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The CoRoT faint stars channel observed about 163 600 targets to detect transiting planetary companions. Because CoRoT targets are faint (11< r <16) and close to the galactic plane, only a small subsample has been observed spectroscopically. We describe the latest classification scheme used to derive the spectral type of CoRoT targets, which is based on broadband multi-colour photometry. We assess the accuracy of this spectral classification for the first time. We find that the classification method performs better for stars that were observed during the mission-dedicated photometric ground-based campaigns.The luminosity class is wrong for less than 7% of the targets. Generally, the effective temperature of stars classified as early type (O, B, and A) is overestimated. Conversely, the temperature of stars classified as later type tends to be underestimated. This is mainly due to the adverse effect of interstellar reddening. We find that the median error on the effective temperature is less than 5% for dwarf stars classified with a spectral later than F0, but it is worse for earlier type stars, with up to 20% error for A and late-B dwarfs, and up to 70% for early-B and O-type dwarfs. Similar results are found for giants, with a median error that is lower than 7% for G- and later type giants, but greater than 25% for earlier types. Overall, we find an average median absolute temperature difference |Delta Teff| = 533+-6 K for the whole sample of stars classified as dwarfs and |Delta Teff| = 280+-3 K for the whole sample of giant stars. The corresponding standard deviation is of about 92+-5 K for dwarfs and 304+-4 K for giants. Typically for late-type stars, this means that the classification is accurate to about half a class.
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The determination of exoplanet properties and occurrence rates using Kepler data critically depends on our knowledge of the fundamental properties (such as temperature, radius and mass) of the observed stars. We present revised stellar properties for 197,096 Kepler targets observed between Quarters 1-17 (Q1-17), which were used for the final transiting planet search run by the Kepler Mission (Data Release 25, DR25). Similar to the Q1--16 catalog by Huber et al. the classifications are based on conditioning published atmospheric parameters on a grid of Dartmouth isochrones, with significant improvements in the adopted methodology and over 29,000 new sources for temperatures, surface gravities or metallicities. In addition to fundamental stellar properties the new catalog also includes distances and extinctions, and we provide posterior samples for each stellar parameter of each star. Typical uncertainties are ~27% in radius, ~17% in mass, and ~51% in density, which is somewhat smaller than previous catalogs due to the larger number of improved logg constraints and the inclusion of isochrone weighting when deriving stellar posterior distributions. On average, the catalog includes a significantly larger number of evolved solar-type stars, with an increase of 43.5% in the number of subgiants. We discuss the overall changes of radii and masses of Kepler targets as a function of spectral type, with particular focus on exoplanet host stars.
CoRoT photometric measurements of asteroseismic targets need complementary ground-based spectroscopic observations. We are using the planet-hunter HARPS spectrograph attached to the 3.6m-ESO telescope in the framework of two consecutive Large Programmes. We discuss its use to study line-profile variations and we report on a specific result obtained for the Delta Sct star HD 170699.
The K2 Mission uses the Kepler spacecraft to obtain high-precision photometry over ~80 day campaigns in the ecliptic plane. The Ecliptic Plane Input Catalog (EPIC) provides coordinates, photometry and kinematics based on a federation of all-sky catalogs to support target selection and target management for the K2 mission. We describe the construction of the EPIC, as well as modifications and shortcomings of the catalog. Kepler magnitudes (Kp) are shown to be accurate to ~0.1 mag for the Kepler field, and the EPIC is typically complete to Kp~17 (Kp~19 for campaigns covered by SDSS). We furthermore classify 138,600 targets in Campaigns 1-8 (~88% of the full target sample) using colors, proper motions, spectroscopy, parallaxes, and galactic population synthesis models, with typical uncertainties for G-type stars of ~3% in Teff, ~0.3 dex in log(g), ~40% in radius, ~10% in mass, and ~40% in distance. Our results show that stars targeted by K2 are dominated by K-M dwarfs (~41% of all selected targets), F-G dwarfs (~36%) and K giants (~21%), consistent with key K2 science programs to search for transiting exoplanets and galactic archeology studies using oscillating red giants. However, we find a significant variation of the fraction of cool dwarfs with galactic latitude, indicating a target selection bias due to interstellar reddening and the increased contamination by giant stars near the galactic plane. We discuss possible systematic errors in the derived stellar properties, and differences to published classifications for K2 exoplanet host stars. The EPIC is hosted at the Mikulski Archive for Space Telescopes (MAST): http://archive.stsci.edu/k2/epic/search.php.
Until a few years ago, the amplitude variation in the photometric data had been limitedly explored mainly because of time resolution and photometric sensitivity limitations. This investigation is now possible thanks to the Kepler and CoRoT databases which provided a unique set of data for studying of the nature of stellar variability cycles. The present study characterizes the amplitude variation in a sample of main--sequence stars with light curves collected using CoRoT exo--field CCDs. We analyze potential stellar activity cycles by studying the variability amplitude over small boxes. The cycle periods and amplitudes were computed based on the Lomb-Scargle periodogram, harmonic fits, and visual inspection. As a first application of our approach we have considered the photometric data for 16 CoRoT FGK main sequence stars, revisited during the IRa01, LRa01 and LRa06 CoRoT runs. The 16 CoRoT stars appear to follow the empirical relations between activity cycle periods ($P_{cyc}$) and the rotation period ($P_{rot}$) found by previous works. In addition to the so-called A (active) and I (inactive) sequences previously identified, there is a possible third sequence, here named S (short-cycles) sequence. However, recovery fractions estimated from simulations suggest that only a half of our sample has confident cycle measurements. Therefore, more study is needed to verify our results and Kepler data shall be notably useful for such a study. Overall, our procedure provides a key tool for exploring the CoRoT and Kepler databases to identify and characterize stellar cycle variability.
The space experiment CoRoT has recently detected a transiting hot Jupiter in orbit around a moderately active F-type main-sequence star (CoRoT-Exo-4a). This planetary system is of particular interest because it has an orbital period of 9.202 days, the second longest one among the transiting planets known to date. We study the surface rotation and the activity of the host star during an uninterrupted sequence of optical observations of 58 days. Our approach is based on a maximum entropy spot modelling technique extensively tested by modelling the variation of the total solar irradiance. It assumes that stellar active regions consist of cool spots and bright faculae, analogous to sunspots and solar photospheric faculae, whose visibility is modulated by stellar rotation. The modelling of the light curve of CoRoT-Exo-4a reveals three main active longitudes with lifetimes between about 30 and 60 days that rotate quasi-synchronously with the orbital motion of the planet. The different rotation rates of the active longitudes are interpreted in terms of surface differential rotation and a lower limit of 0.057 pm 0.015 is derived for its relative amplitude. The enhancement of activity observed close to the subplanetary longitude suggests a magnetic star-planet interaction, although the short duration of the time series prevents us from drawing definite conclusions.
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