arXiv subjects

M. Riello

Publications and source records attributed to M. Riello.

At least 19 recordsLinked to original sources

arXiv2023

Metal-poor stars with disc-like orbits. Traces of the Galactic Disc at very early epochs?

We use photometric metallicity estimates for about 700000 stars in the surroundings of the Sun, with very accurate distances and 3-D motions measures from Gaia DR3, to explore the properties of the metal-poor (-2.0<[Fe/H]<= -1.5; MP) and very metal-poor ([Fe/H]<= -2.0; VMP) stars with disc kinematics in the sample. We confirm the presence of a significant fraction of MP and VMP stars with disc-like orbits and that prograde orbits are prevalent among them, with prograde to retrograde ratio P/R ~3. We highlight for the first time a statistically significant difference in the distribution of the Z-component of the angular momentum (L_Z) and orbital eccentricity between prograde and retrograde disc-like MP stars. The same kind of difference is found also in the VMP subsample, albeit at a much lower level of statistical significance, likely due to the small sample size. We show that prograde disc-like MP and VMP stars display an additional component of the |L_Z| distribution with respect to their retrograde counterpart. This component is at higher |L_Z| with respect to the main peak of the distribution, possibly hinting at the presence of a pristine prograde disc in the Milky Way. This hypothesis is supported by the results of the analysis of a large sub-sample dominated by stars born in-situ. Also in this case the prevalence of prograde stars is clearly detected at [Fe/H]<= -1.5 and their |L_Z| distribution is more skewed toward high |L_Z| values than their retrograde counterpart. This suggests that the seed of what will eventually evolve into the main disc components of the Milky Way may have been already in place in the earliest phases of the Galaxy assembly.

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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↗

arXiv2023

Gaia Data Release 3: The Galaxy in your preferred colours. Synthetic photometry from Gaia low-resolution spectra

Gaia Data Release 3 provides novel flux-calibrated low-resolution spectrophotometry for about 220 million sources in the wavelength range 330nm - 1050nm (XP spectra). Synthetic photometry directly tied to a flux in physical units can be obtained from these spectra for any passband fully enclosed in this wavelength range. We describe how synthetic photometry can be obtained from XP spectra, illustrating the performance that can be achieved under a range of different conditions - for example passband width and wavelength range - as well as the limits and the problems affecting it. Existing top-quality photometry can be reproduced within a few per cent over a wide range of magnitudes and colour, for wide and medium bands, and with up to millimag accuracy when synthetic photometry is standardised with respect to these external sources. Some examples of potential scientific application are presented, including the detection of multiple populations in globular clusters, the estimation of metallicity extended to the very metal-poor regime, and the classification of white dwarfs. A catalogue providing standardised photometry for ~220 million sources in several wide bands of widely used photometric systems is provided (Gaia Synthetic Photometry Catalogue; GSPC) as well as a catalogue of $\simeq 10^5$ white dwarfs with DA/non-DA classification obtained with a Random Forest algorithm (Gaia Synthetic Photometry Catalogue for White Dwarfs; GSPC-WD).

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arXiv2022

Gaia Data Release 3. Rotational modulation and patterns of colour variations in solar-like variables

The Gaia third Data Release (DR3) presents a catalogue of 474\,026 stars with variability induced by magnetic activity. For each star, the catalogue provides a list of about 70 parameters among which the most important are the stellar rotation period $P$, the photometric amplitude $A$ of the rotational signal and the Pearson Correlation Coefficient $r_0$ between brightness and magnitude variations. The Specific Objects Study (SOS) pipeline, developed to characterise magnetically active stars with Gaia Data, has been described in the paper accompanying the Gaia second Data Release. Here we describe the changes made to the pipeline and a new method developed to analyze Gaia time-series and to reveal spurious signals induced by instrumental effects or by the peculiar nature of the investigated stellar source. The period-amplitude diagram obtained with the DR3 data confirms the bimodal distribution of fast rotating stars seen in the DR2 release. The DR3 data permitted, for the first time, to analyze the patterns of magnitude-color variations for thousands of magnetically active stars. The measured $r_0$ values are tightly correlated with the stars position in the period-amplitude diagram. The relationship between the $P$, $A$ and $r_0$ parameters inferred for thousands of stars could be very useful to improve the understanding of stellar magnetic fields and to improve theoretical models. The method developed to reveal the spurious signals can be applied to each of the released Gaia photometric time-series and can be exploited by anyone interested in working directly with Gaia time-series.

