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Understanding the physical and evolutionary properties of Hot Stellar Systems(HSS) is a major challenge in astronomy. We studied the dataset on 13456 HSS ofMisgeld and Hilker (2011) that includes 12763 candidate globular clusters usingstellar mass ($M_s$), effective radius ($R_e$) and mass-to-luminosity ratio($M_s/L_\nu$), and found multi-layered homogeneous grouping among these stellarsystems. Our methods elicited eight homogeneous ellipsoidal groups at thefinest sub-group level. Some of these groups have high overlap and were mergedthrough a multi-phased syncytial algorithm motivated from Almod\'ovar-Riveraand Maitra (2020). Five groups were merged in the first phase, resulting inthree complex-structured groups. Our algorithm determined further complexstructure and permitted another merging phase, revealing two complex-structuredgroups at the highest level. A nonparametric bootstrap procedure was also usedto estimate the confidence of each of our group assignments. These assignmentsgenerally had high confidence in classification, indicating great degree ofcertainty of the HSS assignments into our complex-structured groups. Thephysical and kinematic properties of the two groups were assessed in terms of$M_s$, $R_e$, surface density and $M_s/L_\nu$. The first group consisted ofolder, smaller and less bright HSS while the second group consisted of brighterand younger HSS. Our analysis provides novel insight into the physical andevolutionary properties of HSS and also helps understand physical andevolutionary properties of candidate globular clusters. Further, the candidateglobular clusters (GCs) are seen to have very high chance of really being GCsrather than dwarfs or dwarf ellipticals that are also indicated to be quitedistinct from each other.

Multi-layered characterization of hot stellar systems with confidence