J/ApJ/923/183       Metallicities of very low metal-poor stars       (Li, 2021)

Fuzzy Cluster Analysis: application to determining metallicities for very metal-poor stars. Li H. <Astrophys. J., 923, 183 (2021)> =2021ApJ...923..183L 2021ApJ...923..183L
ADC_Keywords: Abundances, [Fe/H]; Stars, metal-deficient; Spectra, optical Keywords: Population II stars Abstract: This work presents a first attempt to apply fuzzy cluster analysis (FCA) to analyzing stellar spectra. FCA is adopted to categorize line indices measured from LAMOST low-resolution spectra, and automatically remove the least metallicity-sensitive indices. The FCA-processed indices are then transferred to the artificial neural network (ANN) to derive metallicities for 147 very metal-poor (VMP) stars that have been analyzed by high-resolution spectroscopy. The FCA-ANN method could derive robust metallicities for VMP stars, with a precision of ∼0.2dex compared with high-resolution analysis. The recommended FCA threshold value λ for this test is between 0.9965 and 0.9975. After reducing the dimension of the line indices through FCA, the derived metallicities are still robust, with no loss of accuracy, and the FCA-ANN method performs stably for different spectral quality from [Fe/H]∼1.8 down to -3.5. Compared with traditional classification methods, FCA considers ambiguity in groupings and noncontinuity of data, and is thus more suitable for observational data analysis. Though this early test uses FCA to analyze low-resolution spectra, and feeds the input to the ANN method to derive metallicities, FCA should be able to, in the large data era, also analyze slitless spectroscopy and multiband photometry, and prepare the input for methods not limited to ANN, in the field of stellar physics for other studies, e.g., stellar classification, identification of peculiar objects. The literature-collected high-resolution sample can help improve pipelines to derive stellar metallicities, and systematic offsets in metallicities for VMP stars for three published LAMOST catalogs have been discussed. Description: The analysis of this paper is based on spectra obtained through LAMOST DR5 (V/164), which was released in 2019 July. The selected LAMOST targets have been cross-matched with very metal-poor (VMP) stars confirmed by high-resolution spectroscopy from SAGA database (Suda+ 2011, J/MNRAS/412/843) and JINAbase (Abohalima & Frebel 2018ApJS..238...36A 2018ApJS..238...36A). File Summary: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file table3.dat 299 147 List of the very metal-poor (VMP) stars used refs.dat 54 58 References -------------------------------------------------------------------------------- See also: I/345 : Gaia DR2 (Gaia Collaboration, 2018) V/164 : LAMOST DR5 catalogs (Luo+, 2019) J/AJ/103/1987 : Stars of very low metal abundance (Beers+ 1992) J/AJ/117/981 : Estimation of stellar metal abundance. II. (Beers+, 1999) J/AJ/128/1177 : Galactic stellar abundances (Venn+, 2004) J/A+A/439/129 : HERES II. Spectroscopic analysis (Barklem+, 2005) J/A+A/442/961 : Lithium content of the Gal. Halo stars (Charbonnel+, 2005) J/AJ/132/137 : Abund. of extremely metal-poor carbon stars (Cohen+, 2006) J/ApJ/652/1585 : Bright metal-poor stars from HES survey (Frebel+, 2006) J/ApJ/655/492 : Equivalent widths of 26 metal-poor stars (Aoki+, 2007) J/A+A/484/721 : HES survey. IV. Cand. metal-poor stars (Christlieb+, 2008) J/ApJ/681/1524 : Detailed abundances for 28 metal-poor stars (Lai+, 2008) J/A+A/501/519 : Extremely metal-poor turnoff stars abund. (Bonifacio+, 2009) J/AJ/137/4377 : List of SEGUE plate pairs (Yanny+, 2009) J/ApJ/743/140 : Abund. (Be,α) in metal-poor stars (Boesgaard+, 2011) J/ApJ/742/54 : CASH project II. Extremely metal-poor stars (Hollek+, 2011) J/MNRAS/412/843 : SAGA extremely metal-poor stars (Suda+, 2011) J/A+A/548/A34 : Abundances of carbon-enhanced metal-poor stars (Allen+, 2012) J/AJ/145/13 : Metal-poor stars from SDSS/SEGUE. I. Abundances (Aoki+, 2013) J/ApJ/778/56 : Hamburg/ESO Survey extremely metal-poor stars (Cohen+, 2013) J/ApJ/771/67 : Abundances for 97 metal-poor stars. II. (Ishigaki+, 2013) J/ApJ/762/26 : Most metal-poor stars. II. Galactic halo stars (Yong+, 2013) J/AJ/147/136 : Stars of very low metal abundance. VI. (Roederer+, 2014) J/ApJ/797/13 : Abundances of bright metal-poor stars (Schlaufman+, 2014) J/ApJ/807/171 : SkyMapper Survey metal-poor star sp. (Jacobson+, 2015) J/ApJ/798/110 : Equivalent widths of LAMOST metal-poor stars (Li+, 2015) J/ApJ/808/16 : The Cannon: a new approach to determine abund. (Ness+, 