galactic studies. The Gaia Third Data Release (DR3) publishes improved data on Cepheids collected during the initial 34 months of operations. Aims. We present the Gaia DR3 catalogue of Cepheids of all types, obtained through the analysis carried out with the Specific Object Study (SOS) Cep&RRL pipeline. Methods. We discuss the procedures adopted to clean the Cepheid sample from spurious objects, to validate the results, and to re-classify sources with a wrong outcome from the SOS Cep&RRL pipeline. Results. The Gaia DR3 includes multi-band time-series photometry and characterisation by the SOS Cep&RRL pipeline for a sample of 15,006 Cepheids of all types. The sample includes 4,663, 4,616, 321 and 185 pulsators, distributed in the LMC, SMC, M31 and M33, respectively, as well as 5 221 objects in the remaining All Sky sub-region which includes stars in the MW field/clusters and in a number of small satellites of our Galaxy. Among this sample, 327 objects were known as variable stars in the literature but with a different classification, while, to the best of our knowledge, 474 stars have not been reported before to be variable stars and therefore they likely are new Cepheids discovered by Gaia.

astro-ph.SR↗

arXiv2022

Gaia Data Release 3. Summary of the variability processing and analysis

Context. Gaia has been in operations since 2014. The third Gaia data release expands from the early data release (EDR3) in 2020 by providing 34 months of multi-epoch observations that allowed us to probe, characterise and classify systematically celestial variable phenomena. Aims. We present a summary of the variability processing and analysis of the photometric and spectroscopic time series of 1.8 billion sources done 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, GBP, and GRP 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/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 sub-types of variable objects. For 11 variable types, additional specific object parameters are published. An overview of the estimated completeness and contamination of most variability classes is provided. Conclusions. Thanks to Gaia we present the largest whole-sky variability analysis based on coherent photometric, astrometric, and spectroscopic data. Later Gaia data releases will more than double the span of time series and the number of observations, thus allowing for an even richer catalogue in the future.

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arXiv2022

Gaia Data Release 3: The Gaia Andromeda Photometric Survey

Context. As part of Gaia Data Release 3 (Gaia DR3), epoch photometry has been released for 1.2 million sources centred on M31. This is a taster for Gaia Data Release 4 where all the epoch photometry will be released. Aims. In this paper the content of the Gaia Andromeda Photometric Survey is described, including statistics to assess the quality of the data. Known issues with the photometry are also outlined. Methods. Methods are given to improve interpretation of the photometry, in particular, a method for error renormalization. Also, use of correlations between the three photometric passbands allows clearer identification of variables that is not affected by false detections caused by systematic effects. Results. The Gaia Andromeda Photometric Survey presents a unique opportunity to look at Gaia epoch photometry that has not been preselected due to variability. This allows investigations to be carried out that can be applied to the rest of the sky using the mean source results. Additionally scientific studies of variability can be carried out on M31 and the Milky Way in general.

astro-ph.IM↗

arXiv2021

Gaia Early Data Release 3: Summary of the contents and survey properties

We present the early installment of the third Gaia data release, Gaia EDR3, consisting of astrometry and photometry for 1.8 billion sources brighter than magnitude 21, complemented with the list of radial velocities from Gaia DR2. Gaia EDR3 contains celestial positions and the apparent brightness in G for approximately 1.8 billion sources. For 1.5 billion of those sources, parallaxes, proper motions, and the (G_BP-G_RP) colour are also available. The passbands for G, G_BP, and G_RP are provided as part of the release. For ease of use, the 7 million radial velocities from Gaia DR2 are included in this release, after the removal of a small number of spurious values. New radial velocities will appear as part of Gaia DR3. Finally, Gaia EDR3 represents an updated materialisation of the celestial reference frame (CRF) in the optical, the Gaia-CRF3, which is based solely on extragalactic sources. The creation of the source list for Gaia EDR3 includes enhancements that make it more robust with respect to high proper motion stars, and the disturbing effects of spurious and partially resolved sources. The source list is largely the same as that for Gaia DR2, but it does feature new sources and there are some notable changes. The source list will not change for Gaia DR3. Gaia EDR3 represents a significant advance over Gaia DR2, with parallax precisions increased by 30 percent, proper motion precisions increased by a factor of 2, and the systematic errors in the astrometry suppressed by 30--40 percent for the parallaxes and by a factor ~2.5 for the proper motions. The photometry also features increased precision, but above all much better homogeneity across colour, magnitude, and celestial position. A single passband for G, G_BP, and G_RP is valid over the entire magnitude and colour range, with no systematics above the 1 percent level.

