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Euclid preparation: XIII. Forecasts for galaxy morphology with the Euclid Survey using deep generative models

Bretonnière, H.; Huertas-Company, M.; Boucaud, A.; Lanusse, F.; Jullo, E.; Merlin, E.; Tuccillo, D.; Castellano, M.; Brinchmann, J.; Conselice, C. J.; Dole, H.; Cabanac, R.; Courtois, H. M.; Castander, F. J.; Duc, P. A.; Kuchner, U.

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Authors

H. Bretonnière

M. Huertas-Company

A. Boucaud

F. Lanusse

E. Jullo

E. Merlin

D. Tuccillo

M. Castellano

J. Brinchmann

C. J. Conselice

H. Dole

R. Cabanac

H. M. Courtois

F. J. Castander

P. A. Duc



Abstract

We present a machine learning framework to simulate realistic galaxies for the Euclid Survey, producing more complex and realistic galaxies than the analytical simulations currently used in Euclid. The proposed method combines a control on galaxy shape parameters offered by analytic models with realistic surface brightness distributions learned from real Hubble Space Telescope observations by deep generative models. We simulate a galaxy field of 0.4 deg2 as it will be seen by the Euclid visible imager VIS, and we show that galaxy structural parameters are recovered to an accuracy similar to that for pure analytic Sérsic profiles. Based on these simulations, we estimate that the Euclid Wide Survey (EWS) will be able to resolve the internal morphological structure of galaxies down to a surface brightness of 22.5 mag arcsec-2, and the Euclid Deep Survey (EDS) down to 24.9 mag arcsec-2. This corresponds to approximately 250 million galaxies at the end of the mission and a 50% complete sample for stellar masses above 1010.6 M (resp. 109.6 M) at a redshift z ∼ 0.5 for the EWS (resp. EDS). The approach presented in this work can contribute to improving the preparation of future high-precision cosmological imaging surveys by allowing simulations to incorporate more realistic galaxies.

Journal Article Type Article
Acceptance Date Oct 21, 2021
Online Publication Date Jan 18, 2022
Publication Date 2022-01
Deposit Date Mar 29, 2022
Publicly Available Date Apr 5, 2022
Journal Astronomy and Astrophysics
Electronic ISSN 1432-0746
Peer Reviewed Peer Reviewed
Volume 657
Article Number A90
DOI https://doi.org/10.1051/0004-6361/202141393
Keywords Space and Planetary Science; Astronomy and Astrophysics
Public URL https://nottingham-repository.worktribe.com/output/7611442
Publisher URL https://www.aanda.org/articles/aa/full_html/2022/01/aa41393-21/aa41393-21.html
Additional Information Article has 197 authors in total

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