BONNSAI: a Bayesian tool for comparing stars with stellar evolution models
Fabian R. N. Schneider, Norbert Langer, Alex de Koter, Ines Brott,, Robert G. Izzard, Herbert H.B. Lau

TL;DR
BONNSAI is a Bayesian tool that compares stellar observations with models, enabling parameter estimation, model testing, and prediction while accounting for uncertainties and prior knowledge.
Contribution
It introduces a flexible Bayesian framework for analyzing stellar data against models, supporting multiple applications and testing stellar evolution theories.
Findings
Successfully tested on mock stars.
Reproduces Milky Way binary star ages accurately.
Supports models for different galaxy compositions.
Abstract
Powerful telescopes equipped with multi-fibre or integral field spectrographs combined with detailed models of stellar atmospheres and automated fitting techniques allow for the analysis of large number of stars. These datasets contain a wealth of information that require new analysis techniques to bridge the gap between observations and stellar evolution models. To that end, we develop BONNSAI (BONN Stellar Astrophysics Interface), a Bayesian statistical method, that is capable of comparing all available observables simultaneously to stellar models while taking observed uncertainties and prior knowledge such as initial mass functions and distributions of stellar rotational velocities into account. BONNSAI can be used to (1) determine probability distributions of fundamental stellar parameters such as initial masses and stellar ages from complex datasets, (2) predict stellar parameters…
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