J/AJ/156/126 Stellar parameters & abund. from BACCHUS analysis (Jonsson+, 2018)
APOGEE Data Releases 13 and 14: stellar parameter and abundance comparisons with
independent analyses.
Jonsson H., Prieto C.A., Holtzman J.A., Feuillet D.K., Hawkins K., Cunha K.,
Meszaros S., Hasselquist S., Fernandez-Trincado J.G., Garcia-Hernandez D.A.,
Bizyaev D., Carrera R., Majewski S.R., Pinsonneault M.H., Shetrone M.,
Smith V., Sobeck J., Souto D., Stringfellow G.S., Teske J., Zamora O.
<Astron. J., 156, 126 (2018)>
=2018AJ....156..126J 2018AJ....156..126J (SIMBAD/NED BibCode)
ADC_Keywords: Stars, dwarfs ; Stars, giant ; Abundances ;
Effective temperatures ; Models
Keywords: Galaxy: abundances - stars: abundances - surveys
Abstract:
Data from the SDSS-IV/Apache Point Observatory Galactic Evolution
Experiment (APOGEE-2) have been released as part of SDSS Data Releases 13
(DR13) and 14 (DR14). These include high-resolution H-band spectra, radial
velocities, and derived stellar parameters and abundances. DR13, released
in 2016 August, contained APOGEE data for roughly 150000 stars, and DR14,
released in 2017 August, added about 110000 more. Stellar parameters
and abundances have been derived with an automated pipeline, the APOGEE
Stellar Parameter and Chemical Abundance Pipeline (ASPCAP). We evaluate
the performance of this pipeline by comparing the derived stellar
parameters and abundances to those inferred from optical spectra and
analysis for several hundred stars. For most elements - C, Na, Mg, Al, Si,
S, Ca, Cr, Mn, Ni - the DR14 ASPCAP analyses have systematic differences
with the comparisons samples of less than 0.05 dex (median), and random
differences of less than 0.15 dex (standard deviation). These differences
are a combination of the uncertainties in both the comparison samples
as well as the ASPCAP analysis. Compared to the references, magnesium
is the most accurate alpha-element derived by ASPCAP, and shows a very
clear thin/thick disk separation, while nickel is the most accurate
iron-peak element (besides iron itself).
Description:
We have observed a sample of 100 stars using the optical spectrometer
ARCES (R∼32000) on the Apache Point 3.5 m telescope. The stars were chosen
from the APOGEE catalog to have a spread in stellar parameters, and include
both dwarfs and giants with a wide range of metallicities. The stars have
0.0<V<11.1 and the spectra have an S/N that ranges from 50=<S/N=<300, with
a median S/N of 115 around 6000 Å.
For determination of the stellar parameters as well as the abundances
of O, Na, Mg, Al, Si, S, K, Ca, Ti, V, Cr, Mn, Co, Ni, Cu, Rb, and Y,
we used the Brussels Automatic Code for Characterizing High AccUracy
Spectra (henceforth BACCHUS; Masseron et al. 2016ascl.soft05004M).
BACCHUS is a stellar parameter and abundance analysis pipeline that uses
Turbospectrum in combination with MARCS spherical 1D LTE models. The model
atmosphere grid is alpha-enhanced for the lower metallicities according to
the "standard" MARCS scheme. The stellar parameters are determined in
the classical way, demanding excitation and ionization equilibrium using
a set of Fe I and Fe II lines. The analysis performed is similar to that
described in Hawkins et al. (2015MNRAS.447.2046H 2015MNRAS.447.2046H), with the exception of
the line list used: here we used the Gaia-ESO line list (v.5,
U. Heiter et al. 2015PhyS...90e4010H 2015PhyS...90e4010H, 2018, in preparation), complemented
with line information from the VALD database (Kupka et al.
2000BaltA...9..590K 2000BaltA...9..590K; Ryabchikova et al. 2015PhyS...90e4005R 2015PhyS...90e4005R) for the
non-covered wavelength regimes in the Gaia-ESO list.
