A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Euclid preparation LXXI. Simulations and nonlinearities beyond ΛCDM. 3. Constraints on f(R) models from the photometric primary probes
Tekijät: Koyama, K.; Pamuk, S.; Casas, S.; Bose, B.; Carrilho, P.; Saez-Casares, I.; Atayde, L.; Cataneo, M.; Fiorini, B.; Giocoli, C.; Le Brun, A. M. C.; Pace, F.; Pourtsidou, A.; Rasera, Y.; Sakr, Z.; Winther, H. -A.; Altamura, E.; Adamek, J.; Baldi, M.; Breton, M. -A.; Racz, G.; Vernizzi, F.; Amara, A.; Andreon, S.; Auricchio, N.; Baccigalupi, C.; Bardelli, S.; Bernardeau, F.; Biviano, A.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Caillat, A.; Camera, S.; Canas-Herrera, G.; Capobianco, V.; Carbone, C.; Carretero, J.; Castellano, M.; Castignani, G.; Cavuoti, S.; Chambers, K. C.; Cimatti, A.; Colodro-Conde, C.; Congedo, G.; Conselice, C. J.; Conversi, L.; Copin, Y.; Courbin, F.; Courtois, H. M.; Da Silva, A.; Degaudenzi, H.; De Lucia, G.; Dole, H.; Douspis, M.; Dubath, F.; Duncan, C. A. J.; Dupac, X.; Dusini, S.; Escoffier, S.; Farina, M.; Farinelli, R.; Farrens, S.; Ferriol, S.; Finelli, F.; Fosalba, P.; Frailis, M.; Franceschi, E.; Galeotta, S.; Gillis, B.; Gomez-Alvarez, P.; Gracia-Carpio, J.; Grazian, A.; Grupp, F.; Guzzo, L.; Hailey, M.; Haugan, S. V. H.; Holmes, W.; Hormuth, F.; Hornstrup, A.; Hudelot, P.; Ilic, S.; Jahnke, K.; Jhabvala, M.; Joachimi, B.; Keihanen, E.; Kermiche, S.; Kiessling, A.; Kilbinger, M.; Kubik, B.; Kunz, M.; Kurki-Suonio, H.; 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.; Munari, E.; Neissner, C.; Niemi, S. -M.; Padilla, C.; Paltani, S.; Pasian, F.; Pedersen, K.; Percival, W. J.; Pettorino, V.; Pires, S.; Polenta, G.; Poncet, M.; Popa, L. A.; Pozzetti, L.; Raison, F.; Renzi, A.; Rhodes, J.; Riccio, G.; Romelli, E.; Roncarelli, M.; Saglia, R.; Salvignol, J. -C.; Sanchez, A. G.; Sapone, D.; Sartoris, B.; Schirmer, M.; Schrabback, T.; Secroun, A.; Seidel, G.; Serrano, S.; Sirignano, C.; Sirri, G.; Spurio Mancini, A.; Stanco, L.; Steinwagner, J.; Tallada-Crespi, P.; Taylor, A. N.; Tereno, I.; Tessore, N.; 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.; Fabbian, G.; Matthew, S.; Mauri, N.; Pezzotta, A.; Pontinen, M.; Scottez, V.; Tenti, M.; Viel, M.; Wiesmann, M.; Akrami, Y.; Anselmi, S.; Archidiacono, M.; Atrio-Barandela, F.; Ballardini, M.; Bertacca, D.; Blanchard, A.; Blot, L.; Boehringer, H.; Bruton, S.; Cabanac, R.; Calabro, A.; Camacho Quevedo, B.; Cappi, A.; Caro, F.; Carvalho, C. S.; Castro, T.; Contarini, S.; Cooray, A. R.; Desprez, G.; Diaz-Sanchez, A.; Diaz, J. J.; Di Domizio, S.; Ezziati, M.; Ferrari, A. G.; Ferreira, P. G.; Ferrero, I.; Finoguenov, A.; Fontana, A.; Fornari, F.; Gabarra, L.; Ganga, K.; Garcia-Bellido, J.; Gasparetto, T.; Gautard, V.; Gaztanaga, E.; Giacomini, F.; Gianotti, F.; Gozaliasl, G.; Gutierrez, C. M.; Hall, A.; Hildebrandt, H.; Hjorth, J.; Jimenez Munoz, A.; Joudaki, S.; Kajava, J. J. E.; Kansal, V.; Karagiannis, D.; Kirkpatrick, C. C.; Le Graet, J.; Legrand, L.; Lesgourgues, J.; Liaudat, T. I.; Liu, S. J.; Loureiro, A.; Maggio, G.; Magliocchetti, M.; Mannucci, F.; Maoli, R.; Martin-Fleitas, J.; Martins, C. J. A. P.; Maurin, L.; Metcalf, R. B.; Miluzio, M.; Monaco, P.; Montoro, A.; Moretti, C.; Morgante, G.; Murray, C.; Nadathur, S.; Pagano, L.; Patrizii, L.; Popa, V.; Potter, D.; Reimberg, P.; Risso, I.; Rocci, P. -F.; Sahlen, M.; Sarpa, E.; Schneider, A.; Sereno, M.; Silvestri, A.; Stadel, J.; Tanidis, K.; Tao, C.; Testera, G.; Teyssier, R.; Tosi, S.; Troja, A.; Tucci, M.; Vergani, D.; Verza, G.; Vielzeuf, P.; Walton, N. A.; Euclid Collaboration
Kustantaja: EDP Sciences
Kustannuspaikka: LES ULIS CEDEX A
Julkaisuvuosi: 2025
Journal: Astronomy and Astrophysics
Tietokannassa oleva lehden nimi: Astronomy & Astrophysics
Lehden akronyymi: ASTRON ASTROPHYS
Artikkelin numero: A233
Vuosikerta: 698
Sivujen määrä: 24
ISSN: 0004-6361
eISSN: 1432-0746
DOI: https://doi.org/10.1051/0004-6361/202452184
Verkko-osoite: https://doi.org/10.1051/0004-6361/202452184
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/499281538
