The SAPP pipeline for the determination of stellar abundances and atmospheric parameters of stars in the core program of the PLATO mission Article Swipe
Matthew Raymond Gent
,
M. Bergemann
,
Aldo Serenelli
,
L. Casagrande
,
Jeffrey M. Gerber
,
U. Heiter
,
Mikhail Kovalev
,
T. Morel
,
N. Nardetto
,
V. Adibekyan
,
V. Silva Aguirre
,
M. Asplund
,
K. Belkacem
,
C. del Burgo
,
Lionel Bigot
,
A. Chiavassa
,
Luisa Fernanda Rodríguez Díaz
,
C. Pinçon
,
J. I. Gónzalez Hernández
,
D. Mourard
,
T. Merle
,
Szabolcs Mészáros
,
D. J. Marshall
,
R. M. Ouazzani
,
B. Plez
,
D. R. Reese
,
Regner Trampedach
,
M. Tsantaki
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1051/0004-6361/202140863
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1051/0004-6361/202140863
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 temperature, surface gravity, metallicity, chemical abundances, and luminosity. The code in its more general version has a much wider range of potential applications. It can also provide masses, ages, and radii of stars and can be used with stellar types not targeted by the PLATO core program, such as red giants. We validate the code on a set of 27 benchmark stars that includes 19 FGK-type dwarfs, 6 GK-type subgiants, and 2 red giants. Our results suggest that combining various observables is the optimal approach, as 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 sample, we obtain a typical uncertainty of 27 (syst.) ± 37 (stat.) K for T eff , 0.00 ± 0.01 dex for log g , 0.02 ± 0.02 dex for metallicity [Fe/H], −0.01 ± 0.03 R ⊙ for radii, −0.01 ± 0.05 M ⊙ for stellar masses, and −0.14 ± 0.63 Gyr for ages. We also show that the best results are obtained by combining the ν max scaling relation with stellar spectra. This resolves the notorious problem of degeneracies, which is particularly important for F-type stars.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1051/0004-6361/202140863
- https://www.aanda.org/articles/aa/pdf/2022/02/aa40863-21.pdf
- OA Status
- hybrid
- References
- 153
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3214533070
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3214533070Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1051/0004-6361/202140863Digital Object Identifier
- Title
-
The SAPP pipeline for the determination of stellar abundances and atmospheric parameters of stars in the core program of the PLATO missionWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-11-22Full publication date if available
- Authors
-
Matthew Raymond Gent, M. Bergemann, Aldo Serenelli, L. Casagrande, Jeffrey M. Gerber, U. Heiter, Mikhail Kovalev, T. Morel, N. Nardetto, V. Adibekyan, V. Silva Aguirre, M. Asplund, K. Belkacem, C. del Burgo, Lionel Bigot, A. Chiavassa, Luisa Fernanda Rodríguez Díaz, C. Pinçon, J. I. Gónzalez Hernández, D. Mourard, T. Merle, Szabolcs Mészáros, D. J. Marshall, R. M. Ouazzani, B. Plez, D. R. Reese, Regner Trampedach, M. TsantakiList of authors in order
- Landing page
-
https://doi.org/10.1051/0004-6361/202140863Publisher landing page
- PDF URL
-
https://www.aanda.org/articles/aa/pdf/2022/02/aa40863-21.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://www.aanda.org/articles/aa/pdf/2022/02/aa40863-21.pdfDirect OA link when available
- Concepts
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Physics, Metallicity, Stars, Astrophysics, Surface gravity, Luminosity, Effective temperature, Observable, Galaxy, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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153Number of works referenced by this work
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20Other works algorithmically related by OpenAlex
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| abstract_inverted_index.M | 199 |
| abstract_inverted_index.R | 192 |
| abstract_inverted_index.T | 171 |
| abstract_inverted_index.a | 61, 101, 160 |
| abstract_inverted_index.g | 180 |
| abstract_inverted_index.19 | 109 |
| abstract_inverted_index.27 | 104, 164 |
| abstract_inverted_index.37 | 167 |
| abstract_inverted_index.It | 68 |
| abstract_inverted_index.We | 0, 96, 211 |
| abstract_inverted_index.as | 93, 130 |
| abstract_inverted_index.be | 17, 80, 139 |
| abstract_inverted_index.by | 87, 220 |
| abstract_inverted_index.in | 55 |
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| abstract_inverted_index.of | 12, 22, 29, 65, 76, 103, 146, 163, 235 |
| abstract_inverted_index.on | 38, 100 |
| abstract_inverted_index.to | 19, 138 |
| abstract_inverted_index.we | 158 |
| abstract_inverted_index.± | 166, 175, 183, 190, 197, 206 |
| abstract_inverted_index.ν | 223 |
| abstract_inverted_index.For | 153 |
| abstract_inverted_index.Gyr | 208 |
| abstract_inverted_index.Our | 119 |
| abstract_inverted_index.The | 34, 53 |
| abstract_inverted_index.and | 6, 42, 51, 74, 78, 115, 141, 149, 204 |
| abstract_inverted_index.are | 218 |
| abstract_inverted_index.can | 69, 79 |
| abstract_inverted_index.dex | 177, 185 |
| abstract_inverted_index.eff | 172 |
| abstract_inverted_index.for | 170, 178, 186, 194, 201, 209, 241 |
| abstract_inverted_index.has | 60 |
| abstract_inverted_index.its | 56 |
| abstract_inverted_index.log | 179 |
| abstract_inverted_index.max | 224 |
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| abstract_inverted_index.red | 94, 117 |