2015) J/ApJ/819/110 : Extremely metal-poor gal. in SDSS II. (Sanchez Almeida+ 2016) J/A+A/614/A68 : Carbon-enhanced metal-poor stars sample (Caffau+, 2018) J/A+A/612/A98 : APOGEE full information on classes (Garcia-Dias+, 2018) J/ApJ/858/92 : RPA Southern Pilot Search of 107 Stars (Hansen+, 2018) J/ApJS/238/16 : LAMOST-DR3 very metal-poor star catalog (Li+, 2018) J/ApJ/868/110 : R-Process Alliance: 1st release in Gal. halo (Sakari+, 2018) J/ApJS/245/34 : Abundances for 6 million stars from LAMOST DR5 (Xiang+, 2019) J/ApJ/891/39 : LAMOST very metal-poor stars of the Gal. halo (Yuan+, 2020) http://www.lamost.org/ : LAMOST home page http://jinabase.pythonanywhere.com/ : JINAbase - database for metal-poor stars Byte-by-byte Description of file: table3.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 10 F10.6 deg RAdeg Right Ascension (J2000) 12- 20 F9.6 deg DEdeg [-8.6/58.7] Declination (J2000) 22- 25 I4 K Teff [4210/6650]?=9999 Effective temperature derived from high-resolution spectra 27- 30 F4.2 --- logg [0.01/5]?=9.99 Surface gravity derived from high-resolution spectra 32- 36 F5.2 --- [Fe/H] [-4.8/-2] Metallicity derived from high-resolution spectra 38- 43 F6.2 --- SNg [21.5/592] SNR at g-band of the LAMOST spectra 45- 50 F6.2 --- SNr [23.8/913] SNR at r-band of the LAMOST spectra 52- 56 F5.2 --- FeH-FCA865 [-4.3/-0.8] Metallicity derived from LAMOST spectra, FCA clustered, threshold=0.9865 58- 62 F5.2 --- FeH-FCA885 [-5.3/0.8] Metallicity derived from LAMOST spectra, FCA clustered, threshold=0.9885 64- 68 F5.2 --- FeH-FCA965 [-4.6/-1.9] Metallicity derived from LAMOST spectra, FCA clustered, threshold=0.9965 70- 74 F5.2 --- FeH-FCA975 [-4.6/-1.9] Metallicity derived from LAMOST spectra, FCA clustered, threshold=0.9975 76- 80 F5.2 --- FeH-FCA980 [-4.9/-1.4] Metallicity derived from LAMOST spectra, FCA clustered, threshold=0.9980 82- 86 F5.2 --- FeH-FCA983 [-4.3/-1.2] Metallicity derived from LAMOST spectra, FCA clustered, threshold=0.9983 88- 92 F5.2 --- FeH-FCA985 [-4.8/-1.7] Metallicity derived from LAMOST spectra, FCA clustered, threshold=0.9985 94- 98 F5.2 --- FeH-FCA990 [-7.6/-1.5] Metallicity derived from LAMOST spectra, FCA clustered, threshold=0.9990 100- 105 F6.3 0.1nm CaHK [0/21.43] Line index CaHK 107- 112 F6.3 0.1nm K24 [0/11.34] Line index K24 114- 118 F5.3 0.1nm K12 [0/8.16] Line index K12 120- 124 F5.3 0.1nm K6 [0/4.92] Line index K6 126- 130 F5.3 0.1nm HeI4026 [0/0.9] Line index HeI4026 132- 137 F6.3 0.1nm HD24 [0/10.55] Line index HD24 139- 143 F5.3 0.1nm HD12 [0/6.57] Line index HD12 145- 150 F6.3 0.1nm CN1 [0/22] Line index CN1 152- 157 F6.3 0.1nm CN2 [0/22.95] Line index CN2 159- 163 F5.3 0.1nm Ca4227 [0/2.13] Line index Ca4227 165- 169 F5.3 0.1nm G4300 [0/8.93] Line index G4300 171- 175 F5.3 0.1nm G1 [0/8.34] Line index G1 177- 181 F5.3 0.1nm Fe4383 [0/4.45] Line index Fe4383 183- 187 F5.3 0.1nm Ca4455 [0/0.9] Line index Ca4455 189- 193 F5.3 0.1nm HeI4471 [0/0.82] Line index HeI4471 195- 199 F5.3 0.1nm Fe4531 [0/2.66] Line index Fe4531 201- 205 F5.3 0.1nm Hbeta [0.016/7.66] Line index Hbeta 207- 211 F5.3 0.1nm Fe5015 [0/3.4] Line index Fe5015 213- 218 F6.3 0.1nm Mg1 [0/29.87] Line index Mg1 220- 224 F5.3 0.1nm Mg2 [0.1/7.02] Line index Mg2 226- 230 F5.3 0.1nm Mgb [0/4.31] Line index Mgb 232- 236 F5.3 0.1nm Fe5270 [0/1.86] Line index Fe5270 238- 242 F5.3 0.1nm Fe5335 [0/1.74] Line index Fe5335 244- 248 F5.3 0.1nm Fe5406 [0/0.87] Line index Fe5406 250- 254 F5.3 0.1nm Fe5709 [0/0.6] Line index Fe5709 256- 260 F5.3 0.1nm Fe5782 [0/0.68] Line index Fe5782 262- 266 F5.3 0.1nm NaD [0/9.88] Line index NaD 268- 272 F5.2 --- FeH-DDPayne [-3.7/-0.9]?=-9.99 Metallicity derived from LAMOST spectra, from DDPayne 274- 278 F5.2 --- FeH-DR5v3 [-2.5/-1.37]?=-9.99 Metallicity derived from LAMOST spectra, from official DR5v3 280- 284 F5.2 --- FeH-GSN [-2.41/-1.39]?=-9.99 Metallicity derived from LAMOST spectra, from generative spectrum network (GSN) 286- 299 A14 --- r_[Fe/H] Reference of high-resolution analyses (see refs.dat file) -------------------------------------------------------------------------------- Byte-by-byte Description of file: refs.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 14 A14 --- Ref Reference code 16- 34 A19 --- BibCode Bibcode of the reference 36- 54 A19 --- Comm Comment (Catalog's reference in VizieR) -------------------------------------------------------------------------------- History: From electronic version of the journal
(End) Prepared by [AAS], Emmanuelle Perret [CDS] 24-May-2023
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