Euclid preparation. LXXIII. Spatially resolved stellar populations of local galaxies with Euclid: A proof of concept using synthetic images with the TNG50 simulation

Euclid Collaboration; Abdurro'uf; Tortora, C.; Baes, M.; Nersesian, A.; Kovačić, I.; Bolzonella, M.; Lançon, A.; Bisigello, L.; Annibali, F.; Bremer, M. N.; Carollo, D.; Conselice, C. J.; Enia, A.; Ferguson, A. M. N.; Ferré-Mateu, A.; Hunt, L. K.; Iodice, E.; Knapen, J. H.; Iovino, A.; Marleau, F. R.; Peletier, R. F.; Ragusa, R.; Rejkuba, M.; Robotham, A. S. G.; Román, J.; Saifollahi, T.; Salucci, P.; Scodeggio, M.; Siudek, M.; van der Wel, A.; Voggel, K.; Altieri, B.; Andreon, S.; Baccigalupi, C.; Baldi, M.; Bardelli, S.; Biviano, A.; Bonchi, A.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Caillat, A.; Camera, S.; Cañas-Herrera, G.; Capobianco, V.; Carbone, C.; Carretero, J.; Casas, S.; Castellano, M.; Castignani, G.; Cavuoti, S.; Chambers, K. C.; Cimatti, A.; Colodro-Conde, C.; Congedo, G.; Conversi, L.; Copin, Y.; Courbin, F.; Courtois, H. M.; Cropper, M.; Da Silva, A.; Degaudenzi, H.; De Lucia, G.; Di Giorgio, A. M.; Dinis, J.; Dole, H.; Dubath, F.; Dupac, X.; Dusini, S.; Escoffier, S.; Farina, M.; Farinelli, R.; Farrens, S.; Faustini, F.; Ferriol, S.; Finelli, F.; Fotopoulou, S.; Frailis, M.; Franceschi, E.; Fumana, M.; Galeotta, S.; Gillis, B.; Giocoli, C.; Gómez-Alvarez, P.; Gracia-Carpio, J.; Grazian, A.; Grupp, F.; Holmes, W.; Hormuth, F.; Hornstrup, A.; Hudelot, P.; Jahnke, K.; Jhabvala, M.; Keihänen, E.; Kermiche, S.; Kiessling, A.; Kilbinger, M.; Kubik, B.; Kümmel, M.; Kunz, M.; Kurki-Suonio, H.; Le Brun, A. M. C.; Ligori, S.; Lilje, P. B.; Lindholm, V.; Lloro, I.; Mainetti, G.; Maino, D.; Maiorano, E.; Mansutti, O.; Marggraf, O.; Markovic, K.; Martinelli, M.; Martinet, N.; Marulli, F.; Massey, R.; Medinaceli, E.; Mei, S.; Melchior, M.; Mellier, Y.; Meneghetti, M.; Merlin, E.; Meylan, G.; Mora, A.; Moresco, M.; Moscardini, L.; Niemi, S.