J/AJ/165/145ivo://CDS.VizieR/J/AJ/165/145doi:10.26093/cds/vizier.51650145CDSLi Y.Ezzeddine R.2024-02-13T12:09:40Z2023-11-17T11:25:02ZCDS support team

CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France

cds-question@unistra.frastronomical-modelsstellar-atmospheresmetallicityeffective-temperaturevisible-astronomyspectroscopyPrecise fundamental atmospheric stellar parameters and abundance determination of individual elements in stars are important for all stellar population studies. Non-local thermodynamic equilibrium (non-LTE; hereafter NLTE) models are often important for such high precision, however, can be computationally complex and expensive, which renders the models less utilized in spectroscopic analyses. To alleviate the computational burden of such models, we developed a robust 1D, NLTE fundamental atmospheric stellar parameter derivation tool, LOTUS, to determine the effective temperature Teff, surface gravity logg, metallicity [Fe/H], and microturbulent velocity v_mic_ for FGK-type stars, from equivalent width (EW) measurements of FeI and FeII lines. We utilize a generalized curve of growth method to take into account the EW dependencies of each FeI and FeII line on the corresponding atmospheric stellar parameters. A global differential evolution optimization algorithm is then used to derive the fundamental parameters. Additionally, LOTUS can determine precise uncertainties for each stellar parameter using a Markov Chain Monte Carlo algorithm. We test and apply LOTUS on a sample of benchmark stars, as well as stars with available asteroseismic surface gravities from the K2 survey, and metal-poor stars from the Gaia-ESO and R-Process Alliance surveys. We find very good agreement between our NLTE-derived parameters in LOTUS to nonspectroscopic values on average within Teff={+/-}30K, and logg={+/-}0.10dex for benchmark stars. We provide open access of our code, as well as of the interpolated precomputed NLTE EW grids available on Github (the software is available on GitHubunder an MIT License, and version 0.1.1 (as the persistent version) is archived in Zenodo) and documentation with working examples.2023AJ....165..145Lhttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/AJ/165/145CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toIII/283 : RAVE 6th data release (Steinmetz+, 2020)V/154 : Sloan Digital Sky Surveys (SDSS), Release 16 (DR16) (Ahumada+, 2020)J/PASJ/57/109 : Late-G giants abundances (Takeda+, 2005)J/A+A/512/A54 : Teff and Fbol from Infrared Flux Method (Casagrande+, 2010)J/A+A/530/A138 : Geneva-Copenhagen survey re-analysis (Casagrande+, 2011)J/A+A/558/A38 : FAMA code stellar parameters and abundances (Magrini+, 2013)J/ApJ/769/57 : Equivalent widths of metal-poor stars (Frebel+, 2013)J/A+A/564/A119 : CoRoT red giants abundances (Morel+, 2014)J/A+A/564/A133 : Gaia FGK benchmark stars; metallicity (Jofre+, 2014)J/A+A/575/A26 : Properties of Population II star HD 140283 (Creevey+, 2015)J/MNRAS/450/397 : Spectroscopic study of RGs in Kepler field (Takeda+, 2015)J/A+A/587/A2 : SP_Ace derived data from stellar spectra (Boeche+, 2016)J/A+A/592/A70 : Gaia FGK stars; low-metallicities candidates (Hawkins+, 2016)J/AJ/151/144 : ASPCAP weight for 15 APOGEE chemical elements (Garcia+, 2016)J/A+A/608/A89 : Very metal poor stars in MW halo (Mashonkina+, 2017)J/ApJ/847/142 : Ultrametalpoor stars LTE & NLTE abundances (Ezzeddine+, 2017)J/A+A/612/A90 : Inelastic Fe+H collision data (Barklem, 2018)J/AJ/156/18 : APOGEE DR14;Binary comp. evolved stars (Price-Whelan+, 2018)J/ApJ/858/92 : RPA Southern Pilot Search of 107 Stars (Hansen+, 2018)J/ApJ/865/129 : Abundance analysis of HD 222925 (Roederer+, 2018)J/ApJ/868/110 : R-Process Alliance; DR1 in Galactic halo (Sakari+, 2018)J/A+A/625/A33 : Radial