Data reduction, radial velocities and stellar parameters from spectra in the very low signal-to-noise domain

Abstract

Large astronomical facilities usually provide data reduction pipeline designed to deliver ready-to-use scientific data, and too often as- tronomers are relying on this to avoid the most difficult part of an astronomer job Standard data reduction pipelines however are usu- ally designed and tested to have good performance on data with av- erage Signal to Noise Ratio (SNR) data, and the issues that are related with the reduction of data in the very low SNR domain are not taken int account properly. As a result, informations in data with low SNR are not optimally exploited. During the last decade our group has collected thousands of spec- tra using the GIRAFFE spectrograph at Very Large Telescope (Chile) of the European Southern Observatory (ESO) to determine the ge- ometrical distance and dynamical state of several Galactic Globular Clusters but ultimately the analysis has been hampered by system- atics in data reduction, calibration and radial velocity measurements. Moreover these data has never been exploited to get other informa- tions like temperature and metallicity of stars, because considered too noisy for these kind of analyses. In this thesis we focus our attention on data reduction and analysis of spectra with very low SNR. The dataset we analyze in this thesis comprises 7250 spectra for 2771 stars of the Globular Cluster M 4 (NGC 6121) in the wavelength region 5145 − 5360Å obtained with GIRAFFE. Stars from the upper Red Giant Branch down to the Main Sequence have been observed in very different conditions, including nights close to full moon, and reaching SNR ≃ 10 for many spectra in the dataset. We will first review the basic steps of data reduction and spec- tral extraction, adapting techniques well tested in other field (like photometry) but still under-developed in spectroscopy. We improve the wavelength dispersion solution and the correction of radial veloc- ity shift between day-time calibrations and science observations by following a completely different approach with respect to the ESO pipeline. We then analyze deeply the best way to perform sky sub- traction and continuum normalization, the most important sources respectively of noise and systematics in radial velocity determination and chemical analysis of spectra. The huge number of spectra of our dataset requires an automatic but robust approach, which we do not fail to provide. We finally determine radial velocities for the stars in the sample with unprecedented precision with respect to previous works with similar data and we recover the same stellar atmosphere parameters of other studies performed on the same cluster but on brighter stars, with higher spectral resolution and wavelength range ten times larger than our data. In the final chapter of the thesis we face a similar problem but from a completely different perspective. High resolution, high SNR data from the High Accuracy Radial Velocity Planet Searcher spectro- graph (HARPS) in La Silla (Chile) have been used to calibrate the at- mospheric stellar parameters as functions of the main characteristics of Cross-Correlation Functions, specifically built by including spec- tral lines with different sensitivity to stellar atmosphere parameters. These tools has been designed to be quick and to be easy to imple- ment in a instrument pipeline for a real-time determination, neverthe- less they provide accurate parameters even for lower SNR spectra