Star Membership, Density Profiles, and Mass Separation in Open Clusters Using New Machine Learning-Based Methods | Royal Astronomical Society Monthly Notice

12 open clusters, M38, NGC2099, Coma Ber, NGC752, M67, NGC2243, Alessi01, Bochum04, M34, M35, M41, and M48, using a combination of two unsupervised machine learning algorithms, DBSCAN and GMM. Gaia DR3 base. These clusters vary in age, distance, and number of members, thus adequately covering these parameter situations for analysis with this method. Identified 752, 1725, 116, 269, 1422, 936, 43, 38, 743, 1114, 783, 452. This is M38, NGC2099, Coma Ber, NGC752, M67, respectively NGC2243, Alessi01, Bochum04, M34, M35, M41, M48. In addition, we also obtained clear evidence of mass segregation in tidal radii, core radii, and 10 clusters. Examination of the high-quality color-magnitude data of this cluster yielded one white dwarf each for NGC752, Comaver, and M67. In the young open cluster M38, all members were found to be inside the tidal radius, whereas in the older cluster some members were found to be outside the tidal radius, and the young open cluster had a distinct tidal tail. indicates that there was not enough time to form the We find that population segregation occurs at a higher rate in older clusters than in younger clusters.