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A deep learning approach to test the small-scale galaxy morphology and its relationship with star formation activity in hydrodynamical simulations

Authors :
Connor Bottrell
Lars Hernquist
Marc Huertas-Company
Annalisa Pillepich
Dylan Nelson
Mark Vogelsberger
Vicente Rodriguez-Gomez
Lorenzo Zanisi
François Lanusse
Francesco Shankar
Joel R. Primack
Berta Margalef-Bentabol
Avishai Dekel
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres (LERMA)
École normale supérieure - Paris (ENS-PSL)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris
Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-CY Cergy Paris Université (CY)
Astrophysique Interprétation Modélisation (AIM (UMR_7158 / UMR_E_9005 / UM_112))
Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique (LERMA (UMR_8112))
Observatoire de Paris
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-CY Cergy Paris Université (CY)
Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)
Source :
Monthly Notices of the Royal Astronomical Society, Monthly Notices of the Royal Astronomical Society, 2021, 501 (3), pp.4359-4382. ⟨10.1093/mnras/staa3864⟩, Monthly Notices of the Royal Astronomical Society, Oxford University Press (OUP): Policy P-Oxford Open Option A, 2021, 501 (3), pp.4359-4382. ⟨10.1093/mnras/staa3864⟩
Publication Year :
2021
Publisher :
HAL CCSD, 2021.

Abstract

Accepted for publication in MNRAS. Comments welcome; International audience; ABSTRACT Hydrodynamical simulations of galaxy formation and evolution attempt to fully model the physics that shapes galaxies. The agreement between the morphology of simulated and real galaxies, and the way the morphological types are distributed across galaxy scaling relations are important probes of our knowledge of galaxy formation physics. Here, we propose an unsupervised deep learning approach to perform a stringent test of the fine morphological structure of galaxies coming from the Illustris and IllustrisTNG (TNG100 and TNG50) simulations against observations from a subsample of the Sloan Digital Sky Survey. Our framework is based on PixelCNN, an autoregressive model for image generation with an explicit likelihood. We adopt a strategy that combines the output of two PixelCNN networks in a metric that isolates the small-scale morphological details of galaxies from the sky background. We are able to quantitatively identify the improvements of IllustrisTNG, particularly in the high-resolution TNG50 run, over the original Illustris. However, we find that the fine details of galaxy structure are still different between observed and simulated galaxies. This difference is mostly driven by small, more spheroidal, and quenched galaxies that are globally less accurate regardless of resolution and which have experienced little improvement between the three simulations explored. We speculate that this disagreement, that is less severe for quenched discy galaxies, may stem from a still too coarse numerical resolution, which struggles to properly capture the inner, dense regions of quenched spheroidal galaxies.

Details

Language :
English
ISSN :
00358711 and 13652966
Database :
OpenAIRE
Journal :
Monthly Notices of the Royal Astronomical Society, Monthly Notices of the Royal Astronomical Society, 2021, 501 (3), pp.4359-4382. ⟨10.1093/mnras/staa3864⟩, Monthly Notices of the Royal Astronomical Society, Oxford University Press (OUP): Policy P-Oxford Open Option A, 2021, 501 (3), pp.4359-4382. ⟨10.1093/mnras/staa3864⟩
Accession number :
edsair.doi.dedup.....8f3d3b7c85824ee3decbaaac4e6ad654