1 research outputs found
Membership of Stars in Open Clusters using Random Forest with Gaia Data
Membership of stars in open clusters is one of the most crucial parameters in
studies of star clusters. Gaia opened a new window in the estimation of
membership because of its unprecedented 6-D data. In the present study, we used
published membership data of nine open star clusters as a training set to find
new members from Gaia DR2 data using a supervised random forest model with a
precision of around 90\%. The number of new members found is often double the
published number. Membership probability of a larger sample of stars in
clusters is a major benefit in determination of cluster parameters like
distance, extinction and mass functions. We also found members in the outer
regions of the cluster and found sub-structures in the clusters studied. The
color magnitude diagrams are more populated and enriched by the addition of new
members making their study more promising.Comment: Accepted for publication in The European Physical Journal ST, Special
Issue on Modeling Machine Learning and Astronom