astro-ph.GA↗

arXiv2021

Large-amplitude variables in Gaia Data Release 2. Multi-band variability characterization

The second data release (DR2) of Gaia provides mean photometry in three bands for $\sim$1.4 billion sources, but light curves and variability properties are available for only $\sim$0.5 million of them. Here, we provide a census of large-amplitude variables with amplitudes larger than $\sim$0.2 mag in the $G$ band for objects with mean brightnesses between 5.5 and 19 mag. To achieve this, we rely on variability amplitude proxies in $G$, $G_{BP}$ and $G_{RP}$ computed from the uncertainties on the magnitudes published in DR2. We then apply successive filters to identify two subsets containing respectively sources with reliable mean $G_{BP}$ and $G_{RP}$ (for studies using colours) and sources having compatible amplitude proxies in $G$, $G_{BP}$ and $G_{RP}$ (for multi-band variability studies). The full catalogue gathers $23\,315\,874$ large-amplitude variable candidates, and the two subsets with increased levels of purity contain respectively $1\,148\,861$ and $618\,966$ sources. A multi-band variability analysis of the catalogue shows that different types of variable stars can be globally categorized in four groups according to their colour and blue-to-red amplitude ratios as determined from the $G$, $G_{BP}$ and $G_{RP}$ amplitude proxies. The catalogue constitutes the first census of Gaia large-amplitude variable candidates, extracted from the public DR2 archive. The overview presented here illustrates the added-value of the mission for multi-band variability studies even at this stage when epoch photometry is not yet available for all sources. (Abridged abstract)

astro-ph.SR↗

arXiv2019

Gaia's revolution in stellar variability

Stellar variability studies are now reaching a completely new level thanks to ESA's Gaia mission, which enables us to locate many variable stars in the Hertzsprung-Russell diagram and determine the various instability strips/bands. Furthermore, this mission also allows us to detect, characterise and classify many millions of new variable stars thanks to its very unique nearly simultaneous multi-epoch survey with different instruments (photometer, spectro-photometer, radial velocity spectrometer). An overview of what can be found in literature in terms of mostly data products by the Gaia consortium is given. This concerns the various catalogues of variable stars derived from the Gaia time series and also the location and motion of variable stars in the observational Hertzsprung-Russell diagram. In addition, we provide a list of a few thousands of variable white dwarf candidates derived from the DR2 published data, among them probably many hundreds of new pulsating white dwarfs. On a very different topic, we also show how Gaia allows us to reveal the 3D structures of and around the Milky Way thanks to the RR Lyrae stars.

astro-ph.SR↗

arXiv2019

Gaia Data Release 2: All-sky classification of high-amplitude pulsating stars

More than half a million of the 1.69 billion sources in Gaia Data Release 2 (DR2) are published with photometric time series that exhibit light variations during the 22 months of observation. An all-sky classification of common high-amplitude pulsators (Cepheids, long-period variables, Delta Scuti / SX Phoenicis, and RR Lyrae stars) is provided for stars with brightness variations greater than 0.1 mag in G band. A semi-supervised classification approach was employed, firstly training multi-stage random forest classifiers with sources of known types in the literature, followed by a preliminary classification of the Gaia data and a second training phase that included a selection of the first classification results to improve the representation of some classes, before the improved classifiers were applied to the Gaia data. Dedicated validation classifiers were used to reduce the level of contamination in the published results. A relevant fraction of objects were not yet sufficiently sampled for reliable Fourier series decomposition, consequently classifiers were based on features derived from statistics of photometric time series in the G, BP, and RP bands, as well as from some astrometric parameters. The published classification results include 195,780 RR Lyrae stars, 150,757 long-period variables, 8550 Cepheids, and 8882 Delta Scuti / SX Phoenicis stars. All of these results represent candidates whose completeness and contamination are described as a function of variability type and classification reliability. Results are expressed in terms of class labels and classification scores, which are available in the vari_classifier_result table of the Gaia archive.

astro-ph.SR↗