Bayesian estimation of King's profile parameters for ten open clusters in the Milky Way

NAVONE, H.D.; PERA, M. S.; VAZQUEZ, R.A.; PERREN, G. I.

Rosario

Congreso; 62 Reunión Anual de la Asociación Argentina de Astronomía; 2020

Universidad Nacional de Rosario

We apply a Bayesian inference method designed to estimate the parameters of a King profile on ten selected open clusters with data obtained from the Gaia DR2 survey. The clusters are located at various distances, scattered throughout the galactic disk, and spanning a wide age range. Through the application of our pyUPMASK membership estimation algorithm, the input data is cleaned from contaminating field stars previous its processing with the Bayesian framework. The King profile fitting method method allows for an elliptical rotated profile to be fitted on spatial data, resulting in a four parameters solution: rotation angle, eccentricity, core radius, and tidal radius. We plan on extending the results obtained here to as many open clusters as possible, thus creating a homogeneous database of structural parameters estimated through Bayesian inference.