arXiv subjects

Lorenzo Rimoldini

Publications and source records attributed to Lorenzo Rimoldini.

At least 19 recordsLinked to original sources

arXiv2026

Gaia DR3 Variable White Dwarfs vetted by ZTF

The publications of Gaia DR2 and DR3 have brought major improvements in stellar astrometry and photometry, particularly regarding the description of the white dwarf sequence. Notably, Gaia DR2 enabled the detection of variability in white dwarfs based solely on averaged astrometric and photometric quantities, i.e. the astrometric 5 parameters (positions, proper motion, and parallax) and general photometry properties in the G, BP and RP bands (mean, standard deviation and number of measurements). We identify and classify variable white dwarfs using Gaia DR3 data and Zwicky Transient Facility DR23 observations. The objective is to construct a catalogue of pulsating white dwarf candidates with robust selection criteria. We define a new sample of candidate variable white dwarfs using Gaia DR3 astrometric and photometric data. We cross-match this sample with the ZTF DR23 catalogue and apply a multiband Lomb-Scargle periodogram analysis to detect periodic variability. We then use the OPTICS unsupervised clustering algorithm to to group and classify the confirmed periodic stars. We identify 1423 variable white dwarfs candidates from Gaia DR3, with 864 having ZTF time series. 141 present significant periodicity. We classify these objects into known categories, including ZZ Ceti stars, GW Vir, V777 Her, and white dwarf-main sequence binaries. Our analysis yields several periodic stars, including three ZZ Ceti, 15 GW Vir, one V777 Her, and 24 WD-MS binaries. Furthermore, it reveals a significant population of potentialy variable stars, though without confirmed periodicity. Finally we publish our catalogue of candidate variable white dwarfs including variability status, periodicity, and classification information for the 864 sources with ZTF time series, 519 of them newly identified (including 83 new periodic stars).

astro-ph.SR↗

arXiv2023

Gaia Data Release 3: All-sky classification of 12.4 million variable sources into 25 classes

Gaia DR3 contains 1.8 billion sources with G-band photometry, 1.5 billion of which with BP and RP photometry, complemented by positions on the sky, parallax, and proper motion. The median number of field-of-view transits in the three photometric bands is between 40 and 44 measurements per source and covers 34 months of data collection. We pursue a classification of Galactic and extra-galactic objects that are detected as variable by Gaia across the whole sky. Supervised machine learning (eXtreme Gradient Boosting and Random Forest) was employed to generate multi-class, binary, and meta-classifiers that classified variable objects with photometric time series in the G, BP, and RP bands. Classification results comprise 12.4 million sources (selected from a much larger set of potential variable objects) and include about 9 million variable stars classified into 22 variability types in the Milky Way and nearby galaxies such as the Magellanic Clouds and Andromeda, plus thousands of supernova explosions in distant galaxies, 1 million active galactic nuclei, and almost 2.5 million galaxies. The identification of galaxies was made possible by the artificial variability of extended objects as detected by Gaia, so they were published in the galaxy_candidates table of the Gaia DR3 archive, separate from the classifications of genuine variability (in the vari_classifier_result table). The latter contains 24 variability classes or class groups of periodic and non-periodic variables (pulsating, eclipsing, rotating, eruptive, cataclysmic, stochastic, and microlensing), with amplitudes from a few milli-magnitudes to several magnitudes.

astro-ph.GA↗

arXiv2023

Gaia Data Release 3 Validating the classification of variable Young Stellar Object candidates

Context. The Gaia third Data Release (DR3) presents the first catalogue of full-sky variable Young Stellar Object (YSO) candidates observed by the Gaia space telescope during the initial 34 months of science operations. Aims. Numerous types of variable stars were classified using photometric data collected by Gaia. One of the new classes presented in the Gaia DR3 is the class of YSOs showing brightness variability. We analysed 79 375 sources classified as YSO candidates to validate their young nature and investigate the completeness and purity of the sample. Methods. We cross-matched the Gaia DR3 YSO sample with numerous catalogues from the literature, including YSO catalogues based on optical and infrared data, as well as catalogues of extragalactic sources and Galactic variable stars. YSO catalogues were used to quantify the completeness of the Gaia DR3 YSO sample, while others were inspected to calculate the contamination. Results. Among the 79 375 potential Young Stellar Object candidates published in the Gaia DR3 variable star catalogue, the majority of these objects are distributed along the line of sight of well-known Star Forming Regions and the Galactic mid-plane. We found that the contamination level is well below 1%, while the completeness is also at the percent level, taking into account that the Gaia DR3 YSO sample is based on sources that showed significant variability during the data collection period. The number of sources in our sample that were never catalogued before as YSO candidates is in the order of $\sim$40 000 objects.

