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Abstract

This research presents unsupervised machine learning and statistical techniques to detect and analyze tidal tails in five open clusters, BH 164, Alessi 2, NGC 2281, NGC 2354, and M67, with ages ranging from 60 Myr to 4 Gyr, using Gaia DR3 data. Color-magnitude diagram (CMD) matching, principal component analysis (PCA), and density-based clustering were used to detect the tails. Tidal tails were found in all clusters, extending 40 to 100 pc and containing 100 to 200 stars. Other statistical methods were used to study the stellar kinematics, photometry, and spatial distribution of the detected features. The tails had luminosity functions similar to their parent clusters, generally lacked massive stars, and showed higher binary fractions. Significant rotation was detected in M67 and NGC 2281 for the first time.