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arXiv2022

Gaia Data Release 3: Processing and validation of BP/RP low-resolution spectral data

(Abridged) Blue (BP) and Red (RP) Photometer low-resolution spectral data is one of the exciting new products in Gaia Data Release 3 (Gaia DR3). We calibrate about 65 billion individual transit spectra onto the same mean BP/RP instrument through a series of calibration steps, including background subtraction, calibration of the CCD geometry and an iterative procedure for the calibration of CCD efficiency as well as variations of the line-spread function and dispersion across the focal plane and in time. The calibrated transit spectra are then combined for each source in terms of an expansion into continuous basis functions. Time-averaged mean spectra covering the optical to near-infrared wavelength range [330, 1050] nm are published for approximately 220 million objects. Most of these are brighter than G = 17.65 but some BP/RP spectra are published for sources down to G = 21.43. Their signal- to-noise ratio varies significantly over the wavelength range covered and with magnitude and colour of the observed objects, with sources around G = 15 having S/N above 100 in some wavelength ranges. The top-quality BP/RP spectra are achieved for sources with magnitudes 9 < G < 12, having S/N reaching 1000 in the central part of the RP wavelength range. Scientific validation suggests that the internal calibration was generally successful. However, there is some evidence for imperfect calibrations at the bright end G < 11, where calibrated BP/RP spectra can exhibit systematic flux variations that exceed their estimated flux uncertainties. We also report that due to long-range noise correlations, BP/RP spectra can exhibit wiggles when sampled in pseudo-wavelength.

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arXiv2022

Gaia Data Release 3: External calibration of BP/RP low-resolution spectroscopic data

Context. Gaia Data Release 3 contains astrometry and photometry results for about 1.8 billion sources based on observations collected by the European Space Agency (ESA) Gaia satellite during the first 34 months of its operational phase (the same period covered Gaia early Data Release 3; Gaia EDR3). Low-resolution spectra for 220 million sources are one of the important new data products included in this release. Aims. In this paper, we focus on the external calibration of low-resolution spectroscopic content, describing the input data, algorithms, data processing, and the validation of the results. Particular attention is given to the quality of the data and to a number of features that users may need to take into account to make the best use of the catalogue. Methods. We calibrated an instrument model to relate mean Gaia spectra to the corresponding spectral energy distributions using an extended set of calibrators: this includes modelling of the instrument dispersion relation, transmission, and line spread functions. Optimisation of the model is achieved through total least-squares regression, accounting for errors in Gaia and external spectra. Results. The resulting instrument model can be used for forward modelling of Gaia spectra or for inverse modelling of externally calibrated spectra in absolute flux units. Conclusions. The absolute calibration derived in this paper provides an essential ingredient for users of BP/RP spectra. It allows users to connect BP/RP spectra to absolute fluxes and physical wavelengths.

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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.

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arXiv2021

Internal calibration of Gaia BP/RP low-resolution spectra

The full third Gaia data release will provide the calibrated spectra obtained with the blue and red Gaia slit-less spectrophotometers. The main challenge when facing Gaia spectral calibration is that no lamp spectra or flat fields are available during the mission. Also, the significant size of the line spread function with respect to the dispersion of the prisms produces alien photons contaminating neighbouring positions of the spectra. This makes the calibration special and different from standard approaches. This work gives a detailed description of the internal calibration model to obtain the spectrophotometric data in the Gaia catalogue. The main purpose of the internal calibration is to bring all the epoch spectra onto a common flux and pixel (pseudo-wavelength) scale, taking into account variations over the focal plane and with time, producing a mean spectrum from all the observations of the same source. In order to describe all observations in a common mean flux and pseudo-wavelength scale, we construct a suitable representation of the internally calibrated mean spectra via basis functions and we describe the transformation between non calibrated epoch spectra and calibrated mean spectra via a discrete convolution, parametrising the convolution kernel to recover the relevant coefficients. The model proposed here is able to combine all observations into a mean instrument to allow the comparison of different sources and observations obtained with different instrumental conditions along the mission and the generation of mean spectra from a number of observations of the same source. The output of this model provides the internal mean spectra, not as a sampled function (flux and wavelength), but as a linear combination of basis functions, although sampled spectra can easily be derived from them.

