The bimodality of the 10k zCOSMOS-bright galaxies up to z ~ 1: a new statistical and portable classification based on the optical galaxy properties
G. Coppa, M. Mignoli, G. Zamorani, S. Bardelli, S. J. Lilly, M., Bolzonella, M. Scodeggio, D. Vergani, P. Nair, L. Pozzetti, A. Cimatti, E., Zucca, C. M. Carollo, T. Contini, O. Le F\`evre, A. Renzini, V. Mainieri, A., Bongiorno, K. Caputi, O. Cucciati, S. de la Torre

TL;DR
This paper introduces a new statistical classification method for galaxies using PCA and fuzzy clustering, effectively distinguishing galaxy types and revealing the downsizing effect across redshifts.
Contribution
It develops a robust, flexible PCA-UFP classification approach that reliably identifies galaxy populations and their transitional states across a broad redshift range.
Findings
Good agreement with traditional classification methods.
Identifies a coherent intermediate galaxy population.
Reveals the downsizing effect in galaxy evolution.
Abstract
Our goal is to develop a new and reliable statistical method to classify galaxies from large surveys. We probe the reliability of the method by comparing it with a three-dimensional classification cube, using the same set of spectral, photometric and morphological parameters.We applied two different methods of classification to a sample of galaxies extracted from the zCOSMOS redshift survey, in the redshift range 0.5 < z < 1.3. The first method is the combination of three independent classification schemes, while the second method exploits an entirely new approach based on statistical analyses like Principal Component Analysis (PCA) and Unsupervised Fuzzy Partition (UFP) clustering method. The PCA+UFP method has been applied also to a lower redshift sample (z < 0.5), exploiting the same set of data but the spectral ones, replaced by the equivalent width of H. The comparison…
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