COSMOS2020 galaxy morphology classif. with USmorph

In this work, we refine a two-step galaxy morphological classification framework (USmorph), which employs a combination of unsupervised machine-learning and supervised machine-learning techniques, along with a self-consistent and robust data-preprocessing step. The updated method is applied to galaxies with Imag<25 at 0.2<z<1.2 in the COSMOS field.

Based on their Hubble Space Telescope/Advanced Camera for Survey I-band images, we classify them into five distinct morphological types: spherical (SPH, 15200), early-type disk (17369), late-type disk (21143), irregular disk (IRR, 28965), and unclassified (UNC, 17129). In addition, we have conducted both parametric and nonparametric morphological measurements. For galaxies with stellar masses exceeding 10^9^M_{sun}_, a gradual increase in effective radius from SPHs to IRRs is observed, accompanied by a decrease in the Sersic index.