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Euclid preparation: XXVI. The Euclid Morphology Challenge: Towards structural parameters for billions of galaxies

Collaboration, Euclid; Bretonnière, H.; Kuchner, U.; Huertas-Company, M.; Merlin, E.; Castellano, M.; Tuccillo, D.; Buitrago, F.; Conselice, C. J.; Boucaud, A.; Häußler, B.; Kümmel, M.; Hartley, W. G.; Alvarez Ayllon, A.; Bertin, E.; Ferrari, F.; Ferreira, L.; Gavazzi, R.; Hernández-Lang, D.; Lucatelli, G.; Robotham, A. S.G.; Schefer, M.; Wang, L.; Cabanac, R.; Domínguez Sánchez, H.; Duc, P. A.; Fotopoulou, S.; Kruk, S.; La Marca, A.; Margalef-Bentabol, B.; Marleau, F. R.; Tortora, C.; Aghanim, N.; Amara, A.; Auricchio, N.; Azzollini, R.; Baldi, M.; Bender, R.; Bodendorf, C.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Carbone, C.; Carretero, J.; Castander, F. J.; Cavuoti, S.; Cimatti, A.; Cledassou, R.; Congedo, G.; Conversi, L.; Copin, Y.; Corcione, L.; Courbin, F.; Cropper, M.; Da Silva, A.; Degaudenzi, H.; Dinis, J.; Dubath, F.; Duncan, C. A.J.; Dupac, X.; Dusini, S.; Farrens, S.; Ferriol, S.; Frailis, M.; Franceschi, E.; Fumana, M.; Galeotta, S.; Garill...

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Euclid Collaboration

H. Bretonnière

M. Huertas-Company

E. Merlin

M. Castellano

D. Tuccillo

F. Buitrago

C. J. Conselice

A. Boucaud

B. Häußler

M. Kümmel

W. G. Hartley

A. Alvarez Ayllon

E. Bertin

F. Ferrari

L. Ferreira

R. Gavazzi

D. Hernández-Lang

G. Lucatelli

A. S.G. Robotham

M. Schefer

L. Wang

R. Cabanac

H. Domínguez Sánchez

P. A. Duc

S. Fotopoulou

S. Kruk

A. La Marca

B. Margalef-Bentabol

F. R. Marleau

C. Tortora

N. Aghanim

A. Amara

N. Auricchio

R. Azzollini

M. Baldi

R. Bender

C. Bodendorf

E. Branchini

M. Brescia

J. Brinchmann

S. Camera

V. Capobianco

C. Carbone

J. Carretero

F. J. Castander

S. Cavuoti

A. Cimatti

R. Cledassou

G. Congedo

L. Conversi

Y. Copin

L. Corcione

F. Courbin

M. Cropper

A. Da Silva

H. Degaudenzi

J. Dinis

F. Dubath

C. A.J. Duncan

X. Dupac

S. Dusini

S. Farrens

S. Ferriol

M. Frailis

E. Franceschi

M. Fumana

S. Galeotta

B. Garilli

B. Gillis

C. Giocoli

A. Grazian

F. Grupp

S. V.H. Haugan

H. Hoekstra

W. Holmes

F. Hormuth

A. Hornstrup

P. Hudelot

K. Jahnke

S. Kermiche

A. Kiessling

R. Kohley

M. Kunz

H. Kurki-Suonio

S. Ligori

P. B. Lilje

I. Lloro

O. Mansutti

O. Marggraf

K. Markovic

F. Marulli

R. Massey

H. J. McCracken

E. Medinaceli

M. Melchior

M. Meneghetti

G. Meylan

M. Moresco

L. Moscardini

L. Moscardini

L. Moscardini

L. Moscardini

L. Moscardini

L. Moscardini

L Moscardini

L Moscardini

L Moscardini


The various Euclid imaging surveys will become a reference for studies of galaxy morphology by delivering imaging over an unprecedented area of 15 000 square degrees with high spatial resolution. In order to understand the capabilities of measuring morphologies from Euclid-detected galaxies and to help implement measurements in the pipeline of the Organisational Unit MER of the Euclid Science Ground Segment, we have conducted the Euclid Morphology Challenge, which we present in two papers. While the companion paper focusses on the analysis of photometry, this paper assesses the accuracy of the parametric galaxy morphology measurements in imaging predicted from within the Euclid Wide Survey. We evaluate the performance of five state-of-the-art surface-brightness-fitting codes, DeepLeGATo, Galapagos-2, Morfometryka, ProFit and SourceXtractor++, on a sample of about 1.5 million simulated galaxies (350 000 above 5σ) resembling reduced observations with the Euclid VIS and NIR instruments. The simulations include analytic Sérsic profiles with one and two components, as well as more realistic galaxies generated with neural networks. We find that, despite some code-specific differences, all methods tend to achieve reliable structural measurements (< 10% scatter on ideal Sérsic simulations) down to an apparent magnitude of about I E = 23 in one component and I E = 21 in two components, which correspond to a signal-to-noise ratio of approximately 1 and 5, respectively. We also show that when tested on non-analytic profiles, the results are typically degraded by a factor of 3, driven by systematics. We conclude that the official Euclid Data Releases will deliver robust structural parameters for at least 400 million galaxies in the Euclid Wide Survey by the end of the mission. We find that a key factor for explaining the different behaviour of the codes at the faint end is the set of adopted priors for the various structural parameters.


Collaboration, E., Bretonnière, H., Kuchner, U., Huertas-Company, M., Merlin, E., Castellano, M., …Moscardini, L. (2023). Euclid preparation: XXVI. The Euclid Morphology Challenge: Towards structural parameters for billions of galaxies. Astronomy and Astrophysics, 671, Article A102.

Journal Article Type Article
Acceptance Date Oct 22, 2022
Online Publication Date Mar 14, 2023
Publication Date 2023-03
Deposit Date Dec 21, 2022
Publicly Available Date Mar 14, 2023
Journal Astronomy and Astrophysics
Print ISSN 2329-1273
Electronic ISSN 1432-0746
Peer Reviewed Peer Reviewed
Volume 671
Article Number A102
Keywords Methods: data analysis, galaxies: evolution, galaxies: fundamental parameters, cosmology: observations
Public URL
Publisher URL


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