File Summary:
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FileName Lrecl Records Explanations
--------------------------------------------------------------------------------
ReadMe 80 . This file
table1.dat 31 73 The line data used in the BACCHUS analysis
table2.dat 37 6802 Line-to-line abundances from the BACCHUS analysis
table3.dat 340 100 Stellar parameters and abundances from the BACCHUS
analysis
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See also:
II/246 : 2MASS All-Sky Catalog of Point Sources (Cutri+ 2003)
J/AJ/146/133 : Stellar parameters from SDSS-III APOGEE DR10 (Meszaros+, 2013)
J/ApJ/794/125 : IN-SYNC. I. APOGEE stellar parameters (Cottaar+, 2014)
J/AJ/151/144 : ASPCAP weights for the 15 APOGEE chemical elements
(Garcia+, 2016)
J/ApJ/852/50 : Galactic halo with APOGEE. II. Abundances.
(Fernandez-Alvar+, 2018)
Byte-by-byte Description of file: table1.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 5 A5 --- El Element
7- 15 F9.4 0.1nm Wave [4981.7305/8773.896] Wavelength (Å)
17- 23 F7.4 [-] loggf [-9.715/0.57] Log of the oscillator strength times
the statistical weight of the lower energy level
25- 31 F7.4 eV Elow [0/14.677] Lower excitation energy level
--------------------------------------------------------------------------------
Byte-by-byte Description of file: table2.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 22 A22 --- 2MASS 2MASS position based star name
(2MASSJHHMMSSss+DDMMSSs)
24- 25 A2 --- El Element
27- 32 F6.1 0.1nm Line [4981.7/8773.9] Line (Å)
34- 37 F4.2 --- A(El) [0/9.36] BACCHUS absolute abundance
--------------------------------------------------------------------------------
Byte-by-byte Description of file: table3.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 22 A22 --- 2MASS 2MASS position based star name
(2MASSJHHMMSSss+DDMMSSs)
24- 27 I4 K Teff [3993/6642] Stellar effective temperature
29- 31 I3 K e_Teff [2/179] Uncertainty in Teff
33- 36 F4.2 [cm/s2] logg [1.15/4.63] Surface gravity
38- 41 F4.2 [cm/s2] e_logg [0/0.84] Uncertainty in logg
43- 47 F5.2 [-] [Fe/H] [-1.79/0.51] Log abundance, [Fe/H]
49- 52 F4.2 [-] e_[Fe/H] [0.06/0.14] Uncertainty in [Fe/H]
54- 57 F4.2 km/s Vturb [0/1.9] Microturbulent velocity
59- 62 F4.2 km/s e_Vturb [0.03/0.13] Uncertainty in Vturb
64- 71 F8.2 [-] [O/Fe] [-0.2/0.71]?=-9999. Log abundance, [O/Fe] (1)
73- 80 F8.2 [-] e_[O/Fe] [0.01/9.73]?=-9999. Uncertainty in [O/Fe] (1)
82- 89 F8.2 [-] [Na/Fe] [-0.25/0.47]?=-9999. Log abundance, [Na/Fe]
(1)
91- 98 F8.2 [-] e_[Na/Fe] [0.01/0.19]?=-9999. Uncertainty in [Na/Fe] (1)
