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The SAPP pipeline for the determination of stellar abundances and atmospheric parameters of stars in the core program of the PLATO mission

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DOI

  • Matthew Raymond Gent, Max Planck Institute for Astronomy
  • ,
  • Maria Bergemann, Max Planck Institute for Astronomy, Københavns Universitet
  • ,
  • Aldo Serenelli, Max Planck Institute for Astronomy, Institute of Space Studies of Catalonia, Institut d'Estudis Espacials de Catalunya (IEEC)
  • ,
  • Luca Casagrande, Australian National University
  • ,
  • Jeffrey M. Gerber, Max Planck Institute for Astronomy
  • ,
  • Ulrike Heiter, Uppsala University
  • ,
  • Mikhail Kovalev, Max Planck Institute for Astronomy, CAS - National Astronomical Observatories
  • ,
  • Thierry Morel, University of Liege
  • ,
  • Nicolas Nardetto, Observatoire de la Cote d'Azur
  • ,
  • Vardan Adibekyan, Eotvos Lorand University, University of Porto
  • ,
  • Víctor Silva Aguirre
  • ,
  • Martin Asplund, Max Planck Institute for Astrophysics
  • ,
  • Kevin Belkacem, LESIA, Observatoire de Paris
  • ,
  • Carlos Del Burgo, Instituto Nacional de Astrofisica Optica y Electronica, Instituto Astrofisico de Canarias
  • ,
  • Lionel Bigot, Observatoire de la Cote d'Azur
  • ,
  • Andrea Chiavassa, Observatoire de la Cote d'Azur
  • ,
  • Luisa Fernanda Rodríguez Díaz
  • Marie Jo Goupil, LESIA, Observatoire de Paris
  • ,
  • Jonay I.González Hernández, Instituto Astrofisico de Canarias, University of La Laguna
  • ,
  • Denis Mourard, Observatoire de la Cote d'Azur
  • ,
  • Thibault Merle, Université Libre de Bruxelles
  • ,
  • Szabolcs Mészáros, Eotvos Lorand University, MTA-ELTE Lendület Milky Way Research Group
  • ,
  • Douglas J. Marshall, Universite Toulouse III - Paul Sabatier, IRAP
  • ,
  • Rhita Maria Ouazzani, LESIA, Observatoire de Paris
  • ,
  • Bertrand Plez, Universite de Montpellier
  • ,
  • Daniel Reese, LESIA, Observatoire de Paris
  • ,
  • Regner Trampedach, Space Science Institute
  • ,
  • Maria Tsantaki, Osservatorio Astrofisico Di Arcetri, Florence

We introduce the SAPP (Stellar Abundances and atmospheric Parameters Pipeline)the prototype of the code that will be used to determine parameters of stars observed within the core program of the PLATO space mission. The pipeline is based on the Bayesian inference and provides effective temperaturesurface gravitymetallicitychemical abundancesand luminosity. The code in its more general version has a much wider range of potential applications. It can also provide massesagesand radii of stars and can be used with stellar types not targeted by the PLATO core programsuch as red giants. We validate the code on a set of 27 benchmark stars that includes 19 FGK-type dwarfs6 GK-type subgiantsand 2 red giants. Our results suggest that combining various observables is the optimal approachas this allows the degeneracies between different parameters to be broken and yields more accurate values of stellar parameters and more realistic uncertainties. For the PLATO core samplewe obtain a typical uncertainty of 27 (syst.) ± 37 (stat.) K for Teff0.00 ± 0.01 dex for log g0.02 ± 0.02 dex for metallicity [Fe/H]-0.01 ± 0.03 Rfor radii-0.01 ± 0.05 Mfor stellar massesand -0.14 ± 0.63 Gyr for ages. We also show that the best results are obtained by combining the νmaxscaling relation with stellar spectra. This resolves the notorious problem of degeneracieswhich is particularly important for F-type stars.

