arXiv subjects

J. De Ridder

Publications and source records attributed to J. De Ridder.

At least 19 recordsLinked to original sources

arXiv2026

PlatoSim: An end-to-end PLATO camera simulator for modelling high-precision space-based photometry

PLAnetary Transits and Oscillations of stars (PLATO) is the ESA M3 space mission dedicated to detect and characterise transiting exoplanets including information from the asteroseismic properties of their stellar hosts. The uninterrupted and high-precision photometry provided by space-borne instruments such as PLATO require long preparatory phases. An exhaustive list of tests are paramount to design a mission that meets the performance requirements, and as such, simulations are an indispensable tool in the mission preparation. To accommodate PLATO's need of versatile simulations prior to mission launch - that at the same time describe accurately the innovative but complex multi-telescope design - we here present the end-to-end PLATO simulator specifically developed for the purpose, namely PlatoSim. We show step-by-step the algorithms embedded into the software architecture of PlatoSim that allow the user to simulate photometric time series of CCD images and light curves in accordance to the expected observations of PLATO. In the context of the PLATO payload, a general formalism of modelling, end-to-end, incoming photons from the sky to the final measurement in digital units is discussed. We show the strong predictive power of PlatoSim through its diverse applicability and contribution to numerous working groups within the PLATO Mission Consortium. This involves the on-going mechanical integration and alignment, performance studies of the payload, the pipeline development and assessments of the scientific goals. PlatoSim is a state-of-the-art simulator that is able to produce the expected photometric observations of PLATO to a high level of accuracy. We demonstrate that PlatoSim is a key software tool for the PLATO mission in the preparatory phases until mission launch and prospectively beyond.

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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.

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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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arXiv2025

Mode identification and ensemble asteroseismology of 119 $β$ Cep stars detected by Gaia light curves and monitored by TESS

The Gaia mission detected many new candidate $β$ Cephei ($β$ Cep) pulsators, whose variability classification has since been confirmed from Transiting Exoplanet Survey Satellite (TESS) space photometry of the nominal mission. We aim to analyse all currently available TESS data for these $β$ Cep pulsators, of which 145 were new discoveries, in order to exploit their asteroseismic potential. Although they are of critical importance to improve evolution models of massive stars, $β$ Cep stars are under-represented in the current space photometry revolution. We extracted light curves for 216 stars from TESS full-frame images and performed frequency analysis by means of pre-whitening. Based on Gaia Data Release 3, we deduced stellar properties and compared them to those of known $β$ Cep stars from the literature. We developed a methodology to identify the dominant pulsation modes of the $β$ Cep stars from the detection of rotationally-split multiplets and Gaia and TESS amplitude ratios. We used grid modelling to gain insights into the population of $β$ Cep stars. Combining TESS and Gaia, we successfully identified the mode degrees for 148 stars in our sample. We find the majority to have a dominant dipole non-radial mode. Many non-radial modes show splittings in their TESS frequency spectra, which we use to calculate their envelope rotation, spin parameter, and the level of differential envelope-to-surface rotation (upper limit of about 3). We also provide relative frequency asymmetries within the multiplets, ranging from -0.15 to 0.15 with most being positive. Based on grid modelling, we provide mass, convective core mass, and age distributions for 119 stars. Our study prepares for future detailed modelling based on individual frequencies of identified modes leading towards a better understanding of these massive pulsators. (abridged)

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arXiv2024

MOCKA -- A PLATO mock asteroseismic catalogue: Simulations for gravity-mode oscillators

