The local universe in the era of large surveys. I. Spectral classification of S0 galaxies
J. L. Tous, J. M. Solanes, J. D. Perea

TL;DR
This study classifies S0 galaxies using spectral data and machine learning, revealing two distinct sub-populations with different physical properties and environmental preferences, challenging previous notions of their rarity.
Contribution
It introduces a novel machine learning approach to classify S0 galaxies based on spectral features, uncovering two physically distinct sub-populations within this morphological type.
Findings
Two S0 sub-populations with different properties identified
Star-forming S0 galaxies are more common than previously thought
Star-forming S0s resemble late spirals in spectral characteristics
Abstract
This is the first paper in a series devoted to review the main properties of galaxies designated S0 in the Hubble classification system. Our aim is to gather abundant and, above all, robust information on the most relevant physical parameters of this poorly-understood morphological type and their possible dependence on the environment that could later be used to assess their possible formation channel(s). The adopted approach combines the characterisation of the fundamental features of the optical spectra of S0 with heliocentric with the exploration of a comprehensive set of their global attributes. A principal component analysis is used to reduce the huge number of dimensions of the spectral data to a low-dimensional space facilitating a bias-free machine-learning-based classification of the galaxies. This procedure has revealed that objects bearing the S0…
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