Context. An increasing number of high resolution stellar spectra is available today thanks to many past and ongoing spectroscopic surveys. Consequently, numerous methods have been developed in order to perform an automatic spectral analysis on a massive amount of data. When reviewing published results, biases arise and they need to be addressed and minimized.
Aims. We are providing a homogeneous library with a common set of calibration stars (known as the Gaia FGK Benchmark Stars) that will allow to assess stellar analysis methods and calibrate spectroscopic surveys.
Methods. High resolution and signal-to-noise spectra were compiled from different instruments. We developed an automatic process in order to homogenize the observed data and assess the quality of the resulting library.
Results. We built a high quality library that will facilitate the assessment of spectral analyses and the calibration of present and future spectroscopic surveys. The automation of the process minimizes the human subjectivity and ensures reproducibility. Additionally, it allows us to quickly adapt the library to specific needs that can arise from future spectroscopic analyses.
S. Blanco-Cuaresma, C. Soubiran, P. Jofre, et. al.
Fri, 14 Mar 14