OriginalsprogEngelsk
ArtikelnummerA147
TidsskriftAstronomy and Astrophysics
Vol/bind658
ISSN0004-6361
DOI
StatusUdgivet - feb. 2022

Bibliografisk note

Funding Information:
Funding for the DPAC has been provided by national institutionsin particular the institutions participating in the Gaia Multilateral Agreement. A.S. acknowledges support from MICINN grant PID2019- 108709GB-I00. T.M. acknowledges financial support from Belspo for contract PRODEX PLATO mission development. U.H. acknowledges support from the Swedish National Space Agency (SNSA/Rymdstyrelsen). S.M. has been supported by the J?nos Bolyai Research Scholarship of the Hungarian Academy of Sciencesand by the ?NKP-20-5 New National Excellence Program of the Ministry for Innovation and Technology. N.N. acknowledges Anthony Salsi for useful discussions. V.A. is supported by FCT - Funda??o para a Ci?ncia e Tecnologia (FCT) through national grants: UID/FIS/04434/2019; UIDB/04434/2020; UIDP/04434/2020. V.A. also acknowledges the support from FCT through Investigador FCT contract nr. IF/00650/2015/CP1273/CT0001. M.T. acknowledges the funding from MIUR Premiale 2016: MITIC. L.C. is the recipient of the ARC Future Fellowship FT160100402. M.B. is supported through the Lise Meitner grant from the Max Planck Society. We acknowledge support by the Collaborative Research centre SFB 881 (projects A5A10)Heidelberg Universityof the Deutsche Forschungsgemeinschaft (DFGGerman Research Foundation). This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement No. 949173).

Funding Information:
Acknowledgements. This work presents results from the European Space Agency (ESA) space mission PLATO. The PLATO payload, the PLATO Ground Segment and PLATO data processing are joint developments of ESA and the PLATO Mission Consortium (PMC). Funding for the PMC is provided at national levels, in particular by countries participating in the PLATO Multilateral Agreement (Austria, Belgium, Czech Republic, Denmark, France, Germany, Italy, Netherlands, Portugal, Spain, Sweden, Switzerland, Norway, and United Kingdom) and institutions from Brazil. Members of the PLATO Consortium can be found at https://platomission.com. The ESA PLATO mission website is https://www.cosmos.esa.int/plato. We thank the teams working for PLATO for all their work. We thank P.E. Nissen for providing the reduced spectra of the Kepler legacy stars. M.R.G., M.B., J.G., and M.K. are supported by the Lise Meitner grant from the Max Planck Society. B.P. is partially supported by CNES, the Centre National d’Études Spatiales. We acknowledge support by the Collaborative Research centre SFB 881 (projects A5, A10), Heidelberg University, of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). We thank C. Aerts for providing helpful comments to this study. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/ web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. A.S. acknowledges support from MICINN grant PID2019-108709GB-I00. T.M. acknowledges financial support from Belspo for contract PRODEX PLATO mission development. U.H. acknowledges support from the Swedish National Space Agency (SNSA/Rymdstyrelsen). S.M. has been supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, and by the ÚNKP-20-5 New National Excellence Program of the Ministry for Innovation and Technology. N.N. acknowledges Anthony Salsi for useful discussions. V.A. is supported by FCT – Fundação para a Ciência e Tecnolo-gia (FCT) through national grants: UID/FIS/04434/2019; UIDB/04434/2020; UIDP/04434/2020. V.A. also acknowledges the support from FCT through Inves-tigador FCT contract nr. IF/00650/2015/CP1273/CT0001. M.T. acknowledges the funding from MIUR Premiale 2016: MITIC. L.C. is the recipient of the ARC Future Fellowship FT160100402. M.B. is supported through the Lise Meitner grant from the Max Planck Society. We acknowledge support by the Collaborative Research centre SFB 881 (projects A5, A10), Heidelberg University, of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 949173).

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