The VMC Survey – LI. Classifying extragalactic sources using a probabilistic random forest supervised machine learning algorithm

Clara M. Pennock*, Jacco Th van Loon, Maria-Rosa L. Cioni, Chandreyee Maitra, Joana M. Oliveira, Jessica E. M. Craig, Valentin D. Ivanov, James Aird, Joy O. Anih, Nicholas J. G. Cross, Francesca Dresbach, Richard de Grijs, Martin A. T. Groenewegen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We used a supervised machine learning algorithm (probabilistic random forest) to classify ~130 million sources in the VISTA Survey of the Magellanic Clouds (VMC). We used multi-wavelength photometry from optical to far-infrared as features to be trained on, and spectra of Active Galactic Nuclei (AGN), galaxies and a range of stellar classes including from new observations with the Southern African Large Telescope (SALT) and SAAO 1.9m telescope. We also retain a label for sources that remain unknown. This yielded average classifier accuracies of ~79% (SMC) and ~87% (LMC). Restricting to the 56,696,719 sources with class probabilities (P$_{class}$) > 80% yields accuracies of ~90% (SMC) and ~98% (LMC). After removing sources classed as 'Unknown', we classify a total of 707,939 (SMC) and 397,899 (LMC) sources, including > 77,600 extragalactic sources behind the Magellanic Clouds. The extragalactic sources are distributed evenly across the field, whereas the Magellanic sources concentrate at the centres of the Clouds, and both concentrate in optical/IR colour-colour/magnitude diagrams as expected. We also test these classifications using independent datasets, finding that, as expected, the majority of X-ray sources are classified as AGN (554/883) and the majority of radio sources are classed as AGN (1756/2694) or galaxies (659/2694), where the relative AGN-galaxy proportions vary substantially with radio flux density. We have found: > 49,500 hitherto unknown AGN candidates, likely including more AGN dust dominated sources which are in a critical phase of their evolution; > 26,500 new galaxy candidates and > 2800 new Young Stellar Object (YSO) candidates.
Original languageEnglish
Pages (from-to)1028-1055
Number of pages28
JournalMonthly Notices of the Royal Astronomical Society
Volume537
Issue number2
Early online date15 Jan 2025
DOIs
Publication statusPublished - 1 Feb 2025

Keywords / Materials (for Non-textual outputs)

  • Megellanic Clouds
  • methods: data analysis
  • galaxies: active
  • galaxies: photometry

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