Bayesian statistics for massive stars

Spectral analysis is a powerful tool to investigate stellar properties and it has been widely used for decades now. However, the methods considered to perform this kind of analysis are mostly based on iteration among a few diagnostic lines to determine the stellar parameters. While these methods are often simple and fast, they can lead to errors and large uncertainties due to the required assumptions. Here, we present a method based on Bayesian statistics to find simultaneously the best combination of effective temperature, surface gravity, projected rotational velocity, and microturbulence velocity, using all the available spectral lines. Different tests are discussed to demonstrate the strength of our method, which we apply to 54 mid-resolution spectra of field and cluster B stars obtained at the Observatoire du Mont-Megantic. We compare our results with those found in the literature. Differences are seen which are well explained by the different methods used. We conclude that the B-star microturbulence velocities are often underestimated. We also confirm the trend that B stars in clusters are on average faster rotators than field B stars.

Cone search capability for table J/MNRAS/454/28/stars (List of studied stars)

Identifier
Source https://dc.g-vo.org/rr/q/lp/custom/CDS.VizieR/J/MNRAS/454/28
Related Identifier https://cdsarc.cds.unistra.fr/viz-bin/cat/J/MNRAS/454/28
Related Identifier http://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/MNRAS/454/28
Metadata Access http://dc.g-vo.org/rr/q/pmh/pubreg.xml?verb=GetRecord&metadataPrefix=oai_b2find&identifier=ivo://CDS.VizieR/J/MNRAS/454/28
Provenance
Creator Mugnes J.-M.; Robert C.
Publisher CDS
Publication Year 2017
Rights https://cds.unistra.fr/vizier-org/licences_vizier.html
OpenAccess true
Contact CDS support team <cds-question(at)unistra.fr>
Representation
Resource Type Dataset; AstroObjects
Discipline Astrophysics and Astronomy; Natural Sciences; Observational Astronomy; Physics; Stellar Astronomy