The Payne: Self-consistent ab initio Fitting of Stellar Spectra

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dc.contributor.authorTing, Yuan-Sen
dc.contributor.authorConroy, Charlie
dc.contributor.authorRix, Hans-Walter
dc.contributor.authorCargile, Phillip A
dc.date.accessioned2022-11-30T03:16:48Z
dc.date.available2022-11-30T03:16:48Z
dc.date.issued2019
dc.date.updated2021-11-28T07:30:03Z
dc.description.abstractWe present The Payne, a general method for the precise and simultaneous determination of numerous stellar labels from observed spectra, based on fitting physical spectral models. The Payne combines a number of important methodological aspects: it exploits the information from much of the available spectral range; it fits all labels (stellar parameters and elemental abundances) simultaneously; it uses spectral models, where the structure of the atmosphere and the radiative transport are consistently calculated to reflect the stellar labels. At its core The Payne has an approach to accurate and precise interpolation and prediction of the spectrum in high-dimensional label space that is flexible and robust, yet based on only a moderate number of ab initio models ( for 25 labels). With a simple neural-net-like functional form and a suitable choice of training labels, this interpolation yields a spectral flux prediction good to 10-3 rms across a wide range of T eff and (including dwarfs and giants). We illustrate the power of this approach by applying it to the APOGEE DR14 data set, drawing on Kurucz models with recently improved line lists: without recalibration, we obtain physically sensible stellar parameters as well as 15 elemental abundances that appear to be more precise than the published APOGEE DR14 values. In short, The Payne is an approach that for the first time combines all these key ingredients, necessary for progress toward optimal modeling of survey spectra; and it leads to both precise and accurate estimates of stellar labels, based on physical models and without "recalibration." Both the codes and catalog are made publicly available online.en_AU
dc.description.sponsorshipNASA Headquarters under the NASA Earth and Space Science Fellowship Program— Grant NNX15AR83H for this project. C.C. acknowledges support from NASA grant NNX13AI46G, NSF grant AST1313280, and the Packard Foundation. H.W.R.ʼs research contribution is supported by the European Research Council under the European Union’s Seventh Framework Programme (FP 7) ERC grant Agreement No. [321035]en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn0004-637Xen_AU
dc.identifier.urihttp://hdl.handle.net/1885/281410
dc.language.isoen_AUen_AU
dc.provenancehttps://v2.sherpa.ac.uk/id/publication/6401/..."published version can be archived in institutional repository" from Sherpa/Romeo site as at 30/11/2022en_AU
dc.publisherIOP Publishingen_AU
dc.relationhttp://purl.org/au-research/grants/arc/DP160103747en_AU
dc.rights© 2019 The authorsen_AU
dc.sourceThe Astrophysical Journalen_AU
dc.subjectmethodsen_AU
dc.subjectdata analysis – starsen_AU
dc.subjectabundances – techniquesen_AU
dc.subjectspectroscopic Supporting materialen_AU
dc.subjectmachine-readable tableen_AU
dc.titleThe Payne: Self-consistent ab initio Fitting of Stellar Spectraen_AU
dc.typeJournal articleen_AU
dcterms.accessRightsOpen Accessen_AU
local.bibliographicCitation.issue69en_AU
local.bibliographicCitation.lastpage22en_AU
local.bibliographicCitation.startpage1en_AU
local.contributor.affiliationTing, Yuan-Sen, College of Science, ANUen_AU
local.contributor.affiliationConroy, Charlie, Harvard-Smithsonian Center for Astrophysicsen_AU
local.contributor.affiliationRix, Hans-Walter, Max Planck Institute for Astronomyen_AU
local.contributor.affiliationCargile, Phillip A, Harvard-Smithsonian Center for Astrophysicsen_AU
local.contributor.authoremailu5043815@anu.edu.auen_AU
local.contributor.authoruidTing, Yuan-Sen, u5043815en_AU
local.description.notesImported from ARIESen_AU
local.identifier.absfor510109 - Stellar astronomy and planetary systemsen_AU
local.identifier.absfor461104 - Neural networksen_AU
local.identifier.absfor460207 - Modelling and simulationen_AU
local.identifier.absseo280115 - Expanding knowledge in the information and computing sciencesen_AU
local.identifier.absseo280120 - Expanding knowledge in the physical sciencesen_AU
local.identifier.ariespublicationu3102795xPUB4465en_AU
local.identifier.citationvolume879en_AU
local.identifier.doi10.3847/1538-4357/ab2331en_AU
local.identifier.scopusID2-s2.0-85071870075
local.identifier.uidSubmittedByu3102795en_AU
local.publisher.urlhttps://iopscience.iop.org/en_AU
local.type.statusPublished Versionen_AU

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