J/MNRAS/529/2946 Abundance catalogue of solar twins in GALAH (Walsen+, 2024)
Assembling a high-precision abundance catalogue of solar twins in GALAH for
phylogenetic studies.
Walsen K., Jofre P., Buder S., Yaxley K., Das P., Yates R. M., Hua X.,
Signor T., Eldridge C., Rojas-Arriagada A., Tissera P.B., Johnston E.,
Aguilera-Gomez C., Zoccali M., Gilmore G., Foley R.
<Mon. Not. R. Astron. Soc. 529, 2946-2966 (2024)>
=2024MNRAS.529.2946W 2024MNRAS.529.2946W (SIMBAD/NED BibCode)
ADC_Keywords: Milky Way ; Stars, G-type ; Abundances ; Optical
Keywords: methods: data analysis - techniques: spectroscopic - catalogues
stars: abundances - Galaxy: evolution
Abstract:
Stellar chemical abundances have proved themselves a key source of
information for understanding the evolution of the Milky Way, and the
scale of major stellar surveys such as GALAH have massively increased
the amount of chemical data available. However, progress is hampered
by the level of precision in chemical abundance data as well as the
visualization methods for comparing the multidimensional outputs of
chemical evolution models to stellar abundance data. Machine learning
methods have greatly improved the former; while the application of
tree-building or phylogenetic methods borrowed from a biology are
beginning to show promise with the latter. Here we analyse a sample of
GALAH solar twins to address these issues. We apply The Cannon
algorithm to generate a catalogue of about 40000 solar twins with 14
high precision abundances which we use to perform a phylogenetic
analysis on a selection of stars that have two different ranges of
eccentricities. From our analyses we are able to find a group with
mostly stars on circular orbits and some old stars with eccentric
orbits whose age-[Y/Mg] relation agrees remarkably well with the
chemical clocks published by previous high precision abundance
studies. Our results show the power of combining survey data with
machine learning and phylogenetics to reconstruct the history of the
Milky Way.
Description:
Stellar parameter and chemical abundance data for 38320 solar twin
stars. The data was produced by using The Cannon (Ness et al.,
2015ApJ...808...16N 2015ApJ...808...16N, cat. J/ApJ/808/16) with GALAH DR3 solar twin data
(Buder et al., 2021MNRAS.506..150B 2021MNRAS.506..150B, Cat. J/MNRAS/506/150). The model
was trained using 150 high SNR spectra and applied over the whole
solar twin catalogue, reporting new values and internal uncertainties
for these labels (for more information, see paper). We report the
values and internal uncertainties for following stellar parameters:
effective temperature 'teff', surface gravity 'log g' and metallicity
'[Fe/H]'. We also report the values and internal uncertainties for 14
chemical abundances: [Na/Fe], [Mg/Fe], [Al/Fe], [Si/Fe], [Ca/Fe],
[Sc/Fe], [Ti/Fe], [Cr/Fe], [Mn/Fe], [Ni/Fe], [Cu/Fe], [Zn/Fe], [Y/Fe],
[Ba/Fe].
We use our new catalogue in the construction of phylogenetic trees.
For our purpose, we select from the catalogue two groups of solar
twins with different orbit eccentricity. More specifically, we select
the 100 stars with lowest eccentricities and 101 stars with highest
eccentricities in the sample. These values come as valued-added
information in GALAH and are derived from Gaia DR3 data (see Section 2
for details). The eccentricities range from 0.000723 and 0.000733 for
the low-eccentricity group, and from 0.39 to 0.63 for the high
eccentricity group. Our goal is to study what the phylogenetic trees
built using our measurements tell us about the relatedness of our
sample, and how our measurements help in this goal compared to the
GALAH DR3 ones. For this experiment, we compare the phylogenies
constructed from both data sets. The stars selected for the analysis
are listed in Table B1. In that table, we are including the stars ID
as labelled in the tips of our trees, in addition to the Gaia DR3 IDs
for further references, and their ages and eccentricities as
downloaded from the valued added catalogues of GALAH DR3.