With ESA's PLATO space mission set for launch in December 2026, a new photometric legacy and a future of new scientific discoveries await. In this work we investigate PLATO's potential for observing pulsating stars across the Hertzsprung-Russell diagram as part of the PLATO Complimentary Science program (PLATO-CS). Specifically, a PLATO mock asteroseismic catalogue (MOCKA) of intermediate to massive stars is presented as a benchmark to highlight the asteroseismic yield of PLATO-CS in a quantitative way. MOCKA includes simulations of $β$~Cephei, slowly pulsating B (SPB), $δ$~Scuti, $γ$~Doradus, RR Lyrae, Cepheid, hot subdwarf, and white dwarf stars. In particular, main-sequence gravity (g) mode pulsators are of interest as some of these stars form an important foundation for the scientific calibration of PLATO. MOCKA is based on a magnitude limited ($G\lesssim17$) \textit{Gaia} catalogue and is a product of realistic end-to-end \texttt{PlatoSim} simulations of stars for the first PLATO pointing field in the Southern hemisphere, which will be observed for a minimally 2-yr duration. We show that an abundant spectrum of frequencies is achievable across a wide range of magnitudes and co-pointing PLATO cameras. Within the magnitude limited regimes simulated ($G \lesssim 14$ for $γ$~Doradus stars and $G \lesssim 16$ for SPB stars) the dominant g-mode frequency is recovered in more than $95\%$ of the cases. MOCKA help us to understand the limits of the PLATO mission as well as highlight the opportunities to push astrophysics beyond current stellar models. All data products of this paper are made available to the community for further exploration. The key data products of MOCKA are the magnitude limited \textit{Gaia} catalogue of the first PLATO pointing field, together with fully reduced light curves from multi-camera observations for each pulsation class.

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arXiv2024

Detecting and sizing the Earth with PLATO: A feasibility study based on solar data

Context. The PLAnetary Transits and Oscillations of stars (PLATO) mission will observe the same area of the sky continuously for at least two years in an effort to detect transit signals of an Earth-like planet orbiting a solar-like star. Aims. We aim to study how short-term solar-like variability caused by oscillations and granulation would affect PLATO's ability to detect and size Earth if PLATO were to observe the Solar System itself. Methods. We injected Earth-like transit signals onto real solar data taken by the Helioseismic and Magnetic Imager (HMI) instrument. We isolated short-term stellar variability by removing any variability with characteristic timescales longer than five hours. We then added a noise model for a variety of different stellar magnitudes computed by PlatoSim assuming an observation by all 24 normal cameras. We first compared four different commonly used treatments of correlated noise in the time domain. We then tried to recover pairs of transit signals. Finally, we performed transit fits using realistic priors on planetary and stellar parameters. Results. We find that short-term solar-like variability affects the correct retrieval of Earth-like transit signals in PLATO data. Variability models accounting for variations with typical timescales at the order of one hour are sufficient to mitigate these effects. For bright targets (8.5 - 10.5 mag), the transit signal of an Earth analogue can reliably be detected in PLATO data. For faint targets the results of transit search algorithms have to be verified by transit-fitting algorithms to avoid false positive detections being flagged. For bright targets (V-mag $\leq$ 9.5), the radius of an Earth-like planet orbiting a solar-like star can be correctly determined at a precision of 3% or less, assuming that at least two transit events are observed and the characteristics of the host star are well understood.

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arXiv2024

Panopticon: a novel deep learning model to detect single transit events with no prior data filtering in PLATO light curves

To prepare for the analyses of the future PLATO light curves, we develop a deep learning model, Panopticon, to detect transits in high precision photometric light curves. Since PLATO's main objective is the detection of temperate Earth-size planets around solar-type stars, the code is designed to detect individual transit events. The filtering step, required by conventional detection methods, can affect the transit, which could be an issue for long and shallow transits. To protect transit shape and depth, the code is also designed to work on unfiltered light curves. We trained the model on a set of simulated PLATO light curves in which we injected, at pixel level, either planetary, eclipsing binary, or background eclipsing binary signals. We also include a variety of noises in our data, such as granulation, stellar spots or cosmic rays. The approach is able to recover 90% of our test population, including more than 25% of the Earth-analogs, even in the unfiltered light curves. The model also recovers the transits irrespective of the orbital period, and is able to retrieve transits on a unique event basis. These figures are obtained when accepting a false alarm rate of 1%. When keeping the false alarm rate low (<0.01%), it is still able to recover more than 85% of the transit signals. Any transit deeper than 180ppm is essentially guaranteed to be recovered. This method is able to recover transits on a unique event basis, and does so with a low false alarm rate. Thanks to light curves being one-dimensional, model training is fast, on the order of a few hours per model. This speed in training and inference, coupled to the recovery effectiveness and precision of the model make it an ideal tool to complement, or be used ahead of, classical approaches.

