arXiv subjects

M. Roelens

Publications and source records attributed to M. Roelens.

8 recordsLinked to original sources

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.

astro-ph.SR↗

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↗

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↗

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: The first Gaia catalogue of long-period variable candidates

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

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↗

arXiv2017

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

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

astro-ph.IM↗

arXiv2016

Vetting Galactic Leavitt Law Calibrators using Radial Velocities: On the Variability, Binarity, and Possible Parallax Error of 19 Long-period Cepheids

We investigate the radial velocity (RV) variability and spectroscopic binarity of 19 Galactic long-period ($P_{\rm{puls}} \gtrsim 10$ d) classical Cepheid variable stars whose trigonometric parallaxes are being measured using the Hubble Space Telescope and Gaia. Our primary objective is to constrain possible parallax error due to undetected orbital motion. Using $>1600$ high-precision RVs measured between 2011 and 2016, we find no indication of orbital motion on $\lesssim 5$ yr timescales for 18 Cepheids and determine upper limits on allowed configurations for a range of input orbital periods. The results constrain the unsigned parallax error due to orbital motion to $< 2 \%$ for 16 stars, and $< 4 \%$ for 18. We improve the orbital solution of the known binary YZ Carinae and show that the astrometric model must take into account orbital motion to avoid significant error ($\sim \pm 100 μ$arcsec). We further investigate long-timescale ($P_{\rm{orb}} > 10$ yr) variations in pulsation-averaged velocity $v_γ$ via a template fitting approach using both new and literature RVs. We discover the spectroscopic binarity of XZ Car and CD Cyg, find first tentative evidence for AQ Car, and reveal KN Cen's orbital signature. Further (mostly tentative) evidence of time-variable $v_γ$ is found for SS CMa, VY Car, SZ Cyg, and X Pup. We briefly discuss considerations regarding a vetting process of Galactic Leavitt law calibrators and show that light contributions by companions are insignificant for most distance scale applications.

astro-ph.SR↗