Open AccessAn automated system to classify stellar spectra – I
Author(s) -
Allende Prieto Carlos
Publication year - 2003
Publication title -
monthly notices of the royal astronomical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.058
H-Index - 383
eISSN - 1365-2966
pISSN - 0035-8711
DOI - 10.1046/j.1365-8711.2003.06260.x
Subject(s) - physics , spectral line , stellar classification , flux (metallurgy) , stellar atmosphere , stars , astrophysics , noise (video) , sigma , plane (geometry) , infrared , computational physics , optics , astronomy , artificial intelligence , computer science , materials science , geometry , mathematics , metallurgy , image (mathematics)
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.