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arXiv2022

Gaia Data Release 3: Pulsations in main sequence OBAF-type stars

The third Gaia data release provides photometric time series covering 34 months for about 10 million stars. For many of those stars, a characterisation in Fourier space and their variability classification are also provided. This paper focuses on intermediate- to high-mass (IHM) main sequence pulsators M >= 1.3 Msun) of spectral types O, B, A, or F, known as beta Cep, slowly pulsating B (SPB), delta Sct, and gamma Dor stars. These stars are often multi-periodic and display low amplitudes, making them challenging targets to analyse with sparse time series. All datasets used in this analysis are part of the Gaia DR3 data release. The photometric time series were used to perform a Fourier analysis, while the global astrophysical parameters necessary for the empirical instability strips were taken from the Gaia DR3 gspphot tables, and the vsini data were taken from the Gaia DR3 esphs tables. We show that for nearby OBAF-type pulsators, the Gaia DR3 data are precise and accurate enough to pinpoint them in the Hertzsprung-Russell diagram. We find empirical instability strips covering broader regions than theoretically predicted. In particular, our study reveals the presence of fast rotating gravity-mode pulsators outside the strips, as well as the co-existence of rotationally modulated variables inside the strips as reported before in the literature. We derive an extensive period-luminosity relation for delta Sct stars and provide evidence that the relation features different regimes depending on the oscillation period. Finally, we demonstrate how stellar rotation attenuates the amplitude of the dominant oscillation mode of delta Sct stars.

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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.

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arXiv2022

Detection of period-spacing patterns due to the gravity modes of rotating dwarfs in the TESS southern continuous viewing zone

Context: the theory of stellar evolution presents shortcomings when confronted with asteroseismic probes of interior physical properties. The differences between observations and theory are often great because stellar models have mainly been calibrated from observables connected to the surface of stars. Period-spacing patterns caused by gravity modes are a particularly powerful asteroseismic tool that are useful for probing the near-core rotation and mixing of chemical elements in main-sequence stars with convective cores. Aims: we aim to compose a catalog of intermediate-mass stars in the TESS southern continuous viewing zone to reveal period-spacing patterns caused by gravity modes for use in future asteroseismic modeling. Methods: TESS full frame images were inspected to select stars of intermediate- and high-mass using color-magnitude criteria. Light curves were extracted from custom masks per star, adopting stringent constraints on the aperture masks and contamination. The extracted light curves were subject to iterative prewhitening to detect gravity modes. We developed a method based on the assumption that period spacings are an approximately linear function of the mode periods to build a template pattern. This template was used to extract the patterns and their bootstrap uncertainties. Results: our TESS catalog of high-quality period-spacing patterns is the first of its kind and contains 140 gravity-mode patterns in 106 Gamma Doradus stars and 2 slowly pulsating B-type stars. Half of these patterns contain 7 or more measured mode periods and the longest pattern contains 20 modes. We provide the community with a convenient software tool to search for period-spacing patterns and to process the extracted light curves. Conclusions: our catalog offers a fruitful starting point for future gravity-mode asteroseismology of rotating dwarfs with convective cores in the southern hemisphere.

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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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arXiv2020

(Sub)stellar companions shape the winds of evolved stars

Binary interactions dominate the evolution of massive stars, but their role is less clear for low- and intermediate-mass stars. The evolution of a spherical wind from an asymptotic giant branch (AGB) star into a nonspherical planetary nebula (PN) could be due to binary interactions. We observed a sample of AGB stars with the Atacama Large Millimeter/submillimeter Array (ALMA) and found that their winds exhibit distinct nonspherical geometries with morphological similarities to planetary nebulae (PNe). We infer that the same physics shapes both AGB winds and PNe; additionally, the morphology and AGB mass-loss rate are correlated. These characteristics can be explained by binary interaction. We propose an evolutionary scenario for AGB morphologies that is consistent with observed phenomena in AGB stars and PNe.

