Determining stellar properties of massive stars in NGC346 in the SMC with a Bayesian statistic technique

Context . 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. Aims . 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. Methods . Multi-epoch optical spectra are used in combination with a Bayesian statistic technique to fit stellar properties based on a publicly available grid of synthetic spectra of stellar atmospheres. The use of all of the multi-epoch observations simultaneously allows the identification of binaries. Results . The stellar parameters for 34 OB stars within the core of NGC 346 are derived and presented here. By the use of both He I and He II lines, the partial degeneracy between the stellar parameters of effective surface temperature, surface gravity, and projected rotational velocity is overcome. A lower limit to the binary fraction of the sample of stars is found to be at least 46%. Conclusions . Based on comparisons with analysis conducted on an overlapping sample of stars within NGC 346, the Bayesian statistic technique approach is shown to be a viable method to measure stellar parameters for hot massive stars in low-metallicity environments even when only low-resolution spectra are available.