astro-ph.SR↗

arXiv2022

Gaia-TESS synergy: Improving the identification of transit candidates

Context: The TESS team periodically issues a new list of transiting exoplanet candidates based on the analysis of the accumulating light curves obtained by the satellite. The list includes the estimated epochs, periods, and durations of the potential transits. As the point spread function (PSF) of TESS is relatively wide, follow-up photometric observations at higher spatial resolution are required in order to exclude apparent transits that are actually blended background eclipsing binaries (BEBs). Aims: The Gaia space mission, with its growing database of epoch photometry and high angular resolution, enables the production of distinct light curves for all sources included in the TESS PSF, up to the limiting magnitude of Gaia. This paper reports the results of an ongoing Gaia-TESS collaboration that uses the Gaia photometry to facilitate the identification of BEB candidates and even to confirm on-target candidates in some cases. Methods: We inspected the Gaia photometry of the individual sources included in the TESS PSF, searching for periodic dimming events compatible with their ephemerides and uncertainties, as published by TESS. The performance of the search depends mainly on the number of Gaia measurements during transit and their precision. Results: Since February 2021, the collaboration has been able to confirm 126 on-target candidates and exclude 124 as BEBs. Since June 2021, when our search methodology matured, we have been able to identify on the order of 5% as on-target candidates and another 5% as BEBs. Conclusions: This synergistic approach is combining the complementary capabilities of two of the astronomical space missions of NASA and ESA. It serves to optimize the process of detecting new planets by making better use of the resources of the astronomical community.

astro-ph.EP↗

arXiv2022

Gaia Data Release 3: The first Gaia catalogue of variable AGN

One of the novelties of the Gaia-DR3 with respect to the previous data releases is the publication of the multiband light curves of about 1 million AGN. The goal of this work was the creation of a catalogue of variable AGN, whose selection was based on Gaia data only. We first present the implementation of the methods to estimate the variability parameters into a specific object study module for AGN. Then we describe the selection procedure that led to the definition of the high-purity variable AGN sample and analyse the properties of the selected sources. We started from a sample of millions of sources, which were identified as AGN candidates by 11 different classifiers based on variability processing. Because the focus was on the variability properties, we first defined some pre-requisites in terms of number of data points and mandatory variability parameters. Then a series of filters was applied using only Gaia data and the Gaia Celestial Reference Frame 3 (Gaia-CRF3) sample as a reference.The resulting Gaia AGN variable sample, named GLEAN, contains about 872000 objects, more than 21000 of which are new identifications. We checked the presence of contaminants by cross-matching the selected sources with a variety of galaxies and stellar catalogues. The completeness of GLEAN with respect to the variable AGN in the last Sloan Digital Sky Survey quasar catalogue is about 47%, while that based on the variable AGN of the Gaia-CRF3 sample is around 51%. From both a comparison with other AGN catalogues and an investigation of possible contaminants, we conclude that purity can be expected to be above 95%. Multiwavelength properties of these sources are investigated. In particular, we estimate that about 4% of them are radio-loud. We finally explore the possibility to evaluate the time lags between the flux variations of the multiple images of strongly lensed quasars, and show one case.

astro-ph.HE↗

arXiv2022

The Detection of Transiting Exoplanets by Gaia

Context: The space telescope Gaia is dedicated mainly to performing high-precision astrometry, but also spectroscopy and epoch photometry which can be used to study various types of photometric variability. One such variability type is exoplanetary transits. The photometric data accumulated so far have finally matured enough to allow the detection of some exoplanets. Aims: In order to fully exploit the scientific potential of Gaia, we search its photometric data for the signatures of exoplanetary transits. Methods: The search relies on a version of the Box-Least-Square (BLS) method, applied to a set of stars prioritized by machine-learning classification methods. An independent photometric validation was obtained using the public full-frame images of TESS. In order to validate the first two candidates, radial-velocity follow-up observations were performed using the spectrograph PEPSI of the Large Binocular Telescope (LBT). Results: The radial-velocity measurements confirm that two of the candidates are indeed hot Jupiters. Thus, they are the first exoplanets detected by Gaia - Gaia-1b and Gaia-2b. Conclusions: Gaia-1b and Gaia-2b demonstrate that the approach presented in this paper is indeed effective. This approach will be used to assemble a set of additional exoplanet candidates, to be released in Gaia third data release, ensuring better fulfillment of the exoplanet detection potential of Gaia.

