Performance of the <i>Stellar Abundances and atmospheric Parameters Pipeline</i> adapted for M dwarfs

Context. M dwarfs are important targets in the search for Earth-like exoplanets due to their small masses and low luminosities. Several ongoing and upcoming space missions are targeting M dwarfs for this reason, and the ESA P LATO mission is one of these. Aims. In order to fully characterise a planetary system the properties of the host star must be known. For M dwarfs we can derive effective temperature, surface gravity, metallicity, and abundances of various elements from spectroscopic observations in combination with photometric data. Methods. The Stellar Abundances and atmospheric Parameters Pipeline (SAPP) has been developed to serve as a prototype for one of the stellar science software within the P LATO consortium. The pipeline combines results from a spectroscopy, a photometry, an interferometry, and an asteroseismology module to derive stellar parameters for FGK-type stars. We have modified the pipeline to be able to analyse the M dwarf part of the P LATO target sample. The current version of the pipeline for M dwarfs mostly relies on spectroscopic observations. The module processing these data is based on the machine learning algorithm The Payne and fits a grid of model spectra to an observed spectrum to derive effective temperature and metallicity. We use spectra in the H-band, as the nearinfrared region is beneficial for M dwarfs because there are fewer molecular lines and they are brighter in this wavelength region than in the optical. A method based on synthetic spectra was developed for the continuum normalisation of the spectra, taking into account the pseudo-continuum formed by numerous lines of the water molecule. Photometry is used to constrain the surface gravity. Results. We tested the modified SAPP on spectra of M dwarfs from the APOGEE survey. Our validation sample of 26 stars includes stars with interferometric observations and binaries. We found a good agreement between our derived values and reference values from a range of previous studies. We estimate the overall uncertainties in the derived effective temperature, surface gravity, and metallicity to be 100 K, 0.1 dex, and 0.15 dex, respectively. Conclusions. We find that the modified SAPP performs well on M dwarfs and identify possible areas of future development that should lead to an improved precision of the derived stellar parameters.

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Publication Details

Journal
Astronomy and Astrophysics
Published
2025-03-12
DOI
https://doi.org/10.1051/0004-6361/202452048
Citations
3
Primary Topic
Stellar, planetary, and galactic studies
Type
article
Field-Weighted Citation Impact
3.46

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article

Performance of the Stellar Abundances and atmospheric Parameters Pipeline adapted for M dwarfs

M. Bergemann, U. Heiter, Terese Olander, Mikhail Kovalev et al.
3 citations
Astronomy and Astrophysics
Stellar, planetary, and galactic studies
3.46
article

Performance of the Stellar Abundances and atmospheric Parameters Pipeline adapted for M dwarfs

M. Bergemann, U. Heiter, Terese Olander, Mikhail Kovalev, S. Cassisi, E. Delgado Mena, Bárbara Rojas-Ayala, O. Kochukhov, N J Miller, Ekaterina Magg, Diogo Souto, Haiyang Wang, Thierry Morel, Matthew R. Gent, Yutong Shan
article en
3 citations

Abstract

Context. M dwarfs are important targets in the search for Earth-like exoplanets due to their small masses and low luminosities. Several ongoing and upcoming space missions are targeting M dwarfs for this reason, and the ESA P LATO mission is one of these. Aims. In order to fully characterise a planetary system the properties of the host star must be known. For M dwarfs we can derive effective temperature, surface gravity, metallicity, and abundances of various elements from spectroscopic observations in combination with photometric data. Methods. The Stellar Abundances and atmospheric Parameters Pipeline (SAPP) has been developed to serve as a prototype for one of the stellar science software within the P LATO consortium. The pipeline combines results from a spectroscopy, a photometry, an interferometry, and an asteroseismology module to derive stellar parameters for FGK-type stars. We have modified the pipeline to be able to analyse the M dwarf part of the P LATO target sample. The current version of the pipeline for M dwarfs mostly relies on spectroscopic observations. The module processing these data is based on the machine learning algorithm The Payne and fits a grid of model spectra to an observed spectrum to derive effective temperature and metallicity. We use spectra in the H-band, as the nearinfrared region is beneficial for M dwarfs because there are fewer molecular lines and they are brighter in this wavelength region than in the optical. A method based on synthetic spectra was developed for the continuum normalisation of the spectra, taking into account the pseudo-continuum formed by numerous lines of the water molecule. Photometry is used to constrain the surface gravity. Results. We tested the modified SAPP on spectra of M dwarfs from the APOGEE survey. Our validation sample of 26 stars includes stars with interferometric observations and binaries. We found a good agreement between our derived values and reference values from a range of previous studies. We estimate the overall uncertainties in the derived effective temperature, surface gravity, and metallicity to be 100 K, 0.1 dex, and 0.15 dex, respectively. Conclusions. We find that the modified SAPP performs well on M dwarfs and identify possible areas of future development that should lead to an improved precision of the derived stellar parameters.

Astronomy and AstrophysicsVol. 696
Uppsala University (SE), Centre National de la Recherche Scientifique (FR), University of Liège (BE), Kunming Institute of Zoology (CN), University of Oslo (NO), University of Tarapacá (CL), Universidade Federal de Sergipe (BR), Yunnan Observatories (CN), Institute of Astrophysics and Space Sciences (PT), Blue Planet (Norway) (NO), Max Planck Institute for Astronomy (DE), Collurania Teramo Observatory (IT), Centro de Astrobiología (ES), Geocenter Denmark (DK), Istituto Nazionale di Fisica Nucleare, Sezione di Pisa (IT), Institut de Recherche en Astrophysique et Planétologie (FR), University of Göttingen (DE)
Smithsonian Institution, U.S. Department of Energy, Alfred P. Sloan Foundation, Yale University, Carnegie Institution of Washington, Vanderbilt University, Ohio State University, University of Utah, University of Washington, Johns Hopkins University, Carnegie Mellon University, University of Notre Dame, University of Portsmouth, New Mexico State University, European Space Agency, York University, University of Oxford, European Commission, Deutsche Forschungsgemeinschaft, Royal Swedish Academy of Sciences, Swedish National Space Agency, Belgian Federal Science Policy Office, Ministério da Ciência, Tecnologia e Inovação, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Max-Planck-Gesellschaft, Vetenskapsrådet, Universidad Nacional Autónoma de México, Uppsala Universitet, Agencia Nacional de Investigación y Desarrollo, Max-Planck-Institut für Astrophysik, Max-Planck-Institut für Astronomie, Instituto de Astrofísica de Canarias, Office of Science, University of Colorado Boulder, European Research Council, Leibniz-Gemeinschaft, Agencia Estatal de Investigación, European Social Fund, Lawrence Berkeley National Laboratory
Openalex Percentile: Top 9%
Stellar, planetary, and galactic studies
3.46
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