Astroinformatics based search for globular clusters in the Fornax Deep Survey

Abstract

In the last years, Astroinformatics has become a well defined paradigm for many fields of Astronomy. In this work we demonstrate the potential of a multidisciplinary approach to identify globular clusters (GCs) in the Fornax cluster of galaxies taking advantage of multi-band photometry produced by the VLT Survey Telescope using automatic self-adaptive methodologies. The data analyzed in this work consist of deep, multi-band, partially overlapping images centered on the core of the Fornax cluster. In this work we use a Neural-Gas model, a pure clustering machine learning methodology, to approach the GC detection, while a novel feature selection method ($\Phi$LAB) is exploited to perform the parameter space analysis and optimization. We demonstrate that the use of an Astroinformatics based methodology is able to provide GC samples that are comparable, in terms of purity and completeness with those obtained using single band HST data (Brescia et al. 2012) and two approaches based respectively on a morpho-photometric (Cantiello et al. 2018b) and a PCA analysis (D'Abrusco et al. 2015) using the same data discussed in this work.

29 pages, 14 figures

References in corpus (12)

• The R136 star cluster hosts several stars whose individual masses greatly exceed the accepted 150 Msun stellar mass limit
• Machine Learning in Astronomy: a practical overview
• Large-scale study of the NGC 1399 globular cluster system in Fornax
• Black hole mass estimation for Active Galactic Nuclei from a new angle
• Photometric redshifts with Quasi Newton Algorithm (MLPQNA). Results in the PHAT1 contest
• Star Formation Rates for photometric samples of galaxies using machine learning methods
• C3, A Command-line Catalogue Cross-match tool for large astrophysical catalogues
• DAMEWARE: A web cyberinfrastructure for astrophysical data mining
• Improving Missing Data Imputation with Deep Generative Models
• Astroinformatics: A 21st Century Approach to Astronomy
• Spatial Structures In the Globular Cluster Distribution of the Ten Brightest Virgo Galaxies
• Finding Alternate Features in Lasso

Cited by in corpus (4)

• The Fornax Deep Survey with VST. IX. The catalog of sources in the FDS area, with an example study for globular clusters and background galaxies
• The Fornax Cluster VLT Spectroscopic Survey III -- Kinematical characterisation of globular clusters across the Fornax galaxy cluster
• Ultra-compact dwarfs beyond the centre of the Fornax galaxy cluster: Hints of UCD formation in low-density environments
• The Next Generation Fornax Survey (NGFS).VIII. A Support Vector Machine Approach for Disentangling Globular Clusters from other Sources