2018/04/13 by Justyn Campbell-White, J. Campbell-White, D. Froebrich +2
Physics and Astronomy · #Astronomy and Astrophysical Research #Astrophysics #Astrophysics and Star Formation Studies #Cluster (spacecraft) #Cluster analysis #Computer science #Galaxy #Geometry #Group (periodic table) #Hierarchical clustering #Mass segregation #Multidimensional scaling #Optics #Physics #Sampling (signal processing) #Scaling #Star cluster #Stars #Statistical physics #Statistics #Stellar, planetary, and galactic studies #Surface brightness #astro-ph.GA #astro-ph.IM #astro-ph.SR
paper · pdf · doi:10.1093/mnras/sty954
15 pages, 9 figures, 1 table, accepted for publication in MNRAS, full version with full appendix available at http://astro.kent.ac.uk/~df/papers.html
arxiv created 2018/04/13 · openalex publication_date 2018/04/16 · arxiv updated 2018/05/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We present here our shape analysis method for a sample of 76 Galactic HII regions from MAGPIS 1.4 GHz data. The main goal is to determine whether physical properties and initial conditions of massive star cluster formation is linked to the shape of the regions. We outline a systematic procedure for extracting region shapes and perform hierarchical clustering on the shape data. We identified six groups that categorise HII regions by common morphologies. We confirmed the validity of these groupings by bootstrap re-sampling and the ordinance technique multidimensional scaling. We then investigated associations between physical parameters and the assigned groups. Location is mostly independent of group, with a small preference for regions of similar longitudes to share common morphologies. The shapes are homogeneously distributed across Galactocentric distance and latitude. One group contains regions that are all younger than 0.5 Myr and ionised by low- to intermediate-mass sources. Those in another group are all driven by intermediate- to high-mass sources. One group was distinctly separated from the other five and contained regions at the surface brightness detection limit for the survey. We find that our hierarchical procedure is most sensitive to the spatial sampling resolution used, which is determined for each region from its distance. We discuss how these errors can be further quantified and reduced in future work by utilising synthetic observations from numerical simulations of HII regions. We also outline how this shape analysis has further applications to other diffuse astronomical objects.