We study the constraint on f(R) gravity that can be obtained by photometric primary probes of the Euclid mission. Our focus is the dependence of the constraint on the theoretical modelling of the nonlinear matter power spectrum. In the Hu-Sawicki f(R) gravity model, we consider four different predictions for the ratio between the power spectrum in f(R) and that in Lambda cold dark matter (Lambda CDM): a fitting formula, the halo model reaction approach, ReACT, and two emulators based on dark matter only N-body simulations, FORGE and e-Mantis. These predictions are added to the MontePython implementation to predict the angular power spectra for weak lensing (WL), photometric galaxy clustering, and their cross-correlation. By running Markov chain Monte Carlo, we compare constraints on parameters and investigate the bias of the recovered f(R) parameter if the data are created by a different model. For the pessimistic setting of WL, one-dimensional bias for the f(R) parameter, log10|fR0|, is found to be 0.5 sigma when FORGE is used to create the synthetic data with log10|fR0| = -5.301 and fitted by e-Mantis. The impact of baryonic physics on WL is studied by using a baryonification emulator, BCemu. For the optimistic setting, the f(R) parameter and two main baryonic parameters are well constrained despite the degeneracies among these parameters. However, the difference in the nonlinear dark matter prediction can be compensated for the adjustment of baryonic parameters, and the one-dimensional marginalised constraint on log10|fR0| is biased. This bias can be avoided in the pessimistic setting at the expense of weaker constraints. For the pessimistic setting, using the Lambda CDM synthetic data for WL, we obtain the prior-independent upper limit of log10|fR0| < -5.6. Finally, we implement a method to include theoretical errors to avoid the bias due to inaccuracies in the nonlinear matter power spectrum prediction.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
Julkaisussa olevat rahoitustiedot:
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 Forschungsforderungsgesellschaft funded through BMK, the Belgian Science Policy, the Canadian Euclid Consortium, the Deutsches Zentrum fur Luft- und Raumfahrt, the DTU Space and the Niels Bohr Institute in Denmark, the French Centre National d'Etudes Spatiales, the Fundac & atilde;o para a Ciencia e a Tecnologia, the Hungarian Academy of Sciences, the Ministerio de Ciencia, Innovacion 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 (www.euclid-ec.org). K. K. is supported by STFC grant ST/W001225/1. B. B. is supported by a UK Research and Innovation Stephen Hawking Fellowship (EP/W005654/2). A. P. is a UKRI Future Leaders Fellow [grant MR/X005399/1]. P. C. is supported by grant RF/ERE/221061. M. C. acknowledges the financial support provided by the Alexander von Humboldt Foundation through the Humboldt Research Fellowship program, as well as support from the Max Planck Society and the Alexander von Humboldt Foundation in the framework of the Max Planck-Humboldt Research Award endowed by the Federal Ministry of Education and Research. F. P. acknowledges partial support from the INFN grant InDark and the Departments of Excellence grant L.232/2016 of the Italian Ministry of University and Research (MUR). FP also acknowledges the FCT project with ref. number PTDC/FIS-AST/0054/2021. GR's research was supported by an appointment to the NASA Postdoctoral Program administered by Oak Ridge Associated Universities under contract with NASA. GR was supported by JPL, which is run under contract by the California Institute of Technology for NASA (80NM0018D0004). Numerical computations were done on the Sciama High Performance Compute (HPC) cluster which is supported by the ICG, SEPNet, and the University of Portsmouth. This work has made use of the Infinity Cluster hosted by Institut d'Astrophysique de Paris. We acknowledge open libraries support IPython (Perez & Granger 2007), Matplotlib (Hunter 2007), Numpy (Walt et al. 2011), and SciPy (Virtanen et al. 2020). For the purpose of open access, we have applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising. Supporting research data are available on reasonable request from the corresponding author.