astro-ph.EP↗

arXiv2020

Empirical completeness assessment of the Gaia DR2, Pan-STARRS 1 and ASAS-SN-II RR Lyrae catalogues

RR Lyrae stars are an important and widely used tracer of the most ancient populations of our Galaxy, mainly due to their standard candle nature. The availability of large scale surveys of variable stars is allowing us to trace the structure of our entire Galaxy, even in previously inaccessible areas like the Galactic disc. In this work we aim to provide an empirical assessment of the completeness of the three largest RR Lyrae catalogues available: Gaia DR2, PanSTARRS-1 and ASAS-SN-II. Using a joint probabilistic analysis of the three surveys we compute 2D and 3D completeness maps in each survey's full magnitude range. At the bright end (G<13) we find ASAS-SN-II and Gaia are near 100% complete in RRab at high latitude (|b|>20deg); ASAS-SN-II has the best completeness at low latitude for RRab and at all latitudes for RRc. At the faint end (G>13), Gaia DR2 is the most complete catalogue for both RR Lyrae types, at any latitude, with median completeness rates of 95% (RRab) and >85% (RRc) outside the ecliptic plane (|β|>25deg). We confirm a high and uniform completeness of PanSTARRS-1 RR Lyrae at 91% (RRab) and 82% (RRc) down to G~18, and provide the first estimate of its completeness at low galactic latitude (|b|<20deg) at an estimated median 65% (RRab) and 50-60% (RRc). Our results are publicly available as 2D and 3D completeness maps, and as functions to evaluate each survey's completeness versus distance or per line-of sight.

astro-ph.GA↗

arXiv2019

Multivariate Time-series Analysis of Variable Objects in the Gaia Mission

In astronomy, we are witnessing an enormous increase in the number of source detections, precision, and diversity of measurements. Additionally, multi-epoch data is becoming the norm, making time-series analyses an important aspect of current astronomy. The Gaia mission is an outstanding example of a multi-epoch survey that provides measurements in a large diversity of domains, with its broad-band photometry; spectrophotometry in blue and red (used to derive astrophysical parameters); spectroscopy (employed to infer radial velocities, v sin(i), and other astrophysical parameters); and its extremely precise astrometry. Most of all that information is provided for sources covering the entire sky. Here, we present several properties related to the Gaia time series, such as the time sampling; the different types of measurements; the Gaia G, G BP and G RP-band photometry; and Gaia-inspired studies using the CORrelation-RAdial-VELocities data to assess the potential of the information on the radial velocity, the FWHM, and the contrast of the cross-correlation function. We also present techniques (which are used or are under development) that optimize the extraction of astrophysical information from the different instruments of Gaia, such as the principal component analysis and the multi-response regression. The detailed understanding of the behavior of the observed phenomena in the various measurement domains can lead to richer and more precise characterization of the Gaia data, including the definition of more informative attributes that serve as input to (our) machine-learning algorithms.

astro-ph.IM↗

arXiv2018

Gaia Data Release 2: Validation of the classification of RR Lyrae and Cepheid variables with the Kepler and K2 missions

The second data release of the Gaia mission includes an advance catalog of variable stars. The classification of these stars are based on sparse photometry from the first 22 months of the mission. We set out to investigate the purity and completeness of the all-sky Gaia classification results with the help of the continuous light curves of the observed targets from the Kepler and K2 missions, focusing specifically on RR Lyrae and Cepheid pulsators, outside the Galactic Bulge region. We crossmatched the Gaia identifications with the observations collected by the Kepler space telescope. We inspected the light curves visually, then calculated the relative Fourier coefficients and period ratios for the single- and double-mode K2 RR Lyrae stars to further classify them. We identified 1443 and 41 stars classified as RR Lyrae or Cepheid variables in Gaia DR2 in the targeted observations of the two missions and 263 more RR Lyre targets in the Full-Frame Images (FFI) of the original mission. We provide the crossmatch of these sources. We conclude that the RR Lyrae catalog has a completeness between 70-78%, and provide a purity estimate between 92-98% (targeted observations) with lower limits of 75% (FFI stars) and 51% (K2 worst-case scenario). The low number of Cepheids prevents us from drawing detailed conclusions but the purity of the DR2 sample is estimated to be around 66%.

