Non-parametric morphologies of galaxies in the EAGLE simulation

Lucas A. Bignone*, Susana E. Pedrosa, James W. Trayford, Patricia B. Tissera, Leonardo J. Pellizza

*Corresponding author for this work

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We study the optical morphology of galaxies in a large-scale hydrodynamic cosmological simulation, the EAGLE simulation. Galaxy morphologies were characterized using non-parametric statistics (Gini, M20, Concentration, and Asymmetry) derived from mock images computed using a 3D radiative transfer technique and post-processed to approximate observational surveys. The resulting morphologies were contrasted to observational results from a sample of log10(M/M) > 10 galaxies at z ∼ 0.05 in the GAMA survey. We find that the morphologies of EAGLE galaxies reproduce observations, except for asymmetry values which are larger in the simulated galaxies. Additionally, we study the effect of spatial resolution in the computation of non-parametric morphologies, finding that Gini and Asymmetry values are systematically reduced with decreasing spatial resolution. Gini values for lower mass galaxies are especially affected. Comparing against other large-scale simulations, the non-parametric statistics of EAGLE galaxies largely agree with those found in ILLUSTRISTNG. Additionally, EAGLE galaxies mostly reproduce observed trends between morphology and star formation rate and galaxy size. Finally, We also find a significant correlation between optical and kinematic estimators of morphologies, although galaxy classification based on an optical or a kinematic criteria results in different galaxy subsets. The correlation between optical and kinematic morphologies is stronger in central galaxies than in satellites, indicating differences in morphological evolution.

Original languageEnglish
Pages (from-to)3624-3642
Number of pages19
JournalMonthly Notices of the Royal Astronomical Society
Issue number3
Early online date30 Oct 2019
Publication statusPublished - 1 Jan 2020


  • Galaxies: formation
  • Galaxies: statistics
  • Galaxies: structure
  • Methods: numerical
  • Techniques: image processing


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