J/ApJS/259/63 Chemically peculiar stars CP1 & CP2 from LAMOST (Shang+, 2022)
Objective separation between CP1 and CP2 based on feature extraction with
machine learning.
Shang L.-H., Luo A.-L., Wang L., Qin Li, Du B., He X.-J., Cui X.-Q.,
Zhao Y.-H., Zhu R.-H., Zhi Q.-J.
<Astrophys. J. Suppl. Ser., 259, 63 (2022)>
=2022ApJS..259...63S 2022ApJS..259...63S
ADC_Keywords: Stars, peculiar; Spectra, optical; Abundances, [Fe/H];
Spectral types
Keywords: Chemically peculiar stars
Abstract:
In the eighth data release (DR8) of the Large Sky Area Multi-Object
Fiber Spectroscopic Telescope, more than 318,740 low-resolution
stellar spectra with types from B to early F and signal-to-noise
ratios >50 were released. With this large volume of the early-type
stars, we tried machine-learning algorithms to search for class-one
and class-two chemical peculiars (CP1 and CP2), and to detect spectral
features to distinguish the two classes in low-resolution spectra. We
selected the XGBoost algorithm after comparing the classification
efficiency of three machine-learning ensemble algorithms. Using
XGBoost followed by the visual investigation, we presented a catalog
of 20694 sources, including 17986 CP1 and 2708 CP2, in which
6917 CP1 and 1652 CP2 are newly discovered. We also list the spectral
features to separate CP1 from CP2 discovered through XGBoost. The
stellar parameters (including effective temperature (Teff), surface
gravity (log g), metallicity [Fe/H]), the spatial distribution in
Galactic coordinates, and the color magnitude were provided for all of
the entries of the catalog. The Teff for CP1 distributes from ∼6000 to
∼8500K, while for CP2 it distributes from ∼7000 to ∼13700K. The log g
of CP1 ranges from 2.8 to 4.8dex, peaking at 4.5dex, and of CP2 it
ranges from 2.0 to 5.0dex, peaking at 3.6dex, respectively. The [Fe/H]
of CP1 and CP2 are from -1.4 to 0.4dex, and the [Fe/H] of CP1 are on
average higher than that of CP2. Almost all of the targets in our
sample locate around the Galactic plane.
Description:
In this paper, we present a reliable and pure sample of
17986 metallic-line or Am stars (chemically peculiar class 1; CP1) and
2708 CP2 stars from the LAMOST DR8 spectra with machine-learning
methods. The sample includes 11069 known CP1 and 1056 known CP2
collected from the published literature of
Renson & Manfroid (2009, III/260), Hou+ (2015, J/MNRAS/449/1401),
Qin+ (2019ApJS..242...13Q 2019ApJS..242...13Q), and Hummerich+ (2020, J/A+A/640/A40), and
newly found 6917 CP1 and 1652 CP2 stars from LAMOST DR8 spectra.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
table1.dat 116 20694 The catalogs of metallic-line or Am stars (CP1) &
magnetic Bp/Ap/CP2 stars (CP2) stars in
the LAMOST DR8
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See also:
III/162 : General Catalogue of Ap and Am stars (Renson+ 1991)
III/260 : General Catalogue of Ap and Am stars (Renson+ 2009)
V/146 : LAMOST DR1 catalogs (Luo+, 2015)
V/156 : LAMOST DR7 catalogs (Luo+, 2019)
J/A+A/441/631 : Δa photometry of CP stars (Paunzen+, 2005)
J/A+A/475/1053 : Magnetic fields in Ap/Bp stars (Auriere+, 2007)
J/MNRAS/449/1401 : Am stars candidates from LAMOST DR1 (Hou+, 2015)
J/AJ/151/13 : LAMOST-Kepler MKCLASS spectral classification (Gray+, 2016)
J/ApJ/836/77 : A library of high-S/N optical sp. of FGKM stars (Yee+, 2017)
J/MNRAS/480/2953 : Catalogue of CP stars (HgMn, ApBp, AmFm) (Ghazaryan+, 2018)
J/A+A/640/A40 : 1002 mCP stars from LAMOST DR4 (Hummerich+, 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 --- LAMOST LAMOST identifier (JHHMMSS.ss+DDMMSS.s)
21- 27 F7.3 deg RAdeg Right Ascension in decimal degrees (J2000)
29- 34 F6.3 deg DEdeg [-10/87.3] Declination (J2000)
36- 43 F8.2 K Teff [6000/15729] Effective temperature
45- 50 F6.2 K e_Teff [124/623] Uncertainty in Teff
52- 56 F5.3 [cm/s2] logg [2.75/4.75] log surface gravity
58- 61 F4.2 [cm/s2] e_logg [0.12/0.8] Uncertainty in logg
63- 68 F6.3 [Sun] [Fe/H] [-1.4/0.4] Metallicity
70- 73 F4.2 [Sun] e_[Fe/H] [0.08/0.5] Uncertainty in [Fe/H]
75- 79 A5 --- SpTLA LAMOST derived spectral type
81-104 A24 --- SpTMKC MKCLASS code derived spectral type (1)
106-110 A5 --- Qual Data quality (2)
112-114 A3 --- Type Subclass of CP type stars ("CP1" or "CP2")
116-116 A1 --- Note Additional note (3)
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Note (1): The spectral subtypes of sample stars are rederived with the MKCLASS
code (http://www.appstate.edu/~grayro/mkclass/ ;
Gray & Corbally 2014AJ....147...80G 2014AJ....147...80G and Gray+ 2016, J/AJ/151/13).
See Section 4.2.
Note (2): Data quality (with corresponding meanings given in
Gray+ 2016, J/AJ/151/13) as follows:
excel = this requires almost exact correspondence between the program
spectrum and the interpolated spectral standard (1 occurrence)
vgood = Typical uncertainty is ±0.6 spectral subtype in the temperature
dimension where 1 spectral subtype is the difference between, for
instance, F5 and F6. In the luminosity dimension, the uncertainty is
about 0.5 luminosity class, where one luminosity class is the
difference between, for instance, "V" and "IV". Luminosity
classification is particularly difficult in the mid A-type stars,
where the uncertainty might rise to =/-1.0 luminosity class.
6475 occurrences.
good = The errors are typically twice those for the "vgood" category
(2871 occurrences)
fair = Spectral types are much more uncertain (43 occurrences)
poor = Spectral types with "poor" are unreliable (74 occurrences)
Note (3): Note as follows:
l = Candidate obtained from published literature.
n = Candidate obtained from this work (8569 occurrences).
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History:
From electronic version of the journal
(End) Prepared by [AAS], Emmanuelle Perret [CDS] 15-Jul-2022