astro-ph.SR↗

arXiv2018

All-sky RR Lyrae Stars in the Gaia Data

The second Gaia data release is expected to contain data products from about 22 months of observation. Based on these data, we aim to provide an advance publication of a full-sky Gaia map of RR Lyrae stars. Although comprehensive, these data still contain a significant fraction of sources which are insufficiently sampled for Fourier series decomposition of the periodic light variations. The challenges in the identification of RR Lyrae candidates with (much) fewer than 20 field-of-view transits are described. General considerations of the results, their limitations, and interpretation are presented together with prospects for improvement in subsequent Gaia data releases.

astro-ph.SR↗

arXiv2017

Short timescale variables in the Gaia era: detection and characterization by structure function analysis

We investigate the capabilities of the ESA Gaia mission for detecting and character- izing short timescale variability, from tens of seconds to a dozen hours. We assess the efficiency of the variogram analysis, for both detecting short timescale variability and estimating the underlying characteristic timescales from Gaia photometry, through extensive light-curve simulations for various periodic and transient short timescale variable types. We show that, with this approach, we can detect fast periodic variabil- ity, with amplitudes down to a few millimagnitudes, as well as some M dwarf flares and supernovae explosions, with limited contamination from longer timescale variables or constant sources. Timescale estimates from the variogram give valuable informa- tion on the rapidity of the underlying variation, which could complement timescale estimates from other methods, like Fourier-based periodograms, and be reinvested in preparation of ground-based photometric follow-up of short timescale candidates evi- denced by Gaia. The next step will be to find new short timescale variable candidates from real Gaia data, and to further characterize them using all the Gaia information, including color and spectrum.

astro-ph.IM↗

arXiv2017

Gaia's Cepheids and RR Lyrae Stars and Luminosity Calibrations Based on Tycho-Gaia Astrometric Solution

Gaia Data Release 1 contains parallaxes for more than 700 Galactic Cepheids and RR Lyrae stars, computed as part of the Tycho-Gaia Astrometric Solution (TGAS). We have used TGAS parallaxes, along with literature ($V, I, J, {K_\mathrm{s}}, W_1$) photometry and spectroscopy, to calibrate the zero point of the Period-Luminosity and Period-Wesenheit relations of classical and type II Cepheids, and the near-infrared Period-Luminosity, Period-Luminosity-Metallicity and optical Luminosity-Metallicity relations of RR Lyrae stars. In this contribution we briefly summarise results obtained by fitting these basic relations adopting different techniques that operate either in parallax or distance (absolute magnitude) space.

astro-ph.SR↗

arXiv2017

Pulsating star research and the Gaia revolution

In this article we present an overview of the ESA Gaia mission and of the unprecedented impact that Gaia will have on the field of variable star research. We summarise the contents and impact of the first Gaia data release on the description of variability phenomena, with particular emphasis on pulsating star research. The Tycho-Gaia astrometric solution, although limited to 2.1 million stars, has been used in many studies related to pulsating stars. Furthermore a set of 3,194 Cepheids and RR Lyrae stars with their times series have been released. Finally we present the plans for the ongoing study of variable phenomena with Gaia and highlight some of the possible impacts of the second data release on variable, and specifically, pulsating stars.

astro-ph.SR↗

arXiv2017

Learn from every mistake! Hierarchical information combination in astronomy

Throughout the processing and analysis of survey data, a ubiquitous issue nowadays is that we are spoilt for choice when we need to select a methodology for some of its steps. The alternative methods usually fail and excel in different data regions, and have various advantages and drawbacks, so a combination that unites the strengths of all while suppressing the weaknesses is desirable. We propose to use a two-level hierarchy of learners. Its first level consists of training and applying the possible base methods on the first part of a known set. At the second level, we feed the output probability distributions from all base methods to a second learner trained on the remaining known objects. Using classification of variable stars and photometric redshift estimation as examples, we show that the hierarchical combination is capable of achieving general improvement over averaging-type combination methods, correcting systematics present in all base methods, is easy to train and apply, and thus, it is a promising tool in the astronomical "Big Data" era.

