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Titolo:
The INT search for metal-poor stars: Spectroscopic observations and classification via artificial neural networks
Autore:
Prieto, CA; Rebolo, R; Lopez, RJG; Serra-Ricart, M; Beers, TC; Rossi, S; Bonifacio, P; Molaro, P;
Indirizzi:
Inst Astrofis Canarias, E-38200 La Laguna, Tenerife, Spain Inst Astrofis Canarias La Laguna Tenerife Spain E-38200 , Tenerife, Spain Michigan State Univ, Dept Phys & Astron, E Lansing, MI 48824 USA Michigan State Univ E Lansing MI USA 48824 stron, E Lansing, MI 48824 USA Univ Sao Paulo, Inst Astron & Geofis, BR-04301908 Sao Paulo, Brazil Univ Sao Paulo Sao Paulo Brazil BR-04301908 BC04301908 Sao Paulo, Brazil Univ Trieste, Osservatorio Astron Trieste, I-34131 Trieste, Italy Univ Trieste Trieste Italy I-34131 stron Trieste, I-34131 Trieste, Italy Univ La Laguna, Dept Astrofis, E-38071 Tenerife, Spain Univ La Laguna Tenerife Spain E-38071 Astrofis, E-38071 Tenerife, Spain
Titolo Testata:
ASTRONOMICAL JOURNAL
fascicolo: 3, volume: 120, anno: 2000,
pagine: 1516 - 1531
SICI:
0004-6256(200009)120:3<1516:TISFMS>2.0.ZU;2-J
Fonte:
ISI
Lingua:
ENG
Soggetto:
GALACTIC CHEMICAL EVOLUTION; AUTOMATED CLASSIFICATION; STELLAR SPECTRA; ABUNDANCE; PHOTOMETRY; GALAXY; HALO;
Keywords:
Galaxy : halo; stars : fundamental parameters; stars : Population II; surveys; techniques : spectroscopic;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Physical, Chemical & Earth Sciences
Citazioni:
32
Recensione:
Indirizzi per estratti:
Indirizzo: Prieto, CA Univ Texas, McDonald Observ, RLM 15-308, Austin, TX 78712 USA Univ Texas RLM 15-308 Austin TX USA 78712 Austin, TX 78712 USA
Citazione:
C.A. Prieto et al., "The INT search for metal-poor stars: Spectroscopic observations and classification via artificial neural networks", ASTRONOM J, 120(3), 2000, pp. 1516-1531

Abstract

With the dual aims of enlarging the list of extremely metal-poor stars identified in the Galaxy and boosting the numbers of moderately metal-deficient stars in directions that sample the rotational properties of the thick disk, we have used the 2.5 m Isaac Newton Telescope and the Intermediate Dispersion Spectrograph to carry out a survey of brighter (primarily northern hemisphere) metal-poor candidates selected from the HK objective-prism-interference-filter survey of Beers and collaborators. Over the course of only three observing runs (15 nights) we have obtained medium-resolution (lambda/delta lambda similar or equal to 2000) spectra for 1203 objects (V similar or equal to 11-15). Spectral absorption-line indices and radial velocities have been measured for all the candidates. Metallicities, quantified by [Fe/H], and intrinsic (B-V)(0) colors have been estimated for 731 stars with effective temperatures cooler than roughly 6500 K by using artificial neuralnetworks (ANNs) trained with spectral indices. We show that this method performs as well as a previously explored Ca II K calibration technique, yet it presents some practical advantages. Among the candidates in our sample we identify 195 stars with [Fe/H] less than or equal to -1.0, 67 stars with [Fe/H] less than or equal to -2.0, and 12 new stars with [Fe/H] less than or equal to -3.0. Although the effective yield of metal-poor stars in our sample is not as large as that in previous HK survey follow-up programs, the rate of discovery per unit of telescope time is quite high. Further development of the ANN technique, with the networks being fed the entire spectrum,rather than just the spectral indices, holds the promise to produce fast, accurate, multidimensional spectral classifications (with the associated physical parameter estimates), as is required to process the large data flow provided by present and future instrumentation.

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Documento generato il 19/09/20 alle ore 14:41:13