J/AJ/163/152 Stellar parameters for ∼650000 stars with APOGEE (Sprague+, 2022)
APOGEE Net: An Expanded Spectral Model of Both Low-mass and High-mass Stars.
Sprague D., Culhane C., Kounkel M., Olney R., Covey K.R., Hutchinson B.,
Lingg R., Stassun K.G., Roman-zuniga C.G., Roman-lopes A., Nidever D.,
Beaton R.L., Borissova J., Stutz A., Stringfellow G.S., Ramirez K.P.,
Ramirez-preciado V., Hernandez J., Kim J.S., Lane R.R.
<Astron. J., 163, 152-152 (2022)>
=2022AJ....163..152S 2022AJ....163..152S (SIMBAD/NED BibCode)
ADC_Keywords: Stars, variable; Effective temperatures; Abundances, [Fe/H];
Spectral types; Spectra, infrared
Keywords: Astroinformatics; Computational methods; Stellar classification
Massive stars; Magellanic Clouds; Young stellar objects
Abstract:
We train a convolutional neural network, APOGEE Net, to predict Teff,
logg, and, for some stars, [Fe/H], based on the APOGEE spectra. This
is the first pipeline adapted for these data that is capable of
estimating these parameters in a self-consistent manner not only for
low-mass stars, (such as main-sequence dwarfs, pre-main-sequence
stars, and red giants), but also high-mass stars with Teff in excess
of 50000K, including hot dwarfs and blue supergiants. The catalog of
∼650000 stars presented in this paper allows for a detailed
investigation of the star-forming history of not just the Milky Way,
but also of the Magellanic clouds, as different type of objects
tracing different parts of these galaxies can be more cleanly selected
through their distinct placement in Teff-logg parameter space than in
previous APOGEE catalogs produced through different pipelines.
Description:
The APOGEE project uses two spectrographs mounted at two 2.5meter
telescopes; one at the Apache Point Observatory (APO), and the other
one at the Las Campanas Observatory (LCO). It is capable of observing
up to 300 sources simultaneously in the H band (1.51-1.7µm), with
the resolution of R∼22500 with the field of view being 3deg in
diameter at APO, and 2deg in diameter at LCO.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
table1.dat 159 648515 Stellar parameters for sources observed by
APOGEE
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See also:
VI/39 : Model Atmospheres (Kurucz, 1979)
VI/120 : High-resolution synthetic stellar library (Coelho+, 2005)
III/272 : RAVE 4th data release (Kordopatis+, 2013)
III/284 : APOGEE-2 data from DR16 (Johnsson+, 2020)
V/154 : Sloan Digital Sky Surveys (SDSS), Release 16 (DR16) (Ahumada+, 2020)
J/ApJ/804/146 : Atmospheric parameters for nearby B-F stars (David+, 2015)
J/ApJ/808/16 : The Cannon a new approach to determine abundances (Ness+, 2015)
J/AJ/151/144 : ASPCAP weights for 15 APOGEE chemical elements (Garcia+, 2016)
J/A+A/603/A56 : Stellar parameters and assumed wind parameters (Cazorla+, 2017)
J/ApJ/855/68 : Massive stars in the SDSS-IV/APOGEE. I. (Roman-Lopes+, 2018)
J/ApJ/873/66 : Massive stars SDSS/APOGEE-2. II. W3-W4-W5 (Roman-Lopes+, 2019)
J/AJ/159/182 : APOGEE Net, YSO parameters through deep learning (Olney+, 2020)
J/ApJ/892/31 : Teff & metallicities of M dwarfs in APOGEE DR14 (Birky+, 2020)
J/ApJ/894/5 : APOGEE2-N NIR spectra of B-type stars (Ramirez-Preciado+, 2020)
J/ApJS/247/17 : Massive stars in APOGEE2 Survey. III. (Roman-Lopes+, 2020)
Byte-by-byte Description of file: table1.dat
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Bytes Format Units Label Explanations
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1- 19 A19 --- ID APOGEE identifier
21- 31 F11.7 deg RAdeg Right Ascension in decimal degrees (J2000)
33- 43 F11.7 deg DEdeg Declination in decimal degrees (J2000)
45- 51 F7.4 [cm/s2] logg [-1.44/5.9]? log surface gravity (1)
53- 58 F6.4 [cm/s2] e_logg [0/0.3]? Uncertainty in log(g) (1)
60- 65 F6.4 [K] Teff [3.17/4.59]? log effective temperature (1)
67- 72 F6.4 [K] e_Teff [0/0.03]? Uncertainty in logT (1)
74- 79 F6.3 [Sun] [Fe/H] [-2/0.5]? Metallicity (1)
81- 86 F6.3 [Sun] e_[Fe/H] [0.001/0.1]? Uncertainty in [Fe/H] (1)
88- 93 F6.1 --- SNR [0/4469] Signal-to-Noise
95- 99 F5.3 [K] Tefft [3.43/4.65]? log training effective
temperature (2)
101-106 F6.3 [cm/s2] loggt [-1.1/5.71]? log training surface gravity (2)
108-113 F6.3 [Sun] [Fe/H]t [-3.7/7.69]? Training metallicity (2)
115-139 A25 --- Ref Reference (3)
142-159 A18 --- SpType Reference spectral type (3)
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Note (1): Parameters predicted in this work.
Note (2): Parameters used to train the network.
Note (3): Reference for the parameters used in training;
SpT shows that the spectral type and luminosity class were available,
Teff shows that Teff , logg, and occasionally [Fe/H] measurements
were available.
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History:
From electronic version of the journal
(End) Prepared by [AAS], Coralie Fix [CDS], 25-Apr-2022