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Register a new userMasses and ages for metal-poor stars: a pilot program combining asteroseismology and high-resolution spectroscopic follow-up of RAVE halo stars
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Very metal-poor halo stars are the best candidates for being among the oldest objects in our Galaxy. Samples of halo stars with age determination and detailed chemical composition measurements provide key information for constraining the nature of the first stellar generations and the nucleosynthesis in the metal-poor regime.} Age estimates are very uncertain and are available for only a small number of metal-poor stars. Here we present the first results of a pilot program aimed at deriving precise masses, ages and chemical abundances for metal-poor halo giants using asteroseismology, and high-resolution spectroscopy. We obtained high-resolution UVES spectra for four metal-poor RAVE stars observed by the K2 satellite. Seismic data obtained from K2 light curves helped improving spectroscopic temperatures, metallicities and individual chemical abundances. Mass and ages were derived using the code PARAM, investigating the effects of different assumptions (e.g. mass loss, [alpha/Fe]-enhancement). Orbits were computed using Gaia DR2 data. {The stars are found to be normal metal-poor halo stars (i.e. non C-enhanced), with an abundance pattern typical of old stars (i.e. alpha and Eu-enhanced), and with masses in the 0.80-1.0 M_sun range. The inferred model-dependent stellar ages are found to range from 7.4 to 13.0 Gyr, with uncertainties of ~ 30%-35%. We also provide revised masses and ages for metal-poor stars with Kepler seismic data from APOGEE survey and a set of M4 stars. {The present work shows that the combination of asteroseismology and high-resolution spectroscopy provides precise ages in the metal-poor regime. Most of the stars analysed in the present work (covering the metallicity range of [Fe/H] ~ -0.8 to -2 dex), are very old >9 Gyr (14 out of 19 stars ), and all of them are older than > 5 Gyr (within the 68 percentile confidence level).
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We report on the observations of two ultra metal-poor (UMP) stars with [Fe/H]~-4.0 including one new discovery. The two stars are studied in the on-going and quite efficient project to search for extremely metal-poor (EMP) stars with LAMOST and Subaru. Detailed abundances or upper limits of abundances have been derived for 15 elements from Li to Eu based on high-resolution spectra obtained with Subaru/HDS. The abundance patterns of both UMP stars are consistent with the normal-population among the low-metallicity stars. Both of the two program stars show carbon-enhancement without any excess of heavy neutron-capture elements, indicating that they belong to the subclass of CEMP-no stars, as is the case of most UMP stars previously studied. The [Sr/Ba] ratios of both CEMP-no UMP stars are above [Sr/Ba]~-0.4, suggesting the origin of the carbon-excess is not compatible with the mass transfer from an AGB companion where the s-process has operated. Lithium abundance is measured in the newly discovered UMP star LAMOST J125346.09+075343.1, making it the second UMP turnoff star with Li detection. The Li abundance of LAMOST J125346.09+075343.1 is slightly lower than the values obtained for less metal-poor stars with similar temperature, and provides a unique data point at [Fe/H]~-4.2 to support the meltdown of the Li Spite-plateau at extremely low metallicity. Comparison with the other two UMP and HMP (hyper metal-poor with [Fe/H]<-5.0) turnoff stars suggests that the difference in lighter elements such as CNO and Na might cause notable difference in lithium abundances among CEMP-no stars.
We present results from high-resolution, optical to near-IR imaging of host stars of Kepler Objects of Interest (KOIs), identified in the original Kepler field. Part of the data were obtained under the Kepler imaging follow-up observation program over seven years (2009 - 2015). Almost 90% of stars that are hosts to planet candidates or confirmed planets were observed. We combine measurements of companions to KOI host stars from different bands to create a comprehensive catalog of projected separations, position angles, and magnitude differences for all detected companion stars (some of which may not be bound). Our compilation includes 2297 companions around 1903 primary stars. From high-resolution imaging, we find that ~10% (~30%) of the observed stars have at least one companion detected within 1 (4). The true fraction of systems with close (< ~4) companions is larger than the observed one due to the limited sensitivities of the imaging data. We derive correction factors for planet radii caused by the dilution of the transit depth: assuming that planets orbit the primary stars or the brightest companion stars, the average correction factors are 1.06 and 3.09, respectively. The true effect of transit dilution lies in between these two cases and varies with each system. Applying these factors to planet radii decreases the number of KOI planets with radii smaller than 2 R_Earth by ~2-23% and thus affects planet occurrence rates. This effect will also be important for the yield of small planets from future transit missions such as TESS.
Very metal-poor stars are of obvious importance for many problems in chemical evolution, star formation, and galaxy evolution. Finding complete samples of such stars which are also bright enough to allow high-precision individual analyses is of considerable interest. We demonstrate here that stars with iron abundances [Fe/H] < -2 dex, and down to below -4 dex, can be efficiently identified within the Radial Velocity Experiment (RAVE) survey of bright stars, without requiring additional confirmatory observations. We determine a calibration of the equivalent width of the Calcium triplet lines measured from the RAVE spectra onto true [Fe/H], using high spectral resolution data for a subset of the stars. These RAVE iron abundances are accurate enough to obviate the need for confirmatory higher-resolution spectroscopy. Our initial study has identified 631 stars with [Fe/H] <= -2, from a RAVE database containing approximately 200,000 stars. This RAVE-based sample is complete for stars with [Fe/H] < -2.5, allowing statistical sample analysis. We identify three stars with [Fe/H] <= -4. Of these, one was already known to be `ultra metal-poor, one is a known carbon-enhanced metal-poor star, but we obtain [Fe/H]= -4.0, rather than the published [Fe/H]=-3.3, and derive [C/Fe] = +0.9, and [N/Fe] = +3.2, and the third is at the limit of our S/N. RAVE observations are on-going and should prove to be a rich source of bright, easily studied, very metal-poor stars.
We present a novel analysis of the metal-poor star sample in the complete Radial Velocity Experiment (RAVE) Data Release 5 catalog with the goal of identifying and characterizing all very metal-poor stars observed by the survey. Using a three-stage method, we first identified the candidate stars using only their spectra as input information. We employed an algorithm called t-SNE to construct a low-dimensional projection of the spectrum space and isolate the region containing metal-poor stars. Following this step, we measured the equivalent widths of the near-infrared CaII triplet lines with a method based on flexible Gaussian processes to model the correlated noise present in the spectra. In the last step, we constructed a calibration relation that converts the measured equivalent widths and the color information coming from the 2MASS and WISE surveys into metallicity and temperature estimates. We identified 877 stars with at least a 50% probability of being very metal-poor $(rm [Fe/H] < -2,rm dex)$, out of which 43 are likely extremely metal-poor $(rm [Fe/H] < -3,rm dex )$. The comparison of the derived values to a small subsample of stars with literature metallicity values shows that our method works reliably and correctly estimates the uncertainties, which typically have values $sigma_{rm [Fe/H]} approx 0.2,mathrm{dex}$. In addition, when compared to the metallicity results derived using the RAVE DR5 pipeline, it is evident that we achieve better accuracy than the pipeline and therefore more reliably evaluate the very metal-poor subsample. Based on the repeated observations of the same stars, our method gives very consistent results. The method used in this work can also easily be extended to other large-scale data sets, including to the data from the Gaia mission and the upcoming 4MOST survey.
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