| abstract_inverted_index.set | 102 |
| abstract_inverted_index.the | 2, 10, 13, 26, 30, 39, 88, 98, 127, 133, 154, 215, 222, 232 |
| abstract_inverted_index.⊙ | 193, 200 |
| abstract_inverted_index.0.00 | 174 |
| abstract_inverted_index.0.01 | 176 |
| abstract_inverted_index.0.02 | 182, 184 |
| abstract_inverted_index.0.03 | 191 |
| abstract_inverted_index.0.05 | 198 |
| abstract_inverted_index.0.63 | 207 |
| abstract_inverted_index.SAPP | 3 |
| abstract_inverted_index.This | 230 |
| abstract_inverted_index.also | 70, 212 |
| abstract_inverted_index.best | 216 |
| abstract_inverted_index.code | 14, 54, 99 |
| abstract_inverted_index.core | 27, 90, 156 |
| abstract_inverted_index.more | 57, 143, 150 |
| abstract_inverted_index.much | 62 |
| abstract_inverted_index.show | 213 |
| abstract_inverted_index.such | 92 |
| abstract_inverted_index.that | 15, 107, 122, 214 |
| abstract_inverted_index.this | 131 |
| abstract_inverted_index.used | 18, 81 |
| abstract_inverted_index.will | 16 |
| abstract_inverted_index.with | 82, 227 |
| abstract_inverted_index.PLATO | 31, 89, 155 |
| abstract_inverted_index.ages, | 73 |
| abstract_inverted_index.ages. | 210 |
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| abstract_inverted_index.radii | 75 |
| abstract_inverted_index.range | 64 |
| abstract_inverted_index.space | 32 |
| abstract_inverted_index.stars | 23, 77, 106 |
| abstract_inverted_index.types | 84 |
| abstract_inverted_index.which | 237 |
| abstract_inverted_index.wider | 63 |
| abstract_inverted_index.F-type | 242 |
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| abstract_inverted_index.broken | 140 |
| abstract_inverted_index.obtain | 159 |
| abstract_inverted_index.radii, | 195 |
| abstract_inverted_index.stars. | 243 |
| abstract_inverted_index.values | 145 |
| abstract_inverted_index.within | 25 |
| abstract_inverted_index.yields | 142 |
| abstract_inverted_index.(stat.) | 168 |
| abstract_inverted_index.(syst.) | 165 |
| abstract_inverted_index.GK-type | 113 |
| abstract_inverted_index.[Fe/H], | 188 |
| abstract_inverted_index.between | 135 |
| abstract_inverted_index.dwarfs, | 111 |
| abstract_inverted_index.general | 58 |
| abstract_inverted_index.giants. | 95, 118 |
| abstract_inverted_index.masses, | 72, 203 |
| abstract_inverted_index.optimal | 128 |
| abstract_inverted_index.problem | 234 |
| abstract_inverted_index.program | 28 |
| abstract_inverted_index.provide | 71 |
| abstract_inverted_index.results | 120, 217 |
| abstract_inverted_index.sample, | 157 |
| abstract_inverted_index.scaling | 225 |
| abstract_inverted_index.stellar | 83, 147, 202, 228 |
| abstract_inverted_index.suggest | 121 |
| abstract_inverted_index.surface | 46 |
| abstract_inverted_index.typical | 161 |
| abstract_inverted_index.various | 124 |
| abstract_inverted_index.version | 59 |
| abstract_inverted_index.−0.01 | 189, 196 |
| abstract_inverted_index.−0.14 | 205 |
| abstract_inverted_index.(Stellar | 4 |
| abstract_inverted_index.Bayesian | 40 |
| abstract_inverted_index.FGK-type | 110 |
| abstract_inverted_index.accurate | 144 |
| abstract_inverted_index.chemical | 49 |
| abstract_inverted_index.gravity, | 47 |
| abstract_inverted_index.includes | 108 |
| abstract_inverted_index.mission. | 33 |
| abstract_inverted_index.observed | 24 |
| abstract_inverted_index.obtained | 219 |
| abstract_inverted_index.pipeline | 35 |
| abstract_inverted_index.program, | 91 |
| abstract_inverted_index.provides | 43 |
| abstract_inverted_index.relation | 226 |
| abstract_inverted_index.resolves | 231 |
| abstract_inverted_index.spectra. | 229 |
| abstract_inverted_index.targeted | 86 |
| abstract_inverted_index.validate | 97 |
| abstract_inverted_index.approach, | 129 |
| abstract_inverted_index.benchmark | 105 |
| abstract_inverted_index.combining | 123, 221 |
| abstract_inverted_index.determine | 20 |
| abstract_inverted_index.different | 136 |
| abstract_inverted_index.effective | 44 |
| abstract_inverted_index.important | 240 |
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| abstract_inverted_index.introduce | 1 |
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| abstract_inverted_index.potential | 66 |
| abstract_inverted_index.prototype | 11 |
| abstract_inverted_index.realistic | 151 |
| abstract_inverted_index.Abundances | 5 |
| abstract_inverted_index.Parameters | 8 |
| abstract_inverted_index.Pipeline), | 9 |
| abstract_inverted_index.parameters | 21, 137, 148 |
| abstract_inverted_index.subgiants, | 114 |
| abstract_inverted_index.abundances, | 50 |
| abstract_inverted_index.atmospheric | 7 |
| abstract_inverted_index.luminosity. | 52 |
| abstract_inverted_index.metallicity | 187 |
| abstract_inverted_index.observables | 125 |
| abstract_inverted_index.uncertainty | 162 |
| abstract_inverted_index.degeneracies | 134 |
| abstract_inverted_index.metallicity, | 48 |
| abstract_inverted_index.particularly | 239 |
| abstract_inverted_index.temperature, | 45 |
| abstract_inverted_index.applications. | 67 |
| abstract_inverted_index.degeneracies, | 236 |
| abstract_inverted_index.uncertainties. | 152 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 28 |
| citation_normalized_percentile.value | 0.17008798 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |