The Implementation of Markov Chain Monte Carlo on the Study of Star Cluster Membership in Open Cluster NGC 3766 and Globular Cluster 6366 - R. Darma; M. I. Arifyanto; Y. A. Hidayat (Journal of Multidisciplinary Academic, 2019)
The membership study of star cluster is a fundamental topic in order to learn more deeply about the evolution of star and dynamical evolution of star cluster itself in the galactic environment. Here, we introduce the membership study of open cluster NGC 3766 and globular cluster NGC 6366 by implementing Markov Chain Monte Carlo (MCMC) algorithm in parametric method. We implemented MCMC algorithm in the fitting processes of stellar proper motion distribution and isochrones model with HR-diagram for both star clusters. We found that MCMC algorithm has been successfully distinguished member stars with membership probability larger than 50%. The convergence processes of fitting parameters were going sufficiently fast with small uncertainties. We obtain that NGC 3766 is (25 ± 7) Myr which containing (882 ± 5) member stars with distance modulus (V-M_V )= (11,95 ± 0,32) and colour excess E(B-V)= (0,30 ± 0,01). These parameters are corresponding to the distance (1,60 ± 0,12) kpc from the Sun with extinction A_v= (0,93 ± 0,18). Besides that, the age of NGC 6366 is (11,70 ± 1,10) Gyr and containing (0,30 ± 0,01) member stars with (V-M_V )= (14,98 ± 0,09) and E(B-V)= (0,77 ± 0,09). Our computations shows that the distance of NGC 6366 is (3,30 ± 0,19) kpc from the Sun with A_v= (2,39 ± 0,28). In this work, our computations of physical parameters are in a good agreement with previous studies. Furthermore, through this work we also suggest a new computation of star cluster physical parameters with MCMC algorithm