Stellar Formation in NGC 2366: Searching for clusters and associations using unsupervised algorithms

We investigated the characteristics of the young star population in the spiral galaxy NGC 2366. We used unsupervised algorithms as Path Linkage Criterion (PLC), and density based clustering (HDBSCAN).
In particular, we focused our attention in the hierarchical clustering distribution of the young population and the properties of its star groups. As this galaxy shows a prominent He blue sequence, we also analysed this population and used it to understand the spatial distribution of the stellar formation over time.
Direct images of the galaxy were obtained in two photometric bands by the Hubble Space Telescope (HST). They covered almost the central and intermediate zones of NGC 2366, including all the mayor stellar formation regions. HST data allowed to select the blue and young stars and therefore to study the young population. Then, through the PLC and HDBSCAN, we found the young star groups and estimated their fundamental individual parameters, such as their stellar densities, sizes, number of members, and luminosity function slopes. We also performed a fractal analysis to determine the clustering properties of this population. We built a stellar density map corresponding to the galactic young population to detect large structures and depict their main characteristics.

Theme – Machine Learning, Statistics, and Algorithms