Multi-layered characterization of hot stellar systems with confidence

Understanding the physical and evolutionary properties of Hot Stellar Systems (HSS) is a major challenge in astronomy. We studied the dataset on 13456 HSS of Misgeld and Hilker (2011) that includes 12763 candidate globular clusters and found multi-layered homogeneous grouping among these stellar systems. Our methods elicited eight homogeneous ellipsoidal groups at the finest sub-group level. Some of these groups have high overlap and were merged through a multi-phased syncytial algorithm motivated from Almod\'ovar-Rivera and Maitra (2020). Five groups were merged in the first phase, resulting in three complex-structured groups. Our algorithm determined further complex structure and permitted another merging phase, revealing two complex-structured groups at the highest level. A nonparametric bootstrap procedure was also used to estimate the confidence of each of our group assignments. Our group assignments generally had high confidences in classification, indicating great degree of certainty of our HSS assignments into complex-structured groups made by clustering. The physical and kinematic properties of the two groups were assessed in terms of mass, effective radius, surface density and mass-luminosity ratio. The first group consisted of older, smaller and less bright HSS while the second group consisted of brighter and younger HSS. Our analysis provides novel insight into the physical and evolutionary properties of HSS and also helps understand physical and evolutionary properties of candidate globular clusters. Further, the candidate globular clusters are seen to have very high chance of being really so rather than dwarfs or dwarf ellipticals that are also indicated to be quite distinct from each other.