J/ApJS/267/5       S-type stars from LAMOST MRS DR10 spectra       (Chen+, 2023)

S-type stars from LAMOST DR10: classification of intrinsic and extrinsic stars. Chen J., Li Y.-B., Luo A.-L., Ma X.-X., Li S. <Astrophys. J. Suppl. Ser., 267, 5 (2023)> =2023ApJS..267....5C 2023ApJS..267....5C
ADC_Keywords: Stars, S; Spectra, optical; Surveys; Photometry, infrared; Abundances Keywords: S stars Abstract: In this paper, we found 2939 S-type stars from LAMOST Data Release 10 using two machine-learning methods, and 2306 of them were reported for the first time. The main purpose of this work is to study how to divide S-type stars into intrinsic and extrinsic stars with photometric data and LAMOST spectra. Using infrared photometric data, we adopted two methods to distinguish S-type stars, i.e., the XGBoost algorithm and color-color diagrams. We trained the XGBoost model with 15 input features consisting of colors and absolute magnitudes from Two Micron All Sky Survey (2MASS), AllWISE, AKARI, and IRAS, and found that the model trained by input features with 2MASS, AKARI, and IRAS data has the highest accuracy of 95.52%. Furthermore, using this XGBoost model, we found four color-color diagrams with six infrared color criteria to divide S-type stars, which have an accuracy of about 90%. Applying the two methods to the 2939 S-type stars, 381 (XGBoost)/336 (color-color diagrams) intrinsic and 495 (XGBoost)/82 (color-color diagrams) extrinsic stars were classified, respectively. Using these photometrically classified intrinsic and extrinsic stars, we retrained the XGBoost model with their blue and red medium-resolution spectra, and the 2939 stars were divided into 855 intrinsic and 2056 extrinsic stars from spectra with an accuracy of 94.82%. In addition, we also found the four spectral regions of ZrI (6451.6Å), NeII (6539.6Å), Hα (6564.5Å), and FeI (6609.1Å) and CI (6611.4Å) are the most important features, which can reach an accuracy of 92.1% when using them to classify S-type stars. Description: Since 2018 October, LAMOST started the phase II survey, which contains both low- (R∼1800) and medium- (R∼7500) resolution spectroscopic surveys. From 2021 October to 2022 June, LAMOST DR10 collected 8,099,218 single-exposure spectra and 2,205,500 coadded spectra. In our previous paper (Paper I; Chen+ 2022, J/ApJ/931/133), 606 S-type stars were found from LAMOST MRS DR9. In this work, only the machine-learning methods were used to find S-type stars from MRS of LAMOST DR10, and the 606 S-type stars from Paper I were treated as positive samples to search for more complete S-type samples. File Summary: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file table3.dat 121 2939 2939 S-type stars in this work -------------------------------------------------------------------------------- See also: II/246 : 2MASS All-Sky Catalog of Point Sources (Cutri+ 2003) II/297 : AKARI/IRC mid-IR all-sky Survey (ISAS/JAXA, 2010) II/338 : IRAS PSC/FSC Combined Catalogue (Abrahamyan+ 2015) V/156 : LAMOST DR7 catalogs (Luo+, 2019) III/284 : APOGEE-2 data from DR16 (Johnsson+, 2020) I/355 : Gaia DR3 Part 1. Main source (Gaia Collaboration, 2022) V/155 : GDR2AP. Gaia DR2, 2MASS, AllWISE astrophys. param. (Fouesneau+, 2022) J/A+A/387/129 : IR observations of S stars (Wang+, 2002) J/ApJ/831/20 : C/O and Mg/Si for solar neighborhood's stars (Brewer+, 2016) J/A+A/601/A10 : MARCS model atmospheres for S stars (Van Eck+, 2017) J/ApJS/234/31 : Carbon stars from LAMOST using machine learning (Li+, 2018) J/AJ/158/22 : IR study of intrinsic & extrinsic S-type stars (Chen+, 2019) J/A+A/626/A127 : Barium and related stars and WD companions (Jorissen+, 2019) J/MNRAS/490/157 : Fastest stars in the Galaxy with Gaia DR2 (Marchetti+, 2019) J/A+A/633/A135 : Solar neighbourhood carbon stars properties (Abia+, 2020) J/A+A/664/A45 : Characterisation of Galactic carbon stars (Abia+, 2022) J/ApJ/931/133 : S-type stars from LAMOST MRS DR9 with Gaia DR2 (Chen+, 2022) Byte-by-byte Description of file: table3.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 19 A19 --- LAMOST LAMOST DR10 designation (JHHMMSS.ss+DDMMSS.s) 21- 31 F11.7 deg RAdeg Right Ascension (J2000) 33- 43 F11.8 deg DEdeg [-10/84] Declination (J2000) 45- 49 F5.2 mag Jmag [3/13.1]? 2MASS J band magnitude 51- 55 F5.2 mag Hmag [1.97/13]? 2MASS H band magnitude 57- 61 F5.2 mag Ksmag [1/13]? 2MASS Ks band magnitude 63- 68 F6.2 Jy F9um [0.04/277]? AKARI 9um flux 70- 75 F6.2 Jy F18um [0.07/204]? AKARI 18um flux 77- 82 F6.2 Jy F12um [0.08/342]? IRAS 12um flux 84- 89 F6.2 Jy F25um [0.04/195]? IRAS 25um flux 91- 103 A13 --- Type SIMBAD main object type 105- 108 F4.2 --- C/O-M [0.5/1]? Carbon to oxygen abundance ratio estimated by the MARCS S-type star model 110- 113 F4.2 --- C/O-A [0.37/0.98]? C/O estimated by the [C/Fe] and [O/Fe] from APOGEE DR17 115 A1 --- ClXGB [EI] Classified result from XGBoost model (I=Intrinsic S-type; E=extrinsic S-type star) 117 A1 --- ClCol [EI] Classified result from color-color diagram (I=Intrinsic S-type; E=extrinsic S-type star 119 A1 --- ClSp [EI] Classified result from optical spectrum (I=Intrinsic S-type; E=extrinsic S-type star) 121 A1 --- ERV [TF] Sources with large variations in RVs (T=520 occurrences) -------------------------------------------------------------------------------- History: From electronic version of the journal References: Chen et al. Paper I 2022ApJ...931..133C 2022ApJ...931..133C Cat. J/ApJ/931/133
(End) Prepared by [AAS], Emmanuelle Perret [CDS] 16-Aug-2023
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