KIC 11285625: a double-lined spectroscopic binary with a gamma Dor pulsator discovered from Kepler space photometry

We present the first binary modelling results for the pulsating eclipsing binary KIC 11285625, discovered by the Kepler mission. An automated method to disentangle the pulsation spectrum and the orbital variability in high quality light curves, was developed and applied. The goal was to obtain accurate orbital and component properties, in combination with essential information derived from spectroscopy. A binary model for KIC 11285625 was obtained, using a combined analysis of high-quality space-based Kepler light curves and ground-based high-resolution HERMES echelle spectra. The binary model was used to separate the pulsation characteristics from the orbital variability in the Kepler light curve in an iterative way. We used an automated procedure to perform this task, based on the JKTEBOP binary modelling code, and adapted codes for frequency analysis and prewhitening of periodic signals. Using a disentangling technique applied to the composite HERMES spectra, we obtained a higher signal-to-noise mean component spectrum for both the primary and the secondary. A model grid search method for fitting synthetic spectra was used for fundamental parameter determination for both components. Accurate orbital and component properties of KIC 11285625 were derived, and we have obtained the pulsation spectrum of the gamma Dor pulsator in the system. Detailed analysis of the pulsation spectrum revealed amplitude modulation on a time scale of a hundred days, and strong indications of frequency splittings at both the orbital frequency, and the rotational frequency derived from spectroscopy.

Discovery of a red giant with solar-like oscillations in an eclipsing binary system from Kepler space-based photometry

Oscillating stars in binary systems are among the most interesting stellar laboratories, as these can provide information on the stellar parameters and stellar internal structures. Here we present a red giant with solar-like oscillations in an eclipsing binary observed with the NASA Kepler satellite. We compute stellar parameters of the red giant from spectra and the asteroseismic mass and radius from the oscillations. Although only one eclipse has been observed so far, we can already determine that the secondary is a main-sequence F star in an eccentric orbit with a semi-major axis larger than 0.5 AU and orbital period longer than 75 days.

Comparative clustering analysis of variable stars in the Hipparcos, OGLE Large Magellanic Cloud and CoRoT exoplanet databases

Context. Discovery of new variability classes in large surveys using multivariate statistics techniques such as clustering, relies heavily on the correct understanding of the distribution of known classes as point processes in parameter space. Aims. Our objective is to analyze the correspondence between the classical stellar variability types and the clusters found in the distribution of light curve parameters and colour indices of stars in the CoRoT exoplanet sample. The final aim is to help in the identification on new types of variability by first identifying the well known variables in the CoRoT sample. Methods. We apply unsupervised classification algorithms to identify clusters of variable stars from modes of the probability density distribution. We use reference variability databases (Hipparcos and OGLE) as a framework to calibrate the clustering methodology. Furthermore, we use the results from supervised classification methods to interpret the resulting clusters. Results.We interpret the clusters in the Hipparcos and OGLE LMC databases in terms of large-amplitude radial pulsators in the classical instability strip and of various types of eclipsing binaries. The Hipparcos data also provide clear distributions for low-amplitude nonradial pulsators. We show that the preselection of targets for the CoRoT exoplanet programme results in a completely different probability density landscape than the OGLE data, the interpretation of which involves mainly classes of low-amplitude variability in main-sequence stars. Our findings will be incorporated to improve the supervised classification used in the CoRoT catalogue production, once the existence of new classes or subtypes will be confirmed from complementary spectroscopic observations.

Automated supervised classification of variable stars II. Application to the OGLE database

We aim to extend and test the classifiers presented in a previous work against an independent dataset. We complement the assessment of the validity of the classifiers by applying them to the set of OGLE light curves treated as variable objects of unknown class. The results are compared to published classification results based on the so-called extractor methods.Two complementary analyses are carried out in parallel. In both cases, the original time series of OGLE observations of the Galactic bulge and Magellanic Clouds are processed in order to identify and characterize the frequency components. In the first approach, the classifiers are applied to the data and the results analyzed in terms of systematic errors and differences between the definition samples in the training set and in the extractor rules. In the second approach, the original classifiers are extended with colour information and, again, applied to OGLE light curves. We have constructed a classification system that can process huge amounts of time series in negligible time and provide reliable samples of the main variability classes. We have evaluated its strengths and weaknesses and provide potential users of the classifier with a detailed description of its characteristics to aid in the interpretation of classification results. Finally, we apply the classifiers to obtain object samples of classes not previously studied in the OGLE database and analyse the results. We pay specific attention to the B-stars in the samples, as their pulsations are strongly dependent on metallicity.