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A large sample of calibration stars for Gaia log g from Kepler and CoRoT

A large sample of calibration stars for Gaia log g from Kepler and CoRoT

Asteroseismic data can be used to determine surface gravities with precisionsof < 0.05 dex by using the global seismic quantities Deltanu and nu_max alongwith Teff and [Fe/H]. Surface gravity is also one of the four stellarproperties to be derived by automatic analyses for 1 billion stars from Gaiadata (workpackage GSP_Phot). We explore seismic data from MS F, G, K stars(solar-like stars) observed by Kepler as a potential calibration source formethods that Gaia will use for object characterisation (log g). We calculatelog g for bright nearby stars for which radii and masses are known, and usingtheir global seismic quantities in a grid-based method, we determine anasteroseismic log g to within 0.01 dex of the direct calculation, thusvalidating the accuracy of our method. We find that errors in Teff and mainly[Fe/H] can cause systematic errors of 0.02 dex. We then apply our method to alist of 40 stars to deliver precise values of surface gravity, i.e. sigma <0.02 dex, and we find agreement with recent literature values. Finally, weexplore the precision we expect in a sample of 400+ Kepler stars which havetheir global seismic quantities measured. We find a mean uncertainty(precision) on the order of <0.02 dex in log g over the full explored range 3.8< log g < 4.6, with the mean value varying only with stellar magnitude (0.01 -0.02 dex). We study sources of systematic errors in log g and find possiblebiases on the order of 0.04 dex, independent of log g and magnitude, whichaccounts for errors in the Teff and [Fe/H] measurements, as well as from usinga different grid-based method. We conclude that Kepler stars provide a wealthof reliable information that can help to calibrate methods that Gaia will use,in particular, for source characterisation with GSP_Phot where excellentprecision (small uncertainties) and accuracy in log g is obtained from seismicdata.

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Accession: 036787828

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DOI: 10.1093/mnras/stt336

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