Determining stellar properties of massive stars in NGC346 in the SMC with a Bayesian statistic technique
M. J. Rickard, R. Hainich, D. Pauli, W.-R. Hamann, L. M. Oskinova, R., K. Prinja, V. Ramachandran, H. Todt, E. C. Sch\"osser, A. A. C. Sander, P., Zeidler

TL;DR
This study employs a Bayesian statistical method to accurately determine fundamental stellar parameters of massive stars in NGC 346, overcoming spectral degeneracies and identifying binaries in a low-metallicity environment.
Contribution
It introduces a Bayesian technique that simultaneously fits temperature, gravity, and rotational velocity, improving parameter estimation for massive stars in the SMC.
Findings
Derived stellar parameters for 34 OB stars in NGC 346.
Identified a binary fraction of at least 46%.
Validated the Bayesian method for low-resolution spectra in low-metallicity environments.
Abstract
NGC 346 is a young cluster with numerous hot OB stars. It is part of the Small Magellanic Cloud (SMC), and has an average metallicity that is one-seventh of the Milky Way's. A detailed study of its stellar content provides a unique opportunity to understand the stellar and wind properties of massive stars in low-metallicity environments, and enables us to improve our understanding of star formation and stellar evolution. The fundamental stellar parameters defining a star's spectral appearance are its effective surface temperature, surface gravity, and projected rotational velocity. Unfortunately, these parameters cannot be obtained independently from only H and He spectral features as they are partially degenerate. With this work we aim to overcome this degeneracy by applying a newly developed Bayesian statistic technique that can fit these three parameters simultaneously.…
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