-M.; Nightingale, J. W.; Padilla, C.; Paltani, S.; Pasian, F.; Pedersen, K.; Pettorino, V.; Polenta, G.; Poncet, M.; Popa, L. A.; Pozzetti, L.; Raison, F.; Renzi, A.; Rhodes, J.; Riccio, G.; Romelli, E.; Roncarelli, M.; Rossetti, E.; Saglia, R.; Sakr, Z.; Sapone, D.; Sartoris, B.; Schirmer, M.; Schneider, P.; Schrabback, T.; Secroun, A.; Sefusatti, E.; Seidel, G.; Serrano, S.; Simon, P.; Sirignano, C.; Sirri, G.; Stanco, L.; Steinwagner, J.; Tallada-Crespí, P.; Taylor, A. N.; Tereno, I.; Toft, S.; Toledo-Moreo, R.; Torradeflot, F.; Tutusaus, I.; Valenziano, L.; Valiviita, J.; Vassallo, T.; Verdoes Kleijn, G.; Veropalumbo, A.; Wang, Y.; Weller, J.; Zamorani, G.; Zucca, E.; Bozzo, E.; Burigana, C.; Calabrese, M.; Di Ferdinando, D.; Escartin Vigo, J. A.; Matthew, S.; Mauri, N.; Pöntinen, M.; Porciani, C.; Scottez, V.; Tenti, M.; Viel, M.; Wiesmann, M.; Akrami, Y.; Allevato, V.; Anselmi, S.; Archidiacono, M.; Atrio-Barandela, F.; Ballardini, M.; Bertacca, D.; Blanchard, A.; Blot, L.; Borgani, S.; Brown, M. L.; Bruton, S.; Cabanac, R.; Calabro, A.; Cappi, A.; Caro, F.; Carvalho, C. S.; Castro, T.; Cogato, F.; Contini, T.; Cooray, A. R.; Cucciati, O.; Desprez, G.; Díaz-Sánchez, A.; Di Domizio, S.; Ferrari, A. G.; Ferrero, I.; Finoguenov, A.; Fontana, A.; Fornari, F.; Ganga, K.; García-Bellido, J.; Gasparetto, T.; Gaztanaga, E.; Giacomini, F.; Gianotti, F.; Gozaliasl, G.; Gregorio, A.; Guidi, M.; Gutierrez, C. M.; Hall, A.; Hemmati, S.; Hildebrandt, H.; Hjorth, J.; Huertas-Company, M.; Jimenez Muñoz, A.; Kajava, J. J. E.; Kang, Y.; Kansal, V.; Karagiannis, D.; Kirkpatrick, C. C.; Kruk, S.; Lattanzi, M.; Lee, S.; Le Graet, J.; Legrand, L.; Lembo, M.; Lesgourgues, J.; Liaudat, T. I.; Loureiro, A.; Macias-Perez, J.; Magliocchetti, M.; Mannucci, F.; Maoli, R.; Martín-Fleitas, J.; Martins, C. J. A. P.; Maurin, L.; Metcalf, R. B.; Miluzio, M.; Monaco, P.; Moretti, C.; Morgante, G.; Naidoo, K.; Walton, Nicholas A.; Paterson, K.; Patrizii, L.; Pisani, A.; Popa, V.; Potter, D.; Risso, I.; Rocci, P.-F.; Sahlén, M.; Sarpa, E.; Schneider, A.; Sciotti, D.; Sellentin, E.; Sereno, M.; Tanidis, K.; Tao, C.; Testera, G.; Teyssier, R.; Tosi, S.; Troja, A.; Tucci, M.; Valieri, C.; Vergani, D.; Verza, G.; Vielzeuf, P.

