1 / 13

Preliminary results for the Gaia-ESO UVES tests

Preliminary results for the Gaia-ESO UVES tests. C. Allende Prieto Instituto de Astrofísica de Canarias. Team members. Expected FTE Giraffe FTE UVES C. Allende Prieto (IAC) 0.1 0.1

shalin
Download Presentation

Preliminary results for the Gaia-ESO UVES tests

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Preliminary results for the Gaia-ESO UVES tests C. Allende Prieto Instituto de Astrofísica de Canarias

  2. Team members Expected FTE Giraffe FTE UVES • C. Allende Prieto (IAC) 0.1 0.1 • A. Asensio Ramos (IAC) 0.1 - • F. Garzón (IAC) 0.05 - • J. González-Hernández (IAC) 0.05 (Madrid) • Paul Compére (IAC) 0.5 - • C. González-Fernández (Alicante) 0.05 - • Matthias Steffen (AIP) - 0.3 • Swetlana Hubrig (AIP) - 0.1 • Eric Depagne (AIP) - 0.2 • Michael Weber (AIP) - 0.1 total 0.85 + 0.8 = 1.65

  3. Test (input) data • Gaussian-smoothed (FWHM=0.095 Å) synthetic spectra with noise (S/N=40,70,100) simulating Gaia-ESO UVES observations (4800-6800 Å) of 50 late-type (approx. 4000 < Teff < 6500 K) stars: parameters are Teff,logg,[Fe/H], [/Fe], micro-turbulence • Model atmospheres (MARCS, from website) • Linelist (from VALD)

  4. Preliminary tests • Based on Kurucz model atmospheres (ODFNEW) • Kurucz’s atomic and molecular linelists (upgraded with Barklem et al. Damping constants) • Synthetic spectral computed with iq-package (Koesterke) and our own continuum opacities (Allende Prieto et al. 2003 and subsequent upgrades) • Continuum flattening by chopping the spectrum in pieces and setting their mean to one • Fittings with FERRE (F90 code that uses Nelder-Mead optimization algorithm and quadratic interpolation in fluxes) • Three (Teff,logg,[Fe/H]) and four (Teff,logg,[Fe/H],[/Fe]) parameters considered (micro-turbulence set at 2 km/s) • Initially R=40,000 but then redone at R=60,000

  5. Fittings (Teff,logg,[Fe/H]) S/N=100

  6. Fittings (Teff,logg,[Fe/H],[/Fe] S/N=100

  7. Fittings (Teff,logg,[Fe/H],[/Fe] S/N=100

  8. Fittings (Teff,logg,[Fe/H],[/Fe] S/N=70

  9. Fittings (Teff,logg,[Fe/H],[/Fe] S/N=40

  10. Effect of S/N (70 vs. 100)

  11. Effect of S/N (40 vs. 100)

  12. 3 vs. 4 parameters [Fe/H] Teff logg 1-(robust) 0.06 dex 75 K 0.08 dex

  13. Preliminary conclusions • Model fits are reasonably good, but systematics are apparent (which is useful information) • Same exercise with a consistent linelist, but still Kurucz models, would be useful to discern linelist/models effects • If one assumes a 2=1, the fittings will give S/N= 69 36, 54  23, 36  11 for input S/N=100, 70 and 40 (4 parameters). Metal-poor and warm stars fit better, i.e. the largest discrepancies are found on the metal-rich cool end • S/N doesn’t seem to affect much: random errors due to random noise in the spectra are negligible • Modest effect of considering 4 instead of 3 param. • We are well positioned to repeat the exercise with consistent model fluxes (MARCS+VALD)

More Related