Automatic stellar spectra parameterisation in the IR Ca ii triplet region

Context. Galactic archaeology aims to determine the evolution of the Galaxy from the chemical and kinematical properties of its individual stars. This requires the analysis of data from la rge spectroscopic surveys, with sample sizes in tens of thou sands at present, with millions of stars being reached in the near future. Such large samples require automated analysis techniques and cl ssification algorithms to obtain robust estimates of the stellar parame ter values. Several on-going and planned spectroscopic sur veys have selected their wavelength region to contain the IR Ca ii triplet (∼ λλ 8500 Å) and the work presented in this paper focuses on the aut omatic analysis of such spectra. Aims. We aim to develop and test an automatic method by which one can obtain estimates of values of the stellar atmospheric parameters (e ffective temperature, surface gravity, overall metallicity ) from a stellar spectrum. We also explore the degeneracies i n parameter space, estimate the uncertainties in the derived parameter values and investigate the consequences of these limitations for achieving the goals of galactic archaeology. Methods. We investigated two algorithms, both of which compare the ob served spectrum to a grid of synthetic spectra, but each uses a different mathematical approach for finding the optimum match an d he ce the best values of the stellar parameters. Our invest igation of these algorithms’ robustness can be widely applied becau se it amplifies the main problems that the other methods can en counter. The first algorithm, MATISSE, derives the values of each stel lar parameter through a local fit to the spectrum such that eac h pixel in wavelength space is treated separately. The sensitivity of he flux at each wavelength to the value of a given stellar pa rameter is determined from the synthetic spectra. The observed spectr um is then projected using these sensitivity vectors to give an stimated value of the stellar parameters. This value depends on findin g the true minimum in the fit and the algorithm must avoid being trapped in false local minima. The second algorithm, DEGAS, uses a pa ttern-recognition approach and consequently has a more glo bal vision of the parameter space. The best-fit synthetic spectrum is de rive through a series of comparisons between the observed a nd synthetic spectra, summed over wavelength pixels, with additional re finements in the set of synthetic spectra after each stage, i. e. a decision tree. Results. We identified physical degeneracies in di fferent regions of the H–R diagram: hot dwarf and giant stars sh are t e same spectral signatures. Furthermore, it is very di fficult to determine an accurate value for the surface gravity o f co ler dwarfs. These e ffects are intensified when the lack of information increases, which ha ppens for low-metallicity stars or spectra with low signalto-noise ratios (SNRs). Our results demonstrate that the local projection m ethod is preferred for spectra with high SNR, whereas the dec ision-tree method is preferred for spectra of lower SNR. We therefore pr opose a hybrid approach, combining these methods, and demon strate that sufficiently accurate results for the purposes of galactic archa eology studies are retrieved down to SNR ∼20 for typical parameter values of stars belonging to the local thin or thick disc, and for SNR down to∼50 for the more metal-poor giant stars of the halo. Conclusions. If unappreciated, degeneracies in stellar parameters can i ntroduce biases and systematic errors in derived quantitie s for target stars such as distances and full space motions. These can be minimised using the knowledge gained by thorough test ing of the proposed stellar classification algorithm, which in tur n lead to robust automated methods for the coming extensive s pectroscopic surveys of stars in the Local Group.