100-107 F8.2 [-] [Mg/Fe] [-0.19/0.46]?=-9999. Log abundance, [Mg/Fe]
(1)
109-116 F8.2 [-] e_[Mg/Fe] [0/0.11]?=-9999. Uncertainty in [Mg/Fe] (1)
118-125 F8.2 [-] [Al/Fe] [-0.19/0.47]?=-9999. Log abundance, [Al/Fe]
(1)
127-134 F8.2 [-] e_[Al/Fe] [0.01/0.08]?=-9999. Uncertainty in [Al/Fe] (1)
136-143 F8.2 [-] [Si/Fe] [-0.16/0.42]?=-9999. Log abundance, [Si/Fe]
(1)
145-152 F8.2 [-] e_[Si/Fe] [0.01/0.05]?=-9999. Uncertainty in [Si/Fe] (1)
154-161 F8.2 [-] [S/Fe] [-0.27/0.6]?=-9999. Log abundance, [S/Fe] (1)
163-170 F8.2 [-] e_[S/Fe] [0/0.07]?=-9999. Uncertainty in [S/Fe] (1)
172-179 F8.2 [-] [K/Fe] [-0.17/0.72]?=-9999. Log abundance, [K/Fe] (1)
181-188 F8.2 [-] e_[K/Fe] [0.02/0.6]?=-9999. Uncertainty in [K/Fe] (1)
190-194 F5.2 [-] [Ca/Fe] [-0.1/0.48]?=-9999. Log abundance, [Ca/Fe] (1)
196-199 F4.2 [-] e_[Ca/Fe] [0.01/0.14]?=-9999. Uncertainty in [Ca/Fe] (1)
201-208 F8.2 [-] [Ti/Fe] [-0.22/0.4]?=-9999. Log abundance, [Ti/Fe] (1)
210-217 F8.2 [-] e_[Ti/Fe] [0.02/0.11]?=-9999. Uncertainty in [Ti/Fe] (1)
219-226 F8.2 [-] [V/Fe] [-0.31/0.37]?=-9999. Log abundance, [V/Fe] (1)
228-235 F8.2 [-] e_[V/Fe] [0.01/0.09]?=-9999. Uncertainty in [V/Fe] (1)
237-241 F5.2 [-] [Cr/Fe] [-0.23/0.31]?=-9999. Log abundance, [Cr/Fe]
(1)
243-246 F4.2 [-] e_[Cr/Fe] [0.01/0.12]?=-9999. Uncertainty in [Cr/Fe] (1)
248-252 F5.2 [-] [Mn/Fe] [-0.43/0.27]?=-9999. Log abundance, [Mn/Fe]
(1)
254-257 F4.2 [-] e_[Mn/Fe] [0/0.18]?=-9999. Uncertainty in [Mn/Fe] (1)
259-266 F8.2 [-] [Co/Fe] [-0.22/0.3]?=-9999. Log abundance, [Co/Fe] (1)
268-275 F8.2 [-] e_[Co/Fe] [0.01/0.12]?=-9999. Uncertainty in [Co/Fe] (1)
277-284 F8.2 [-] [Ni/Fe] [-0.19/0.22]?=-9999. Log abundance, [Ni/Fe]
(1)
286-293 F8.2 [-] e_[Ni/Fe] [0.01/0.07]?=-9999. Uncertainty in [Ni/Fe] (1)
295-299 F5.2 [-] [Cu/Fe] [-0.33/0.35]?=-9999. Log abundance, [Cu/Fe]
(1)
301-304 F4.2 [-] e_[Cu/Fe] [0/0.3]?=-9999. Uncertainty in [Cu/Fe] (1)
306-313 F8.2 [-] [Rb/Fe] [-0.46/0.28]?=-9999. Log abundance, [Rb/Fe]
(1)
315-322 F8.2 [-] e_[Rb/Fe] [0/0.17]?=-9999. Uncertainty in [Rb/Fe] (1)
324-331 F8.2 [-] [Y/Fe] [-0.6/0.35]?=-9999. Log abundance, [Y/Fe] (1)
333-340 F8.2 [-] e_[Y/Fe] [0.01/0.21]?=-9999. Uncertainty in [Y/Fe] (1)
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Note (1): Log of the abundance compared to iron, normalized to the solar
abundances of Grevesse et al. (2007SSRv..130..105G 2007SSRv..130..105G).
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History:
From electronic version of the journal
(End) Prepared by [AAS], Tiphaine Pouvreau [CDS] 04-Mar-2019