2025ApJ...993..112G

Star clusters are interesting laboratories to study star formation, single and binary stellar evolution, and stellar dynamics. We have used the exquisite data from Gaia's Data Release 3 (DR3) to study 21 relatively rich and nearby open clusters with member numbers (N_cl) > 500. We have developed a nonparametric method to identify cluster members. Our method works well for clusters located in both sparse and crowded environments and hence can be applied to a wide variety of star clusters. Since the member classification scheme does not make any assumptions on the expected distributions of potential cluster members, our method can identify members associated with clusters that are oddly shaped or have complex internal spatial or kinematic structures. In addition, since the membership determination does not depend on the proximity to any well-defined sequences on the color-magnitude diagram, this method easily identifies straggler members. Furthermore, for each of these clusters, we estimate essential cluster properties including age, metallicity, distance, and reddening using detailed Markov Chain Monte Carlo parameter estimation. We report the full posteriors for these important cluster properties for all clusters in our study.