doi:10.1051/0004-6361/202554516

Published October 2025 | Version Published

Journal Article Open

Euclid preparation. LXXIII. Spatially resolved stellar populations of local galaxies with Euclid: A proof of concept using synthetic images with the TNG50 simulation

1. Johns Hopkins University
2. Astronomical Observatory of Capodimonte
3. Ghent University
4. University of Liège
5. INAF-Osservatorio di Astrofisica e Scienza dello Spazio di Bologna, Via Piero Gobetti 93/3, 40129, Bologna, Italy
6. Observatory of Strasbourg
7. National Institute for Astrophysics
8. University of Padua
9. University of Bristol
10. Trieste Astronomical Observatory
11. University of Manchester
12. University of Bologna
13. University of Edinburgh
14. Instituto de Astrofísica de Canarias
15. University of La Laguna
16. Arcetri Astrophysical Observatory
17. Brera Astronomical Observatory
18. Universität Innsbruck
19. University of Groningen
20. European Southern Observatory
21. International Centre for Radio Astronomy Research
22. Complutense University of Madrid
23. Institute for Fundamental Physics of the Universe
24. International School for Advanced Studies
25. INFN Sezione di Trieste
26. Istituto di Astrofisica Spaziale e Fisica Cosmica di Milano
27. Institute of Space Sciences
28. European Space Astronomy Centre
29. INFN Sezione di Bologna
30. Agenzia Spaziale Italiana
31. Osservatorio Astrofisico di Torino
32. University of Genoa
33. INFN Sezione di Genova
34. University of Naples Federico II
35. INFN Sezione di Napoli
36. University of Porto
37. French National Centre for Scientific Research
38. University of Turin
39. INFN Sezione di Torino
40. European Space Research and Technology Centre
41. Leiden University
42. Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas
43. RWTH Aachen University
44. University of Portsmouth
45. INAF-Osservatorio Astronomico di Roma, Via Frascati 33, 00078, Monteporzio Catone, Italy
46. University of Hawaii at Manoa
47. European Space Research Institute
48. Claude Bernard University Lyon 1
49. École Polytechnique Fédérale de Lausanne
50. University of Barcelona
51. Institució Catalana de Recerca i Estudis Avançats
52. UCB Lyon 1, CNRS/IN2P3, IUF, IP2I Lyon, 4 rue Enrico Fermi, 69622, Villeurbanne, France
53. University College London
54. University of Lisbon
55. University of Geneva
56. Institute for Space Astrophysics and Planetology
57. Institut d'Astrophysique Spatiale
58. INFN Sezione di Padova
59. Center for Particle Physics of Marseilles
60. University of Paris
61. FRACTAL S.L.N.E., calle Tulipán 2, Portal 13 1A, 28231, Las Rozas de Madrid, Spain
62. Max Planck Institute for Extraterrestrial Physics
63. Osservatorio Astronomico di Padova
64. Ludwig-Maximilians-Universität München
65. Jet Propulsion Lab
66. Felix Hormuth Engineering, Goethestr. 17, 69181, Leimen, Germany
67. Technical University of Denmark
68. University of Copenhagen
69. Institut d'Astrophysique de Paris
70. Max Planck Institute for Astronomy
71. Goddard Space Flight Center
72. University of Helsinki
73. Helsinki Institute of Physics
74. University of Oslo
75. Square Kilometre Array Organisation
76. Centre de Calcul de l'IN2P3/CNRS, 21 avenue Pierre de Coubertin, 69627, Villeurbanne Cedex, France
77. University of Milan
78. INFN Sezione di Milano
79. University of Bonn
80. INFN Sezione di Roma I
81. Durham University
82. Astroparticle and Cosmology Laboratory
83. University of Applied Sciences and Arts Northwestern Switzerland
84. Aurora Technology for European Space Agency (ESA), Camino bajo del Castillo, s/n, Urbanizacion Villafranca del Castillo, Villanueva de la Cañada, 28692, Madrid, Spain
85. Newcastle University
86. Institute for High Energy Physics
87. Centre National d'Études Spatiales
88. Institute of Space Science
89. Heidelberg University
90. Research Institute in Astrophysics and Planetology
91. Université St Joseph; Faculty of Sciences, Beirut, Lebanon
92. University of Chile
93. Institut d'Estudis Espacials de Catalunya
94. Satlantis, University Science Park, Sede Bld 48940, Leioa-Bilbao, Spain
95. Cosmic Dawn Center (DAWN)
96. Polytechnic University of Cartagena
97. Infrared Processing and Analysis Center
98. Astronomical Observatory of the Autonomous Region of the Aosta Valley (OAVdA), Loc. Lignan 39, I-11020, Nus (Aosta Valley), Italy
99. ICL, Junia, Université Catholique de Lille, LITL, 59000, Lille, France
100. ICSC – Centro Nazionale di Ricerca in High Performance Computing, Big Data e Quantum Computing, Via Magnanelli 2, Bologna, Italy
101. Institute for Theoretical Physics
102. Case Western Reserve University
103. University of Salamanca
104. University of Ferrara
105. INFN Sezione di Ferrara
106. University of Tokyo
107. University of Trieste
108. California Institute of Technology
109. Observatoire de la Côte d'Azur
110. University of California, Irvine
111. Saint Mary's University
112. Aalto University
113. Ruhr University Bochum
114. Sorbonne University
115. Grenoble Institute of Technology
116. University of Turku
117. Serco for European Space Agency (ESA), Camino bajo del Castillo, s/n, Urbanizacion Villafranca del Castillo, Villanueva de la Cañada, 28692, Madrid, Spain
118. Swinburne University of Technology
119. Queen Mary University of London
120. University of the Western Cape
121. University of Cambridge
122. Institut de Recherche sur les Lois Fondamentales de l'Univers
123. Stockholm University
124. Imperial College London
125. Sapienza University of Rome
126. HE Space for European Space Agency (ESA), Camino bajo del Castillo, s/n, Urbanizacion Villafranca del Castillo, Villanueva de la Cañada, 28692, Madrid, Spain
127. Princeton University
128. University of Zurich
129. Uppsala University
130. University of Oxford
131. New York University
132. Center for Computational Astrophysics, Flatiron Institute, 162 5th Avenue, 10010, New York, NY, USA

