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  • 标题:The LUMBA UVES stellar parameter pipeline
  • 本地全文:下载
  • 作者:Alvin Gavel ; Pieter Gruyters ; Ulrike Heiter
  • 期刊名称:Astronomy & Astrophysics
  • 印刷版ISSN:0004-6361
  • 电子版ISSN:1432-0746
  • 出版年度:2019
  • 卷号:629
  • 页码:1-11
  • DOI:10.1051/0004-6361/201935937
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:Context.TheGaia-ESO Survey has taken high-quality spectra of a subset of 100 000 stars observed with theGaiaspacecraft. The goal for this subset is to derive chemical abundances for these stars that will complement the astrometric data collected byGaia. Deriving the chemical abundances requires that the stellar parameters be determined.Aims.We present a pipeline for deriving stellar parameters from spectra observed with the FLAMES-UVES spectrograph in its standard fibre-fed mode centred on 580 nm, as used in theGaia-ESO Survey. We quantify the performance of the pipeline in terms of systematic offsets and scatter. In doing so, we present a general method for benchmarking stellar parameter determination pipelines.Methods.Assuming a general model of the errors in stellar parameter pipelines, together with a sample of spectra of stars whose stellar parameters are known from fundamental measurements and relations, we use a Markov chain Monte Carlo method to quantitatively test the pipeline.Results.We find that the pipeline provides parameter estimates with systematic errors on effective temperature below 100 K, on surface gravity below 0.1 dex, and on metallicity below 0.05 dex for the main spectral types of star observed in theGaia-ESO Survey and tested here. The performance on red giants is somewhat lower.Conclusions.The pipeline performs well enough to fulfil its intended purpose within theGaia-ESO Survey. It is also general enough that it can be put to use on spectra from other surveys or other spectrographs similar to FLAMES-UVES.
  • 关键词:enmethods: numericalstars: atmospheresstars: statistics
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