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The BAyesian STellar algorithm (BASTA) : A fitting tool for stellar studies, asteroseismology, exoplanets, and Galactic archaeology

Aguirre Børsen-Koch, V. ; Rørsted, J. L. ; Justesen, A. B. LU ; Stokholm, A. ; Verma, K. ; Winther, M. L. ; Knudstrup, E. ; Nielsen, K. B. ; Sahlholdt, C. LU and Larsen, J. R. , et al. (2022) In Monthly Notices of the Royal Astronomical Society 509(3). p.4344-4364
Abstract

We introduce the public version of the BAyesian STellar Algorithm (BASTA), an open-source code written in Python to determine stellar properties based on a set of astrophysical observables. BASTA has been specifically designed to robustly combine large data sets that include asteroseismology, spectroscopy, photometry, and astrometry. We describe the large number of asteroseismic observations that can be fit by the code and how these can be combined with atmospheric properties (as well as parallaxes and apparent magnitudes), making it the most complete analysis pipeline available for oscillating main-sequence, subgiant, and red giant stars. BASTA relies on a set of pre-built stellar isochrones or a custom-designed library of stellar... (More)

We introduce the public version of the BAyesian STellar Algorithm (BASTA), an open-source code written in Python to determine stellar properties based on a set of astrophysical observables. BASTA has been specifically designed to robustly combine large data sets that include asteroseismology, spectroscopy, photometry, and astrometry. We describe the large number of asteroseismic observations that can be fit by the code and how these can be combined with atmospheric properties (as well as parallaxes and apparent magnitudes), making it the most complete analysis pipeline available for oscillating main-sequence, subgiant, and red giant stars. BASTA relies on a set of pre-built stellar isochrones or a custom-designed library of stellar tracks, which can be further refined using our interpolation method (both along and across stellar tracks or isochrones). We perform recovery tests with simulated data that reveal levels of accuracy at the few percent level for radii, masses, and ages when individual oscillation frequencies are considered, and show that asteroseismic ages with statistical uncertainties below 10 per cent are within reach if our stellar models are reliable representations of stars. BASTAis extensively documented and includes a suite of examples to support easy adoption and further development by new users.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
asteroseismology, methods: numerical, methods: statistical, stars: fundamental parameters
in
Monthly Notices of the Royal Astronomical Society
volume
509
issue
3
pages
21 pages
publisher
Oxford University Press
external identifiers
  • scopus:85122323583
ISSN
0035-8711
DOI
10.1093/mnras/stab2911
language
English
LU publication?
yes
id
2ad390ef-7106-4f5f-97b0-e274ffac3bce
date added to LUP
2022-02-02 11:44:46
date last changed
2023-01-01 19:33:35
@article{2ad390ef-7106-4f5f-97b0-e274ffac3bce,
  abstract     = {{<p>We introduce the public version of the BAyesian STellar Algorithm (BASTA), an open-source code written in Python to determine stellar properties based on a set of astrophysical observables. BASTA has been specifically designed to robustly combine large data sets that include asteroseismology, spectroscopy, photometry, and astrometry. We describe the large number of asteroseismic observations that can be fit by the code and how these can be combined with atmospheric properties (as well as parallaxes and apparent magnitudes), making it the most complete analysis pipeline available for oscillating main-sequence, subgiant, and red giant stars. BASTA relies on a set of pre-built stellar isochrones or a custom-designed library of stellar tracks, which can be further refined using our interpolation method (both along and across stellar tracks or isochrones). We perform recovery tests with simulated data that reveal levels of accuracy at the few percent level for radii, masses, and ages when individual oscillation frequencies are considered, and show that asteroseismic ages with statistical uncertainties below 10 per cent are within reach if our stellar models are reliable representations of stars. BASTAis extensively documented and includes a suite of examples to support easy adoption and further development by new users. </p>}},
  author       = {{Aguirre Børsen-Koch, V. and Rørsted, J. L. and Justesen, A. B. and Stokholm, A. and Verma, K. and Winther, M. L. and Knudstrup, E. and Nielsen, K. B. and Sahlholdt, C. and Larsen, J. R. and Cassisi, S. and Serenelli, A. M. and Casagrande, L. and Christensen-Dalsgaard, J. and Davies, G. R. and Ferguson, J. W. and Lund, M. N. and Weiss, A. and White, T. R.}},
  issn         = {{0035-8711}},
  keywords     = {{asteroseismology; methods: numerical; methods: statistical; stars: fundamental parameters}},
  language     = {{eng}},
  month        = {{01}},
  number       = {{3}},
  pages        = {{4344--4364}},
  publisher    = {{Oxford University Press}},
  series       = {{Monthly Notices of the Royal Astronomical Society}},
  title        = {{The BAyesian STellar algorithm (BASTA) : A fitting tool for stellar studies, asteroseismology, exoplanets, and Galactic archaeology}},
  url          = {{http://dx.doi.org/10.1093/mnras/stab2911}},
  doi          = {{10.1093/mnras/stab2911}},
  volume       = {{509}},
  year         = {{2022}},
}