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arXiv2021

Gaia Photometric Science Alerts

Since July 2014, the Gaia mission has been engaged in a high-spatial-resolution, time-resolved, precise, accurate astrometric, and photometric survey of the entire sky. Aims: We present the Gaia Science Alerts project, which has been in operation since 1 June 2016. We describe the system which has been developed to enable the discovery and publication of transient photometric events as seen by Gaia. Methods: We outline the data handling, timings, and performances, and we describe the transient detection algorithms and filtering procedures needed to manage the high false alarm rate. We identify two classes of events: (1) sources which are new to Gaia and (2) Gaia sources which have undergone a significant brightening or fading. Validation of the Gaia transit astrometry and photometry was performed, followed by testing of the source environment to minimise contamination from Solar System objects, bright stars, and fainter near-neighbours. Results: We show that the Gaia Science Alerts project suffers from very low contamination, that is there are very few false-positives. We find that the external completeness for supernovae, $C_E=0.46$, is dominated by the Gaia scanning law and the requirement of detections from both fields-of-view. Where we have two or more scans the internal completeness is $C_I=0.79$ at 3 arcsec or larger from the centres of galaxies, but it drops closer in, especially within 1 arcsec. Conclusions: The per-transit photometry for Gaia transients is precise to 1 per cent at $G=13$, and 3 per cent at $G=19$. The per-transit astrometry is accurate to 55 milliarcseconds when compared to Gaia DR2. The Gaia Science Alerts project is one of the most homogeneous and productive transient surveys in operation, and it is the only survey which covers the whole sky at high spatial resolution (subarcsecond), including the Galactic plane and bulge.

astro-ph.IM↗

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)

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arXiv2020

Gaia Early Data Release 3: Modelling and calibration of Gaia's point and line spread functions

Context: The unprecedented astrometric precision of the Gaia mission relies on accurate estimates of the locations of sources in the Gaia data stream. This is ultimately performed by point spread function (PSF) fitting, which in turn requires an accurate reconstruction of the PSF. Gaia Early Data Release 3 (EDR3) will, for the first time, use a PSF calibration that models several of the strongest dependences, leading to signficantly reduced systematic errors. Aims: We describe the PSF model and calibration pipeline implemented for Gaia EDR3, including an analysis of the calibration results over the 34 months of data. We include a discussion of the limitations of the current pipeline and directions for future releases. This will be of use both to users of Gaia data and as a reference for other precision astrometry missions. Methods: We develop models of the 1D line spread function (LSF) and 2D PSF profiles based on a linear combination of basis components. We fit the models to selected primary sources in independent time ranges, using simple parameterisations for the colour and other dependences. Variation in time is smoothed by merging the independent calibrations in a square root information filter, with resets at certain mission events that induce a discontinuous change in the PSF. Results: The PSF calibration shows strong time and colour dependences that accurately reproduce the varying state of the Gaia astrometric instrument. Analysis of the residuals reveals both the performance and the limitations of the current models and calibration pipeline, and indicates the directions for future development. Conclusions: The PSF modelling and calibration carried out for Gaia EDR3 represents a major step forwards in the data processing and will lead to reduced systematic errors in the core mission data products. Further significant improvements are expected in the future data releases.

astro-ph.IM↗

arXiv2020

Gaia Early Data Release 3: Photometric content and validation

Gaia Early Data Release 3 contains astrometry and photometry results for about 1.8 billion sources based on observations collected by the ESA Gaia satellite during the first 34 months of operations. This paper focuses on the photometric content, describing the input data, the algorithms, the processing, and the validation of the results. Particular attention is given to the quality of the data and to a number of features that users may need to take into account to make the best use of the EDR3 catalogue. The treatment of the BP and RP background has been updated to include a better estimation of the local background, and the detection of crowding effects has been used to exclude affected data from the calibrations. The photometric calibration models have also been updated to account for flux loss over the whole magnitude range. Significant improvements in the modelling and calibration of the point and line spread functions have also helped to reduce a number of instrumental effects that were still present in DR2. EDR3 contains 1.806 billion sources with G-band photometry and 1.540 billion sources with BP and RP photometry. The median uncertainty in the G-band photometry, as measured from the standard deviation of the internally calibrated mean photometry for a given source, is 0.2 mmag at magnitude G=10 to 14, 0.8 mmag at G=17, and 2.6 mmag at G=19. The significant magnitude term found in the Gaia DR2 photometry is no longer visible, and overall there are no trends larger than 1 mmag/mag. Using one passband over the whole colour and magnitude range leaves no systematics above the 1% level in magnitude in any of the bands, and a larger systematic is present for a very small sample of bright and blue sources. A detailed description of the residual systematic effects is provided. Overall the quality of the calibrated mean photometry in EDR3 is superior with respect to DR2 for all bands.

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arXiv2020

Electromagnetic counterparts to gravitational wave events from Gaia

The recent discoveries of gravitational wave events and in one case also its electromagnetic (EM) counterpart allow us to study the Universe in a novel way. The increased sensitivity of the LIGO and Virgo detectors has opened the possibility for regular detections of EM transient events from mergers of stellar remnants. Gravitational wave sources are expected to have sky localisation up to a few hundred square degrees, thus Gaia as an all-sky multi-epoch photometric survey has the potential to be a good tool to search for the EM counterparts. In this paper we study the possibility of detecting EM counterparts to gravitational wave sources using the Gaia Science Alerts system. We develop an extension to current used algorithms to find transients and test its capabilities in discovering candidate transients on a sample of events from the observation periods O1 and O2 of LIGO and Virgo. For the gravitational wave events from the current run O3 we expect that about 16 (25) per cent should fall in sky regions observed by Gaia 7 (10) days after gravitational wave. The new algorithm will provide about 10 candidates per day from the whole sky.

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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. Short-timescale variability processing and analysis

The Gaia DR2 sample of short-timescale variable candidates results from the investigation of the first 22 months of Gaia photometry for a subsample of sources at the Gaia faint end. For this exercise, we limited ourselves to the case of suspected rapid periodic variability. Our study combines fast-variability detection through variogram analysis, high-frequency search by means of least-squares periodograms, and 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 and validation of this selection criterion also benefited from supplementary ground-based photometric monitoring of a few preliminary candidates, performed at the Flemish Mercator telescope (Canary Islands, Spain) between August and November 2017. We publish a list of 3,018 short-timescale variable candidates, spread throughout the sky, with a false-positive rate 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 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.

astro-ph.IM↗

arXiv2018

Gaia Data Release 2: Observational Hertzsprung-Russell diagrams

We highlight the power of the Gaia DR2 in studying many fine structures of the Hertzsprung-Russell diagram (HRD). Gaia allows us to present many different HRDs, depending in particular on stellar population selections. We do not aim here for completeness in terms of types of stars or stellar evolutionary aspects. Instead, we have chosen several illustrative examples. We describe some of the selections that can be made in Gaia DR2 to highlight the main structures of the Gaia HRDs. We select both field and cluster (open and globular) stars, compare the observations with previous classifications and with stellar evolutionary tracks, and we present variations of the Gaia HRD with age, metallicity, and kinematics. Late stages of stellar evolution such as hot subdwarfs, post-AGB stars, planetary nebulae, and white dwarfs are also analysed, as well as low-mass brown dwarf objects. The Gaia HRDs are unprecedented in both precision and coverage of the various Milky Way stellar populations and stellar evolutionary phases. Many fine structures of the HRDs are presented. The clear split of the white dwarf sequence into hydrogen and helium white dwarfs is presented for the first time in an HRD. The relation between kinematics and the HRD is nicely illustrated. Two different populations in a classical kinematic selection of the halo are unambiguously identified in the HRD. Membership and mean parameters for a selected list of open clusters are provided. They allow drawing very detailed cluster sequences, highlighting fine structures, and providing extremely precise empirical isochrones that will lead to more insight in stellar physics. Gaia DR2 demonstrates the potential of combining precise astrometry and photometry for large samples for studies in stellar evolution and stellar population and opens an entire new area for HRD-based studies.

astro-ph.SR↗

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.

astro-ph.SR↗