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Title:
An automated system to classify stellar spectra - I
Authors:
Allende Prieto, Carlos
Affiliation:
AA(Department of Astronomy, University of Texas, Austin TX 78712-1083, USA;)
Publication:
Monthly Notice of the Royal Astronomical Society, Volume 339, Issue 4, pp. 1111-1116. (MNRAS Homepage)
Publication Date:
03/2003
Origin:
MNRAS
MNRAS Keywords:
methods: data analysis, techniques: spectroscopic, stars: fundamental parameters
DOI:
10.1046/j.1365-8711.2003.06260.x
Bibliographic Code:
2003MNRAS.339.1111A

Abstract

Analyses of stellar spectra often begin with the determination of a number of parameters that define a model atmosphere. This work presents a prototype for an automated spectral classification system that uses a 150-Å-wide region around Hβ, and applies to stars of spectral types A-K with normal (scaled solar) chemical composition. The new tool exploits synthetic spectra based on plane-parallel flux-constant model atmospheres. The input data are high signal-to-noise ratio spectra with a resolution greater than approximately 1 Å. The output parameters are forced to agree with an external scale of effective temperatures, based on the infrared flux method. The system is fast - a spectrum is classified in a few seconds - and well suited for implementation on a web server. We estimate upper limits to the 1σ random error in the retrieved effective temperatures, surface gravities and metallicities as 100 K, 0.3 and 0.1 dex, respectively.

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