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J/ApJ/562/528 Teff and log(g) of low-metallicity stars (Snider+, 2001)
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Three-dimensional spectral classification of low-metallicity stars using
artificial neural networks.
Snider S., Allende Prieto C., von Hippel T., Beers T.C., Sneden C.,
Qu Y., Rossi S.
<Astrophys. J. 562, 528 (2001)>
=2001ApJ...562..528S
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ADC_Keywords: Stars, population II ; Spectroscopy ; Effective temperatures
Keywords: Galaxy: halo - methods: data analysis - nuclear reactions,
nucleosynthesis, abundances - stars: abundances - stars: Population II
Abstract:
We explore the application of artificial neural networks (ANNs) for
the estimation of atmospheric parameters (T_eff_, log(g), and [Fe/H])
for Galactic F- and G-type stars. The ANNs are fed with
medium-resolution ({Delta}{lambda}~1-2{AA}) nonflux-calibrated
spectroscopic observations. From a sample of 279 stars with previous
high-resolution determinations of metallicity and a set of (external)
estimates of temperature and surface gravity, our ANNs are able to
predict T_eff_ with an accuracy of {sigma}(T_eff_)=135-150K over the
range 4250K<=T_eff_<=6500K, logg with an accuracy of
{sigma}(logg)=0.25-0.30dex over the range 1.0<=logg<=5.0, and [Fe/H]
with an accuracy {sigma}([Fe/H])=0.15-0.20dex over the range
-4.0<=[Fe/H]<=0.3. Such accuracies are competitive with the results
obtained by fine analysis of high-resolution spectra.
It is noteworthy that the ANNs are able to obtain these results
without consideration of photometric information for these stars. We
have also explored the impact of the signal-to-noise ratio (S/N) on
the behavior of ANNs and conclude that, when analyzed with ANNs
trained on spectra of commensurate S/N, it is possible to extract
physical parameter estimates of similar accuracy with stellar spectra
having S/N as low as 13. Taken together, these results indicate that
the ANN approach should be of primary importance for use in present
and future large-scale spectroscopic surveys. The stars that comprise
our study are a subset of the calibration stars used in the Beers et
al. (1999, Cat. <J/AJ/117/981>) medium-resolution surveys.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
table2.dat 55 209 Catalog and ANN parameters for the training sample
table3.dat 55 70 Catalog and ANN parameters for the testing sample
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See also:
J/AJ/117/981 : Estimation of stellar metal abundance. II. (Beers+, 1999)
Byte-by-byte Description of file: table2.dat table3.dat
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Bytes Format Units Label Explanations
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1- 12 A12 --- Name Metal-poor star name
14 A1 --- Source Spectrum source (1)
16 A1 --- f_Source [*] Indicates star is a member of the `nearby'
subsample
18- 21 I4 K CTeff The catalog effective temperature
22 A1 --- f_CTeff [:] Indicates a large discrepancy with ATeff
24- 27 I4 K ATeff The artificial neural network effective
temperature
28 A1 --- f_ATeff [:] Indicates a large discrepancy with CTeff
30- 33 F4.2 [cm/s2] Clog(g) Log of the catalog surface gravity
34 A1 --- f_Clog(g) [:] Indicates a large discrepancy with Alog(g)
36- 39 F4.2 [cm/s2] Alog(g) Log of the artificial neural network
surface gravity
40 A1 --- f_Alog(g) [:] Indicates a large discrepancy with Clog(g)
42- 46 F5.2 --- CFe/H Catalog [Fe/H] (2)
47 A1 --- f_CFe/H [:] Indicates a large discrepancy with AFe/H
49- 53 F5.2 --- AFe/H Artificial neural network [Fe/H] (2)
54 A1 --- f_AFe/H [:] Indicates a large discrepancy with CFe/H
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Note (1): Table 1: The spectroscopic data sets
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Telescope Detector Coverage Disersion Number
({AA}) ({AA}/px)
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E: ESO 1.5 m Ford + Loral 2048x2048 3750-4750 0.65+0.50 52
K: KPNO 2.1 m Tek 2048x2048 3750-5000 0.65 115
L: LCO 2.5 m Reticon + 2D-Frutti 3700-4500 0.65 50
O: ORM INT 2.5 m Tek 1024x1024 3750-4700 0.85 3
P: PAL 5 m Reticon + 2D-Frutti 3700-4500 0.65 3
S: SSO 2.3 m SITe 1752x532 3750-4600 0.50 58
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Note : ESO: European Southern Observatory (Chile)
KPNO: Kitt Peak National Observatory (USA)
LCO: Las Campanas Observatory (Chile)
ORM: Observatorio del Roque de los Muchachos (Spain)
PAL: Palomar Observatory (USA)
SSO: Siding Spring Observatory (Australia)
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Note (2): Where [Fe/H] = log(N(Fe)/N(H))_star_ - log(N(Fe)/N(H))_sun_
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History:
From electronic version of the journal
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(End) Greg Schwarz [AAS], Patricia Bauer [CDS] 22-Jan-2002