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arXiv · 2201.10694

The Hierarchical Structure of Galactic Haloes: Generalised N-Dimensional Clustering with CluSTAR-ND

William H. Oliver·Pascal J. Elahi·Geraint F. Lewis
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Abstract

We present CluSTAR-ND, a fast hierarchical galaxy/(sub)halo finder that produces {\bf Clu}stering {\bf S}tructure via {\bf T}ransformative {\bf A}ggregation and {\bf R}ejection in {\bf N}-{\bf D}imensions. It is designed to improve upon Halo-OPTICS -- an algorithm that automatically detects and extracts significant astrophysical clusters from the 3D spatial positions of simulation particles -- by decreasing run-times, possessing the capability for metric adaptivity, and being readily applicable to data with any number of features. We directly compare these algorithms and find that not only does CluSTAR-ND produce a similarly robust clustering structure, it does so in a run-time that is at least $3$ orders of magnitude faster. In optimising CluSTAR-ND's clustering performance, we have also carefully calibrated $4$ of the $7$ CluSTAR-ND parameters which -- unless specified by the user -- will be automatically and optimally chosen based on the input data. We conclude that CluSTAR-ND is a robust astrophysical clustering algorithm that can be leveraged to find stellar satellite groups on large synthetic or observational data sets.

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William H. Oliver, Pascal J. Elahi, Geraint F. Lewis. 2022-01-26. The Hierarchical Structure of Galactic Haloes: Generalised N-Dimensional Clustering with CluSTAR-ND. https://doi.org/10.1093/mnras%2Fstac1701

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