Determination of stellar parameters: the GAUDI archive

1. EuroVO-DCA Workshop, ESAC; Mar 2007 Determination of stellar parameters: the GAUDI archive Enrique Solano1 Carlos Allende-Prieto2 1.- INTA-LAEFF, Spanish-VO 2.- University of Texas, Austin, Spanish-VO

2. EuroVO-DCA Workshop, ESAC; Mar 2007 Determination of stellar parameters • Physical parametrization of stars is essential for the understanding of astrophysical phenomena (e.g. the HR diagram and stellar evolution).

3. EuroVO-DCA Workshop, ESAC; Mar 2007 Determination of stellar parameters (cnt’d) • Advances in technology (robotic telescopes, multiobject spectrographs, automated reduction pipelines) have led to the existence of a large volume of spectroscopic data covering wide wavelength ranges. • FLAMES/GIRAFFE: Up to 130 spectra. • 2dF: Up to 400 simultaneous spectra. FoV: 2 deg. Redshift survey of 250000 galaxies. • RAVE: 300 fibers. FoV: 6 deg. Spectroscopy of up to a million of stars. • SDSS: Up to 640 fibers (DR5 > 1 000 000 spectra). • … and GAIA will collect several millions of stellar spectra.

4. EuroVO-DCA Workshop, ESAC; Mar 2007 Determination of stellar parameters (cnt’d) • The classical methodology, where a high degree of human intervention is present, is quite inappropriate. • Automated methods constitute the only approach to guarantee repeatability and high efficiency in the analysis of these vast datasets.

5. The data • COROT (COnvection, ROtation and planetary Transits, launched on December 2006) has a twofold objective: • Study the stellar interiors (Asteroseismology) • Discover extrasolar planets (transits) • The intrinsic nature of the Seismology Programme (long observations of a few objects) makes the target selection a critical issue. • A preparatory ground-based observing programme (spectroscopy and photometry) of > 1500 potential candidates initiated well before the launch (1998). • All this information is accessible from GAUDI, a VO-compliant archive hosted at LAEFF (http://sdc.laeff.inta.es/gaudi/). • Our sample: GAUDI spectra observed with ELODIE also present in the ELODIE.3 library (Prugniel & Soubiran 2001 A&A 369, 1048):801 objects / 1437 spectra.

6. EuroVO-DCA Workshop, ESAC; Mar 2007 Preprocessing • Resampling and weighted average • Radial velocity correction

7. Preprocessing (cnt’d) • Wavelength range used in the analysis: 4819.94 – 4899.81Å (full range: 3900 – 6800 Å). • Red enough to avoid the difficulties of dealing with metal opacities in the UV. • Blue enough to include a statistically significant number of metallic lines for a reliable determination of the metal abundance even in metal-poor stars. • Forcing the excitation and ionization equilibrium balance is insufficient to determine the triplet (Teff, logg, [M/H]). Hβ used as temperature indicator.

8. EuroVO-DCA Workshop, ESAC; Mar 2007 The synthetic data • Model atmospheres: Kurucz ODFNEW: No convective overshooting, better opacities and abundances. • Grid of models: 4500 < Teff < 7500 (∆:500K), 1.0 < logg < 5.0 (∆:0.5dex), , -2.5 < [Fe/H] < 0.5 (∆:0.5dex)  819 nodes • The range was selected to avoid extreme conditions where Kurucz models may fail: • Cool temperatures at which the contribution of molecules is not fully taken into account • Departures from LTE • Vanishment of spectral lines (very metal-poor object). • Resolution: R=7700. • Low enough to make rotational and macro-turbulent broadening in late-type stars negligible. • High enough to be able to recover information on the line profiles.

9. EuroVO-DCA Workshop, ESAC; Mar 2007 The fitting procedure • The goal: Find the synthetic spectrum that best fits the observed one. • Different methodologies: • Neural networks / Bayesian methods: the learning process is a time-consuming task but, one trained, the speed is very high. • Minimum distance methods • Do not have to be trained. • Inefficient for large surveys and/or multi-parameter space. • Our choice: MDM

10. EuroVO-DCA Workshop, ESAC; Mar 2007 Minimum distance method • Only three parameters (Teff, logg, [M/H]) • Synthetic grid with a modest number of nodes (819) • The number of points per spectra is not high: 198. • p=2; ωi = 1 / σi²  χ² minimization

11. EuroVO-DCA Workshop, ESAC; Mar 2007 Optimization: The Nelder-Mead (downhill) method • Simplicity: requires only function evaluations (not derivatives). • The minimum is enclosed in a simplex (a triangle for two parameters) that is continuously diminished. Interpolation • Continuity and smoothness between neighboring synthetic data (a must for interpolation) is guaranteed. • Generation of interpolated synthetic models is speeded up by interpolating opacities in the plane (log ρ, log T) at any given metallicity (Koersterke, priv. comm.)

12. A-type F-G type K-type The results

13. EuroVO-DCA Workshop, ESAC; Mar 2007 Connecting with the ELODIE.3 • Modelling Hβ is affected by a number of issues. • Core is affected by non-LTE effects (F < 0.4 not taking into account in the fitting process). • The line is formed in deep atmospheric layers where convection is significant. • Normalization is difficult.  Systematic effect in Teff and, therefore, in logg and [M/H]. • Results have been anchored to ELODIE.3 • Careful compilation of physical parameters from the literature • Comparison restricted to the most trusted ones (based on the quality flags).

14. Comparison with ELODIE.3

15. EuroVO-DCA Workshop, ESAC; Mar 2007 Comparisons. [Fe/H] (Cayrel)

16. EuroVO-DCA Workshop, ESAC; Mar 2007 Comparison: Teff (Ribas)

17. EuroVO-DCA Workshop, ESAC; Mar 2007 Future applications • Implementation of a VO service • Routines for pre-processing (concatenation, radial velocity correction, rebinning, normalization). • Access to Kurucz models from SVO Theoretical Data Server using TSAP . • Identifying spectral lines using SLAP (ESA-VO). • Obtaining the best atomic data from VO services (e.g. VALD-VO). • Application to new datasets

18. EuroVO-DCA Workshop, ESAC; Mar 2007 New datasets • GAUDI spectra (others than ELODIE): FEROS, SARG, CORALIE,... • The COROT Exoplanet Programme • Preparatory observations of the COROT fields • 5000 dwarfs with R < 15. • Multifiber spectroscopic observations to determine the parameters. • Follow-up observations to • Assess the planetary nature of a detected transit. • Characterize the planet.