Einsatzmittel schätzen

Valentini, Uwe; Weißbach, Rüdiger; Fahney, Ralf; Gartung, Thomas; Glunde, Jörg; Herrmann, Andrea; Hoffmann, Anne; Knauss, Eric

doi:10.1007/978-3-642-29432-7_11

Cited by 1 publication

(2 citation statements)

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“…The multiplicative polynomial is meant to absorb errors in the flux calibration, Galactic extinction or any other source affecting the shape of the spectrum. It replaces the prior rectification or normalization to the pseudo-continuum that other methods require, as in Valentini & Munari (2010). This model is compared to the data through a non-linear least-square minimization.…”

Section: Ulyss Methodsmentioning

confidence: 99%

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Automatic determination of stellar atmospheric parameters and construction of stellar spectral templates of the Guoshoujing Telescope (LAMOST)

Luo

et al. 2011

Res. Astron. Astrophys.

225

189

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A number of spectroscopic surveys have been carried out or are planned to study the origin of the Milky Way. Their exploitation requires reliable automated methods and softwares to measure the fundamental parameters of the stars. Adopting the ULySS package, we have tested the effect of different resolutions and signal-to-noise ratios (SNR) on the measurement of the stellar atmospheric parameters (effective temperature T eff , surface gravity log g, and metallicity [Fe/H]). We show that ULySS is reliable to determine these parameters with medium-resolution spectra (R∼2000). Then, we applied the method to measure the parameters of 771 stars selected in the commissioning database of the Guoshoujing Telescope (GSJT). The results were compared with the SDSS/SEGUE Stellar Parameter Pipeline (SSPP), and we derived precisions of 167 K, 0.34 dex, and 0.16 dex for T eff , log g and [Fe/H] respectively. Furthermore, 120 of these stars are selected to construct the primary stellar spectra template library (Version 1.0) of GSJT, and will be deployed as basic ingredients for the GSJT automated parametrization pipeline.

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Section: Ulyss Methodsmentioning

confidence: 99%

“…Derivation of radial velocities via cross-correlation against the best matched templates, e.g. Tonry & Davis (1979), Valentini & Munari (2010); 4. Calibration of spectroscopic line/band classification criteria; 5.…”

Section: Introductionmentioning

confidence: 99%