astro-ph.IM↗

arXiv2017

Crossmatching variable objects with the Gaia data

Tens of millions of new variable objects are expected to be identified in over a billion time series from the Gaia mission. Crossmatching known variable sources with those from Gaia is crucial to incorporate current knowledge, understand how these objects appear in the Gaia data, train supervised classifiers to recognise known classes, and validate the results of the Variability Processing and Analysis Coordination Unit (CU7) within the Gaia Data Analysis and Processing Consortium (DPAC). The method employed by CU7 to crossmatch variables for the first Gaia data release includes a binary classifier to take into account positional uncertainties, proper motion, targeted variability signals, and artefacts present in the early calibration of the Gaia data. Crossmatching with a classifier makes it possible to automate all those decisions which are typically made during visual inspection. The classifier can be trained with objects characterized by a variety of attributes to ensure similarity in multiple dimensions (astrometry, photometry, time-series features), with no need for a-priori transformations to compare different photometric bands, or of predictive models of the motion of objects to compare positions. Other advantages as well as some disadvantages of the method are discussed. Implementation steps from the training to the assessment of the crossmatch classifier and selection of results are described.

astro-ph.IM↗

arXiv2016

Short timescale variables in stellar clusters: From Gaia to ground-based telescopes

Combined studies of variable stars and stellar clusters open great horizons, and they allow us to improve our understanding of stellar cluster formation and stellar evolution. In that prospect, the Gaia mission will provide astrometric, photometric, and spectroscopic data for about one billion stars of the Milky Way. This will represent a major census of stellar clusters, and it will drastically increase the number of known variable stars. In particular, the peculiar Gaia scanning law offers the opportunity to investigate the rather unexplored domain of short timescale variability (from tens of seconds to a dozen of hours), bringing invaluable clues to the fields of stellar physics and stellar aggregates. We assess the Gaia capabilities in terms of short timescale variability detection, using extensive light-curve simulations for various variable object types. We show that Gaia can detect periodic variability phenomena with amplitude variations larger than a few millimagnitudes. Additionally, we plan to perform subsequent follow-up of variables stars detected in clusters by Gaia to better characterize them. Hence, we develop a pipeline for the analysis of high cadence photometry from ground-based telescopes such as the 1.2m Euler telescope (La Silla, Chile) and the 1.2m Mercator telescope (La Palma, Canary Islands).

astro-ph.IM↗

arXiv2015

A comparative study of four significance measures for periodicity detection in astronomical surveys

We study the problem of periodicity detection in massive data sets of photometric or radial velocity time series, as presented by ESA's Gaia mission. Periodicity detection hinges on the estimation of the false alarm probability (FAP) of the extremum of the periodogram of the time series. We consider the problem of its estimation with two main issues in mind. First, for a given number of observations and signal-to-noise ratio, the rate of correct periodicity detections should be constant for all realized cadences of observations regardless of the observational time patterns, in order to avoid sky biases that are difficult to assess. Second, the computational loads should be kept feasible even for millions of time series. Using the Gaia case, we compare the $F^M$ method (Paltani 2004, Schwarzenberg-Czerny 2012), the Baluev method (Baluev 2008) and the GEV method (Süveges 2014), as well as a method for the direct estimation of a threshold. Three methods involve some unknown parameters, which are obtained by fitting a regression-type predictive model using easily obtainable covariates derived from observational time series. We conclude that the GEV and the Baluev methods both provide good solutions to the issues posed by a large-scale processing. The first of these yields the best scientific quality at the price of some moderately costly pre-processing. When this pre-processing is impossible for some reason (e.g. the computational costs are prohibitive or good regression models cannot be constructed), the Baluev method provides a computationally inexpensive alternative with slight biases in regions where time samplings exhibit strong aliases.

astro-ph.IM↗

arXiv2015

The Gaia Mission, Binary Stars and Exoplanets

On the 19th of December 2013, the Gaia spacecraft was successfully launched by a Soyuz rocket from French Guiana and started its amazing journey to map and characterise one billion celestial objects with its one billion pixel camera. In this presentation, we briefly review the general aims of the mission and describe what has happened since launch, including the Ecliptic Pole scanning mode. We also focus especially on binary stars, starting with some basic observational aspects, and then turning to the remarkable harvest that Gaia is expected to yield for these objects.

astro-ph.IM↗