The European Space Agency’s Euclid mission will observe approximately 14000 deg² of the extragalactic sky and deliver high-quality imaging of a large number of galaxies. The depth and high spatial resolution of the data will enable a detailed analysis of the stellar population properties of local galaxies through spatially resolved spectral energy distribution (SED) fitting. In this study, we test our pipeline for spatially resolved SED fitting using synthetic images of Euclid, LSST, and GALEX generated from the TNG50 simulation using the SKIRT 3D radiative transfer code. Our pipeline uses functionalities in piXedfit for processing the simulated data cubes and carrying out SED fitting. We apply our pipeline to 25 simulated galaxies at z ∼ 0 to recover their resolved stellar population properties. For each galaxy, we produce three types of data cubes: GALEX + LSST + Euclid, LSST + Euclid, and Euclid-only. We performed the SED fitting tests with two stellar population synthesis (SPS) models in a Bayesian framework. Because the age, metallicity (Z), and dust attenuation estimates are biased when applying only classical formulations of flat priors (even with the combined GALEX + LSST + Euclid data), we examined the effects of additional physically motivated priors in the forms of mass-age and mass-metallicity relations, constructed using a combination of empirical and simulated data. Stellar-mass surface densities can be recovered well using any of the three data cubes, regardless of the SPS model and prior variations. The new priors then significantly improve the measurements of mass-weighted age and Z compared to results obtained without priors, but they may play an excessive role compared to the data in determining the outcome when no ultraviolet (UV) data is available. Compared to varying the spectral extent of the data cube or including and discarding the additional priors, replacing one SPS model family with the other has little effect on the results. The spatially resolved SED fitting method is powerful for mapping the stellar population properties of many galaxies with the current abundance of high-quality imaging data. Our study re-emphasizes the gain added by including multi-wavelength data from ancillary surveys and the roles of priors in Bayesian SED fitting. With the Euclid data alone, we will be able to generate complete and deep stellar mass maps of galaxies in the local Universe (z ≲ 0.1), exploiting the telescope’s wide field, near-infrared sensitivity, and high spatial resolution.

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© The Authors 2025. Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Acknowledgement

The Euclid Consortium acknowledges the European Space Agency and a number of agencies and institutes that have supported the development of Euclid, in particular the Agenzia Spaziale Italiana, the Austrian Forschungsförderungsgesellschaft funded through BMK, the Belgian Science Policy, the Canadian Euclid Consortium, the Deutsches Zentrum für Luft- und Raumfahrt, the DTU Space and the Niels Bohr Institute in Denmark, the French Centre National d’Etudes Spatiales, the Fundação para a Ciência e a Tecnologia, the Hungarian Academy of Sciences, the Ministerio de Ciencia, Innovación y Universidades, the National Aeronautics and Space Administration, the National Astronomical Observatory of Japan, the Netherlandse Onderzoekschool Voor Astronomie, the Norwegian Space Agency, the Research Council of Finland, the Romanian Space Agency, the State Secretariat for Education, Research, and Innovation (SERI) at the Swiss Space Office (SSO), and the United Kingdom Space Agency. A complete and detailed list is available on the Euclid web site (http://www.euclid-ec.org). Co-funded by the European Union. Views and opinions expressed are however, those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them. CT acknowledges the INAF grant 2022 LEMON. JHK acknowledges grant PID2022-136505NB-I00 funded by MCIN/AEI/10.13039/501100011033 and EU, ERDF. This project makes use of the MaNGA-Pipe3D data products. We thank the IA-UNAM MaNGA team for creating this catalogue, and the Conacyt Project CB-285080 for supporting them.

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Is new version of: Discussion Paper: arXiv:2503.15635 (arXiv)

National Institute for Astrophysics
2022 LEMON
Ministerio de Ciencia, Innovación y Universidades
PID2022-136505NB-I00
European Union

Accepted: 2025-06-06
Available: 2025-10-14

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Caltech groups: Infrared Processing and Analysis Center (IPAC) , Division of Physics, Mathematics and Astronomy (PMA) , Physics Department
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Euclid preparation. LXXIII. Spatially resolved stellar populations of local galaxies with Euclid: A proof of concept using synthetic images with the TNG50 simulation

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Euclid preparation. LXXIII. Spatially resolved stellar populations of local galaxies with Euclid: A proof of concept using synthetic images with the TNG50 simulation

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