J/ApJ/944/47 High-res. opt. spectra of metal-poor subgiants (Griffith+, 2023)
Untangling the sources of abundance dispersion in low-metallicity stars.
Griffith E.J., Johnson J.A., Weinberg D.H., Ilyin I., Johnson J.W.,
Rodriguez-Martinez R., Strassmeier K.G.
<Astrophys. J., 944, 47 (2023)>
=2023ApJ...944...47G 2023ApJ...944...47G
ADC_Keywords: Abundances; Spectra, optical; Stars, metal-deficient;
Effective temperatures
Keywords: Abundance ratios ; High resolution spectroscopy ;
Chemical enrichment ; Supernovae
Abstract:
We measure abundances of 12 elements (Na, Mg, Si, Ca, Sc, Ti, V, Cr,
Mn, Fe, Co, Ni) in a sample of 86 metal-poor (-2≲[Fe/H]≲-1) subgiant
stars in the solar neighborhood. Abundances are derived from
high-resolution spectra taken with the Potsdam Echelle Polarimetric
and Spectroscopic Instrument on the Large Binocular Telescope, modeled
using iSpec and MOOG. By carefully quantifying the impact of
photon-noise (<0.05dex for all elements), we robustly measure the
intrinsic scatter of abundance ratios. At fixed [Fe/H], the rms
intrinsic scatter in [X/Fe] ranges from 0.04 (Cr) to 0.16dex (Na),
with a median of 0.08dex. Scatter in [X/Mg] is similar, and accounting
for [α/Fe] only reduces the overall scatter moderately. We
consider several possible origins of the intrinsic scatter with
particular attention to fluctuations in the relative enrichment by
core-collapse supernovae (CCSN) and Type Ia supernovae and stochastic
sampling of the CCSN progenitor mass distribution. The stochastic
sampling scenario provides a good quantitative explanation of our data
if the effective number of CCSN contributing to the enrichment of a
typical sample star is N∼50. At the median metallicity of our sample,
this interpretation implies that the CCSN ejecta are mixed over a gas
mass ∼6x104M☉ before forming stars. The scatter of elemental
abundance ratios is a powerful diagnostic test for simulations of star
formation, feedback, and gas mixing in the early phases of the Galaxy.
Description:
We obtained high-resolution optical spectra of 98 stars from the
Potsdam Echelle Polarimetric and Spectroscopic Instrument (PEPSI)
on the Large Binocular Telescope (LBT) between 2021 April 30 and
2022 February 12. Observations were taken with the 300um fiber and
cross-dispersers (CD) II and IV, to obtain R=50000 spectra in the
wavelength ranges 4260-4800 and 5440-6270Å. We achieve a median S/N
of 125 in CD II and 236 in CD IV.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
table1.dat 55 98 Observing details
table2.dat 71 97 Spectroscopic and photometric stellar parameters
table3.dat 155 89 Stellar abundances
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See also:
II/246 : 2MASS All-Sky Catalog of Point Sources (Cutri+ 2003)
VII/233 : 2MASS All-Sky Extended Source Catalog (XSC) (IPAC/UMass, 2003-2006)
I/289 : UCAC2 Catalogue (Zacharias+ 2004)
II/328 : AllWISE Data Release (Cutri+ 2013)
V/164 : LAMOST DR5 catalogs (Luo+, 2019)
I/350 : Gaia EDR3 (Gaia Collaboration, 2020)
III/284 : APOGEE-2 data from DR16 (Johnsson+, 2020)
I/355 : Gaia DR3 Part 1. Main source (Gaia Collaboration, 2022)
J/AJ/120/1841 : Abund. & Kinematics of Halo and Disk Stars (Fulbright 2000)
J/A+A/410/527 : Abundances in the Galactic disk (Bensby+, 2003)
J/A+A/440/321 : Chemical abundances in 43 metal-poor stars (Jonsell+, 2005)
J/AJ/136/2782 : Star formation efficiency in nearby galaxies (Leroy+, 2008)
J/A+A/511/L10 : Abundances and space velocities of 94 stars (Nissen+, 2010)
J/A+A/530/A15 : Abundances of 94 stars (Nissen+, 2011)
J/A+A/562/A71 : Abundances of solar neighbourhood dwarfs (Bensby+, 2014)
J/AJ/147/136 : Stars of very low metal abundance. VI. (Roederer+, 2014)
J/ApJ/807/171 : SkyMapper Survey metal-poor star sp. (Jacobson+, 2015)
J/A+A/594/A43 : APOGEE/Kepler sample stars abundances (Hawkins+, 2016)
J/MNRAS/460/884 : EMBLA survey. Galactic bulge metal-poor stars (Howes+, 2016)
J/ApJ/852/49 : Properties of metal-poor stars in APOGEE DR13 (Hayes+, 2018)
J/MNRAS/488/2283 : COMBS survey. Galactic Bulge metal-poor stars (Lucey+, 2019)
J/AJ/158/14 : Stellar populations of GCs using APOGEE (Nataf+, 2019)
J/ApJS/245/34 : Abund. for 6 million stars from LAMOST DR5 (Xiang+, 2019)
J/MNRAS/493/5195 : Milky Way halo stars ages and kinematics (Das+, 2020)
J/MNRAS/506/150 : The GALAH+ Survey DR3 (Buder+, 2021)
J/A+A/645/A106 : Atomic data for the Gaia-ESO Survey (Heiter+, 2021)
J/ApJ/931/147 : Very metal-poor stars with LAMOST & Subaru. II. (Li+, 2022)
J/A+A/665/A33 : Non-LTE abundances for Na, Mg and Al (Lind+, 2022)
J/A+A/665/A10 : CERES I. Abundances for 52 star (Lombardo+, 2022)
Byte-by-byte Description of file: table1.dat
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Bytes Format Units Label Explanations
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1- 23 A23 --- Name Star name (1)
25- 29 F5.2 mag Vmag [9.42/13.5] V-band magnitude
31- 34 I4 yr Obs.Y [2021/2022] Observation date, year
36- 37 I2 "month" Obs.M Observation date, month
39- 40 I2 d Obs.D Observation date, day in month
42- 47 F6.1 s ExpTime [300/2164] Exposure time
49- 51 I3 --- SNR-CDII [64/230] Signal-to-noise per pixel for
cross-dispersers (CD) II (blue)
53- 55 I3 --- SNR-CDIV [134/443] Signal-to-noise per pixel for
CDIV (red)
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Note (1): The cross correlation routine finds two RV solutions for the spectra
of star 2MASS J14042846+1330190, suggestive of a double line
spectroscopic binary, so we remove this star from our sample (this
star is not included in Tables 2 and 3). See Section 3.2.
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Byte-by-byte Description of file: table2.dat
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Bytes Format Units Label Explanations
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1- 23 A23 --- Name Star name
25- 28 I4 K Teff1 [5061/7288] Spectroscopic (iSpec) effective
temperature
30- 32 I3 K e_Teff1 [16/378] Uncertainty in Teff1
34- 37 F4.2 [cm/s2] logg1 [2.89/4.62] Log, Spectroscopic (iSpec)
surface gravity
39- 42 F4.2 [cm/s2] e_logg1 [0.03/0.7] Uncertainty in logg1
44- 47 F4.2 km/s vt [0/2.92] Spectroscopic (iSpec),
microturbulent velocity
49- 52 F4.2 km/s e_vt [0/3.4] Uncertainty in vt
54- 57 I4 K Teff2 [5034/6720] Photometric (EXOFASTv2) effective
temperature
59- 61 I3 K e_Teff2 [74/445] Uncertainty in Teff2
63- 66 F4.2 [cm/s2] logg2 [3.2/4.32] Log, Photometric (EXOFASTv2)
surface gravity
68- 71 F4.2 [cm/s2] e_logg2 [0.03/0.2] Uncertainty in logg2
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Byte-by-byte Description of file: table3.dat
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Bytes Format Units Label Explanations
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1- 23 A23 --- Name Star name
25- 29 F5.2 [-] FeH [-2.21/0.03] Abundance, FeH
31- 34 F4.2 [-] e_FeH [0.01/0.2] Uncertainty in FeH
36- 40 F5.2 [-] MgH [-1.86/0.08] Abundance, MgH
42- 45 F4.2 [-] e_MgH [0.01/0.21] Uncertainty in MgH
47- 51 F5.2 [-] SiH [-1.72/0.03] Abundance, SiH
53- 56 F4.2 [-] e_SiH [0.01/0.12] Uncertainty in SiH
58- 62 F5.2 [-] CaH [-1.85/0.1] Abundance, CaH
64- 67 F4.2 [-] e_CaH [0.01/0.12] Uncertainty in CaH
69- 73 F5.2 [-] TiH [-1.83/0.08] Abundance, TiH
75- 78 F4.2 [-] e_TiH [0.01/0.25] Uncertainty in TiH
80- 84 F5.2 [-] NaH [-2.2/0.1] Abundance, NaH
86- 89 F4.2 [-] e_NaH [0.01/0.13] Uncertainty in NaH
91- 95 F5.2 [-] ScH [-2.3/0.07] Abundance, ScH
97-100 F4.2 [-] e_ScH [0.02/0.3] Uncertainty in ScH
102-106 F5.2 [-] VH [-2.25/0.11] Abundance, VH
108-111 F4.2 [-] e_VH [0.02/0.3] Uncertainty in VH
113-117 F5.2 [-] CrH [-2.3/0.05] Abundance, CrH
119-122 F4.2 [-] e_CrH [0.02/0.21] Uncertainty in CrH
124-128 F5.2 [-] MnH [-2.66/0.06] Abundance, MnH
130-133 F4.2 [-] e_MnH [0.01/0.3] Uncertainty in MnH
135-139 F5.2 [-] CoH [-2.21/0] Abundance, CoH
141-144 F4.2 [-] e_CoH [0.02/0.25] Uncertainty in CoH
146-150 F5.2 [-] NiH [-2.1/0.07] Abundance, NiH
152-155 F4.2 [-] e_NiH [0.01/0.2] Uncertainty in NiH
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History:
From electronic version of the journal
(End) Prepared by [AAS], Emmanuelle Perret [CDS] 23-Jan-2025