J/ApJS/266/18   Double-line spectroscopic binaries from LAMOST   (Zheng+, 2023)

Searching for double-line spectroscopic binaries in the LAMOST Medium-Resolution Spectroscopic survey with deep learning. Zheng Z., Cao Z., Deng H., Mei Y., Tan L., Wang F. <Astrophys. J. Suppl. Ser., 266, 18 (2023)> =2023ApJS..266...18Z 2023ApJS..266...18Z
ADC_Keywords: Binaries, spectroscopic; Spectra, optical; Abundances, [Fe/H] Keywords: Convolutional neural networks ; Spectroscopic binary stars Abstract: Double-line spectroscopic binaries (SB2s) are a vital class of spectroscopic binaries for studying star formation and evolution. Searching for SB2s has been a hot topic in astronomy. Although considerable efforts have been made with fruitful outcomes, limitations in automation and accuracy still persist. In this study, we developed a convolutional neural network (CNN) model to search for SB2 candidates in LAMOST medium-resolution survey (MRS) DR9 v1.0 by detecting double peaks in the cross-correlation function (CCF). We first generated a large number of spectra of single stars and binaries using the iSpec spectral synthesis software (Blanco-Cuaresma+ 2014A&A...569A.111B 2014A&A...569A.111B & Blanco-Cuaresma 2019MNRAS.486.2075B 2019MNRAS.486.2075B). The CCFs of these synthesized spectra were then calculated to form our training set. To efficiently detect the peaks of the CCFs, we applied a Softmax function-based noise reduction method. After testing and validation, the model achieved an accuracy of 97.76% in the testing set and was validated for more than 90% of the sample in several published SB2 catalogs. Finally, by applying the model to examine approximately 1.59 million LAMOST-MRS DR9 spectra, we identified 728 candidate SB2s, including 281 newly discovered ones. File Summary: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file table4.dat 94 2139 Information of 2139 SB2 candidate spectra, identified with the CNN and visually inspected table5.dat 68 36470 Information on the complete table of 36470 SB2 candidates, identified with the CNN table6.dat 68 728 Information on the 728 SB2 candidates, identified with the convolutional neural network (CNN) and visually inspected -------------------------------------------------------------------------------- See also: B/sb9 : SB9: 9th Catalogue of Spectroscopic Binary Orbits (Pourbaix+ 2004-2014) V/156 : LAMOST DR7 catalogs (Luo+, 2019) I/355 : Gaia DR3 Part 1. Main source (Gaia Collaboration, 2022) J/A+A/450/681 : Companions to close sp. binaries (Tokovinin+, 2006) J/AJ/140/184 : RAVE double-lined spectroscopic binaries (Matijevic+, 2010) J/ApJS/190/1 : A survey of stellar families (Raghavan+, 2010) J/A+A/566/A98 : The Gaia Benchmark Stars - Library (Blanco-Cuaresma+, 2014) J/A+A/608/A95 : GES: multi-line spectroscopic binary cand. (Merle+, 2017) J/AJ/156/45 : M-dwarf multiples in the SDSS-III/APOGEE (Skinner+, 2018) J/AJ/157/196 : Close companions around young stars (Kounkel+, 2019) J/A+A/635/A155 : Gaia-ESO Survey SB1 catalogue (Merle+, 2020) J/A+A/638/A145 : GALAH survey. FGK binary stars (Traven+, 2020) J/MNRAS/506/150 : The GALAH+ Survey DR3 (Buder+, 2021) J/other/RAA/21.292 : LAMOST Time-Domain survey, first results (Wang+, 2021) J/MNRAS/510/1515 : Double-lined spectroscopic binaries in M11 (Kovalev+, 2022) J/A+A/664/A159 : Radial velocities of Galactic SB1s (Mahy+, 2022) J/ApJS/258/26 : Spectroscopic binaries from LAMOST MRS. I. (Zhang+, 2022) Byte-by-byte Description of file: table4.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 10 F10.6 deg RAdeg Right Ascension in decimal degrees (J2000) 12- 20 F9.6 deg DEdeg [-10/78.6] Declination in decimal degrees (J2000) 22- 40 I19 --- GaiaDR3 ? Gaia DR3 source identifier 42- 46 F5.2 mag Gmag [8.4/19.1]? Gaia DR3 G band magnitude 48- 84 A37 --- spFile LAMOST FITS spectrum identifier 86- 91 F6.2 --- S/N [50/524.1] Signal-to-Noise of the spectrum 93- 94 I2 --- Index [1/12] Indicies in the spectrum FITS file -------------------------------------------------------------------------------- Byte-by-byte Description of file: table5.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 10 F10.6 deg RAdeg Right Ascension (J2000) 12- 21 F10.6 deg DEdeg [-87.3/89.3] Declination (J2000) 23- 41 I19 --- Gaia ? Gaia DR3 source identifier 43- 47 F5.2 mag Gmag [2.2/21.4]? Gaia DR3 G band magnitude 49- 56 F8.2 K Teff [2900/41505]? Effective temperature from Gaia DR3 58- 62 F5.2 [cm/s2] logg [-0.4/5.1]? Log surface gravity from Gaia DR3 64- 68 F5.2 [Sun] [Fe/H] [-4.2/0.8]? Metallicity from Gaia DR3 -------------------------------------------------------------------------------- Byte-by-byte Description of file: table6.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 10 F10.6 deg RAdeg Right Ascension in decimal degrees (J2000) 12- 20 F9.6 deg DEdeg [-10/78.6] Declination in decimal degrees (J2000) 22- 40 I19 --- Gaia ? Gaia DR3 source identifier 42- 46 F5.2 mag Gmag [8.4/19.1]? Gaia DR3 G band magnitude 48- 55 F8.2 K Teff [4652/11559]? Effective temperature from Gaia DR3 57- 60 F4.2 [cm/s2] logg [2/4.6]? Log surface gravity from Gaia DR3 62- 66 F5.2 [Sun] [Fe/H] [-3.8/0.71]? Metallicity from Gaia DR3 68 A1 --- New? Newly discovered SB2 candidate ("T": 281 sources) -------------------------------------------------------------------------------- History: From electronic version of the journal
(End) Prepared by [AAS], Emmanuelle Perret [CDS] 03-Aug-2023
The document above follows the rules of the Standard Description for Astronomical Catalogues; from this documentation it is possible to generate f77 program to load files into arrays or line by line