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Tutorial: Asteroseismic Stellar Modelling with AIMS

  • Mikkel N. LundEmail author
  • Daniel R. Reese
Conference paper
Part of the Astrophysics and Space Science Proceedings book series (ASSSP, volume 49)

Abstract

The goal of aims (Asteroseismic Inference on a Massive Scale) is to estimate stellar parameters and credible intervals/error bars in a Bayesian manner from a set of asteroseismic frequency data and so-called classical constraints. To achieve reliable parameter estimates and computational efficiency, it searches through a grid of pre-computed models using an MCMC algorithm—interpolation within the grid of models is performed by first tessellating the grid using a Delaunay triangulation and then doing a linear barycentric interpolation on matching simplexes. Inputs for the modelling consist of individual frequencies from peak-bagging, which can be complemented with classical spectroscopic constraints. aims is mostly written in Python with a modular structure to facilitate contributions from the community. Only a few computationally intensive parts have been rewritten in Fortran in order to speed up calculations.

Notes

Acknowledgements

aims is a software for fitting stellar pulsation data, developed in the context of the SPACEINN network, funded by the European Commission’s Seventh Framework Programme. DRR wishes to thank all those who helped him in the development of aims, including D. Bossini, T.L. Campante, W.J. Chaplin, H.R. Coelho, G.R. Davies, B.D.C.P. Herbert, J.S. Kuszlewicz, M.W. Long, M.N. Lund, and A. Miglio.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.School of Physics and AstronomyUniversity of BirminghamBirminghamUK
  2. 2.LESIA, Observatoire de ParisPSL Ressearch University, CNRS, Sorbonne UniversitésSorbonne Paris CitéeFrance

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