File Summary:
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FileName Lrecl Records Explanations
--------------------------------------------------------------------------------
ReadMe 80 . This file
tablec1.dat 838 38320 Solar twin catalogue
tableb1.dat 36 201 Stars selected for phylogenetic analysis
linemask.dat 32 143 Line masks
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See also:
I/355 : Gaia DR3 Part 1. Main source (Gaia Collaboration, 2022)
J/MNRAS/506/150 : The GALAH+ Survey DR3 (Buder+, 2021)
Byte-by-byte Description of file: tablec1.dat
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Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 19 I19 --- GaiaDR3 ? GAIA DR3 source identifier
21- 35 I15 --- GALAHDR3 GALAH DR3 spectrum identifier
37- 57 F21.17 --- chisq Chi-Square test
59- 76 F18.13 K Teff Effective Temperature
78- 95 F18.16 [cm/s2] logg Surface Gravity
97-120 E24.17 --- [Fe/H] Metallicity
122-145 E24.17 --- [Na/Fe] Na/Fe abundance
147-170 E24.17 --- [Mg/Fe] Mg/Fe abundance
172-195 E24.17 --- [Al/Fe] Al/Fe abundance
197-220 E24.17 --- [Si/Fe] Si/Fe abundance
222-245 E24.17 --- [Ca/Fe] Ca/Fe abundance
247-270 E24.17 --- [Sc/Fe] Sc/Fe abundance
272-295 E24.17 --- [Ti/Fe] Ti/Fe abundance
297-320 E24.17 --- [Cr/Fe] Cr/Fe abundance
322-345 E24.17 --- [Mn/Fe] Mn/Fe abundance
347-370 E24.17 --- [Ni/Fe] Ni/Fe abundance
372-395 E24.17 --- [Cu/Fe] Cu/Fe abundance
397-420 E24.17 --- [Zn/Fe] Zn/Fe abundance
422-445 E24.17 --- [Y/Fe] Y/Fe abundance
447-470 E24.17 --- [Ba/Fe] Ba/Fe abundance
472-491 F20.17 K e_Teff Effective Temperature internal uncertainty
493-513 F21.19 [cm/s2] e_logg Surface Gravity internal uncertainty
515-536 F22.20 --- e_[Fe/H] Metallicity internal uncertainty
538-558 F21.19 --- e_[Na/Fe] Na/Fe abundance internal uncertainty
560-579 F20.18 --- e_[Mg/Fe] Mg/Fe abundance internal uncertainty
581-600 F20.18 --- e_[Al/Fe] Al/Fe abundance internal uncertainty
602-622 F21.19 --- e_[Si/Fe] Si/Fe abundance internal uncertainty
624-644 F21.19 --- e_[Ca/Fe] Ca/Fe abundance internal uncertainty
646-666 F21.19 --- e_[Sc/Fe] Sc/Fe abundance internal uncertainty
668-688 F21.19 --- e_[Ti/Fe] Ti/Fe abundance internal uncertainty
690-710 F21.19 --- e_[Cr/Fe] Cr/Fe abundance internal uncertainty
712-732 F21.19 --- e_[Mn/Fe] Mn/Fe abundance internal uncertainty
734-754 F21.19 --- e_[Ni/Fe] Ni/Fe abundance internal uncertainty
756-775 F20.18 --- e_[Cu/Fe] Cu/Fe abundance internal uncertainty
777-796 F20.18 --- e_[Zn/Fe] Zn/Fe abundance internal uncertainty
798-817 F20.18 --- e_[Y/Fe] Y/Fe abundance internal uncertainty
819-838 F20.18 --- e_[Ba/Fe] Ba/Fe abundance internal uncertainty
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Byte-by-byte Description of file: tableb1.dat
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Bytes Format Units Label Explanations
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1- 3 I3 --- Tip [0/200] Tip ID (1)
5- 23 I19 --- GaiaDR3 GAIA DR3 source identifier
25- 29 F5.2 Gyr Age Age
31- 36 F6.4 --- Ecc Eccentricity
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Note (1): Tip ID corresponds to the integer displayed in the tips of the trees.
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Byte-by-byte Description of file: linemask.dat
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Bytes Format Units Label Explanations
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1- 2 A2 --- El Element
4- 12 F9.4 0.1nm lambda Wavelength
14- 22 F9.4 0.1nm Linemask1 Lower value of line mask interval
24- 32 F9.4 0.1nm Linemask2 Upper value of line mask interval
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Acknowledgements:
Kurt Walsen, kurt.walsen.b(at)gmail.com
History:
28-Mar-2024: on-line version
14-Aug-2024: tables B1 and linemask added from electronic version
(End) Patricia Vannier [CDS] 01-Feb-2024