velocity time series of HD 122563 (Creevey+, 2019)J/A+A/628/A54 : Fe, Mg, Ti in Galactic clusters (Kovalev+, 2019)J/A+A/640/A25 : Metal-poor stars limb-darkening coeff. (Karovicova+, 2020)J/A+A/643/A83 : K2-Gaia-ESO stellar param. and abundances (Worley+, 2020)J/ApJ/898/150 : High-res. MIKE obs. of metal-poor stars (Ezzeddine+, 2020)J/ApJS/249/30 : R-Process Alliance; metal-poor star spectro (Holmbeck+, 2020)J/A+A/645/A106 : Atomic data for the Gaia-ESO Survey (Heiter+, 2021)J/A+A/650/A194 : Titans metal-poor reference stars. I. (Giribaldi+, 2021)J/A+A/658/A47 : Dwarf stars limb-darkening coefficients (Karovicova+, 2022)J/A+A/658/A48 : 7 giants/subgiants limb-darkening coeff (Karovicova, 2022)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/AJ/165/145https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/AJ/165/145http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/AJ/165/145https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/AJ/165/145https://vizier.iucaa.in/viz-bin/votable?-source=J/AJ/165/145http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/AJ/165/145GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/AJ/165/145/table3 (Derived stellar atmospheric parameters of the target stars)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/AJ/165/145/table3?https://vizier.iucaa.in/viz-bin/conesearch/J/AJ/165/145/table3?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/AJ/165/145/table3?GETtext/xml+votable180.050000true210.63268979.68609560.0055555555555555560/https://cdsarc.cds.unistra.fr/viz-bin/moc/J/AJ/165/145?format=asciiOpticaldefaultJ/AJ/165/145/table1FeI and FeII linelist selected for LOTUSSpeciesSpeciesmeta.notecharrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintWave[3440/8221] Wavelength, Angstroms0.1nmem.wlfloatExPot[0/5.1] Excitation potentialeVphys.atmol.excitationfloatloggf[-5.97/0.65] log, statistical weight*oscillator strengthstat.weight;phys.atmol.oscStrengthfloatJ/AJ/165/145/table3Derived stellar atmospheric parameters of the target starsRefReferences (3)meta.refcharrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintSubset[1/5] Subset (1)meta.noteintNameStar Name (2)meta.id;meta.maincharSimbadNameSimbad column added by the CDSmeta.idcharnullablee_Teff-LTE[15/289] Uncertainty in Teff-LTEKstat.errorintTeff-LTE[4270/6493] LTE Surface Effective Temperature, LTEKphys.temperature.effectiveintlogg-LTE[0.06/4.55] log, surface gravity, cgs, LTElog(cm.s**-2)phys.gravityfloate_logg-LTE[0.03/1] Uncertainty in logg-LTElog(cm.s**-2)stat.errorfloatFeH-LTE[-3.17/0.42] Metallicity, LTEphys.abund.Fefloate_FeH-LTE[0.01/0.3] Uncertainty in FeH-LTEstat.errorfloatvt-LTE[0.59/2.81] microturbulent velocity, LTEkm/sphys.velocfloate_vt-LTE[0.01/0.7] Uncertainty in vt-LTEkm/sstat.errorfloatNFeI-LTENumber, FeI lines, LTEmeta.numbercharNFeII-LTENumber, FeII lines, LTEmeta.numbercharChi-LTE[0/2.7] Cutoff, {chi}^2, LTEmeta.notefloatTeff-NLTE[4234/6407] Surface Effective Temperature, NLTEKphys.temperature.effectiveinte_Teff-NLTE[15/251] Uncertainty in Teff-LTEKstat.errorintlogg-NLTE[0.11/4.66] log, surface gravity, cgs, NLTElog(cm.s**-2)phys.gravityfloate_logg-NLTE[0.04/0.8] Uncertainty in logg-LTElog(cm.s**-2)stat.errorfloatFeH-NLTE[-3.01/0.45] Metallicity, NLTEphys.abund.Fefloate_FeH-NLTE[0.01/0.3] Uncertainty in FeH-LTEstat.errorfloatvt-NLTE[0.63/2.8] microturbulent velocity, NLTEkm/sphys.velocfloate_vt-NLTE[0.01/0.4] Uncertainty in vt-LTEkm/sstat.errorfloatNFeI-NLTENumber, FeI lines, NLTEmeta.numbercharNFeII-NLTENumber, FeII lines, NLTEmeta.numbercharChi-NLTE[0/2.7] Cutoff, {chi}^2^, NLTEmeta.notefloatSNR[19/850] Signal-to-Noisestat.snrfloat_RAPosition from SIMBAD (right ascension part)degpos.eq.ra;meta.main_DEPosition from SIMBAD (declination part)degpos.eq.dec;meta.main