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arXiv2020

The Carina High-Contrast Imaging Project for massive Stars (CHIPS) I. Methodology and proof of concept on QZ Car ($\equiv$ HD93206)

Massive stars like company. However, low-mass companions have remained extremely difficult to detect at angular separations ($ρ$) smaller than 1" (~1000-3000 au considering typical distance to nearby massive stars) given the large brightness contrast between the companion and the central star. Constraints on the low-mass end of the companions mass-function for massive stars are however needed, for example to help distinguishing between various scenarios for the formation of massive stars. To obtain statistically significant constraint on the presence of low-mass companions beyond the typical detection limit of current surveys ($Δ\mathrm{mag} \lesssim 5$ at $ρ\lesssim 1$"), we initiated a survey of O and Wolf-Rayet stars in the Carina region using the SPHERE coronagraphic instrument on the VLT. In this first paper, we aim to introduce the survey, to present the methodology and to demonstrate the capability of SPHERE for massive stars using the multiple system QZ~Car. High-contrast imaging techniques, such as angular- and spectral-differential imaging techniques as well as PSF-fitting, were applied to detect and measure the relative flux of companions in each spectral channel of the instrument. We detected 19 sources around the QZ~Car system with detection limits of 9~mag at $ρ> 200$~mas for IFS and as faint as 13~mag at $ρ$ > 1".8 for IRDIS (corresponding to sub-solar masses for potential companions). All but two are reported here for the first time. Based on this proof of concept, we showed that VLT/SPHERE allows us to reach the sub-solar mass regime of the companion mass function. This paves the way for this type of observation with a large sample of massive stars to provide novel constraints on the multiplicity of massive stars in a region of the parameter space that has remained inaccessible so far.

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arXiv2019

The young stellar content of the giant HII regions M8, G333.6-0.2, and NGC6357 with VLT/KMOS

Context: The identification and characterisation of populations of young massive stars in (giant) HII regions provides important constraints on i) the formation process of massive stars and their early feedback on the environment, and ii) the initial conditions for population synthesis models predicting the evolution of ensembles of stars. Aims: We identify and characterise the stellar populations of the following young giant HII regions: M8, G333.6-0.2, and NGC6357. Methods: We acquired H- and K-band spectra of around 200 stars using The K-band KMOS on the ESO Very Large Telescope. The targets for M8 and NGC6357 were selected from the MYStIX project, which combines X-ray observations with near-infrared and mid-infrared data. For G333.6-0.2, the sample selection is based on the near-infrared colours combined with X-ray data. We introduce an automatic spectral classification method in order to obtain temperatures and luminosities for the observed stars. We analyse the stellar populations using their photometric, astrometric, and spectroscopic properties and compared the position of the stars in the Hertzprung-Russell diagram with stellar evolution models to constrain their ages and mass ranges. Results: We confirm the presence of candidate ionising sources in the three regions and report new ones, including the first spectroscopically identified O stars in G333.6-0.2. In M8 and NGC6357, two populations are identified: i) OB main-sequence stars ($M > 5~\rm{M_{\odot}}$) and ii) pre-main sequence stars ($M\approx0.5-5~\rm{M_{\odot}}$). The ages of the clusters are $\sim$1-3~Myr, $< 3$~Myr, and $\sim$0.5-3~Myr for M8, G333.6-0.2, and NGC6357, respectively. We show that MYStIX selected targets have $>$ 90\% probability of being members of the HII region, whereas a selection based on near infrared (NIR) colours leads to a membership probability of only $\sim$70\%.

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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.

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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

KIC 2568888: To be or not to be a binary

In cases where both components of a binary system show oscillations, asteroseismology has been proposed as a method to identify the system. For KIC 2568888, observed with $Kepler$, we detect oscillation modes for two red giants in a single power density spectrum. Through an asteroseismic study we investigate if the stars have similar properties, which could be an indication that they are physically bound into a binary system. While one star lies on the red giant branch (RGB), the other, more evolved star, is either a RGB or asymptotic-giant-branch star. We found similar ages for the red giants and a mass ratio close to 1. Based on these asteroseismic results we propose KIC 2568888 as a rare candidate binary system ($\sim 0.1\%$ chance). However, when combining the asteroseismic data with ground-based $BVI$ photometry we estimated different distances for the stars, which we cross-checked with $Gaia$ DR2. From $Gaia$ we obtained for one object a distance between and broadly consistent with the distances from $BVI$ photometry. For the other object we have a negative parallax with a not yet reliable $Gaia$ distance solution. The derived distances challenge a binary interpretation and may either point to a triple system, which could explain the visible magnitudes, or, to a rare chance alignment ($\sim 0.05\%$ chance based on stellar magnitudes). This probability would even be smaller, if calculated for close pairs of stars with a mass ratio close to unity in addition to similar magnitudes, which may indeed indicate that a binary scenario is more favourable.

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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.

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