A1 Refereed original research article in a scientific journal
Euclid preparation XLIV. Modelling spectroscopic clustering on mildly nonlinear scales in beyond-ΛCDM models
Authors: Bose, B.; Carrilho, P.; Marinucci, M.; Moretti, C.; Pietroni, M.; Carella, E.; Piga, L.; Wright, B. S.; Vernizzi, F.; Carbone, C.; Casas, S.; D'Amico, G.; Frusciante, N.; Koyama, K.; Pace, F.; Pourtsidou, A.; Baldi, M.; de la Bella, L. F.; Fiorini, B.; Giocoli, C.; Lombriser, L.; Aghanim, N.; Amara, A.; Andreon, S.; Auricchio, N.; Bardelli, S.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Cardone, V. F.; Carretero, J.; Castellano, M.; Cavuoti, S.; Cimatti, A.; Congedo, G.; Conselice, C. J.; Conversi, L.; Copin, Y.; Costille, A.; Courbin, F.; Courtois, H. M.; Da Silva, A.; Degaudenzi, H.; Di Giorgio, A. M.; Dubath, F.; Duncan, C. A. J.; Dupac, X.; Dusini, S.; Farina, M.; Farrens, S.; Ferriol, S.; Fosalba, P.; Frailis, M.; Franceschi, E.; Galeotta, S.; Garilli, B.; Gillis, B.; Grazian, A.; Grupp, F.; Guzzo, L.; Haugan, S. V. H.; Hormuth, F.; Hornstrup, A.; Jahnke, K.; Joachimi, B.; Keihanen, E.; Kermiche, S.; Kiessling, A.; Kilbinger, M.; Kitching, T.; Kunz, M.; Kurki-Suonio, H.; Ligori, S.; Lilje, P. B.; Lindholm, V.; Lloro, I.; Maino, D.; Maiorano, E.; Mansutti, O.; Marggraf, O.; Markovic, K.; Martinet, N.; Marulli, F.; Massey, R.; Medinaceli, E.; Meneghetti, M.; Meylan, G.; Moresco, M.; Moscardini, L.; Mota, D. F.; Munari, E.; 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.; Sapone, D.; Sartoris, B.; Schneider, P.; Secroun, A.; Seidel, G.; Seiffert, M.; Serrano, S.; Sirignano, C.; Sirri, G.; Stanco, L.; Starck, J. -l.; Tallada-Crespi, P.; Taylor, A. N.; Tereno, I.; Toledo-Moreo, R.; Torradeflot, F.; Tutusaus, I.; Valentijn, E. A.; Valenziano, L.; Vassallo, T.; Veropalumbo, A.; Wang, Y.; Weller, J.; Zamorani, G.; Zoubian, J.; Zucca, E.; Biviano, A.; Bozzo, E.; Burigana, C.; Colodro-Conde, C.; Di Ferdinando, D.; Gracia-Carpio, J.; Mauri, N.; Neissner, C.; Sakr, Z.; Scottez, V.; Tenti, M.; Viel, M.; Wiesmann, M.; Akrami, Y.; Allevato, V.; Anselmi, S.; Ballardini, M.; Bernardeau, F.; Borgani, S.; Bruton, S.; Cabanac, R.; Cappi, A.; Carvalho, C. S.; Castignani, G.; Castro, T.; Canas-Herrera, G.; Chambers, K. C.; Cooray, A. R.; Coupon, J.; Davini, S.; de la Torre, S.; De Lucia, G.; Desprez, G.; Di Domizio, S.; Dole, H.; Diaz-Sanchez, A.; Escartin Vigo, J. A.; Escoffier, S.; Ferreira, P. G.; Ferrero, I.; Finelli, F.; Gabarra, L.; Ganga, K.; Garcia-Bellido, J.; Giacomini, F.; Gozaliasl, G.; Guinet, D.; Hall, A.; Joudaki, S.; Kajava, J. J. E.; Kansal, V.; Karagiannis, D.; Kirkpatrick, C. C.; Legrand, L.; Loureiro, A.; Macias-Perez, J.; Magliocchetti, M.; Maoli, R.; Martinelli, M.; Martins, C. J. A. P.; Matthew, S.; Maturi, M.; Maurin, L.; Metcalf, R. B.; Migliaccio, M.; Monaco, P.; Morgante, G.; Nadathur, S.; Walton, Nicholas A.; Patrizii, L.; Pezzotta, A.; Popa, V.; Porciani, C.; Potter, D.; Pontinen, M.; Reimberg, P.; Rocci, P. -F.; Sanchez, A. G.; Schneider, A.; Sefusatti, E.; Sereno, M.; Silvestri, A.; Mancini, A. Spurio; Steinwagner, J.; Testera, G.; Teyssier, R.; Toft, S.; Tosi, S.; Troja, A.; Tucci, M.; Valiviita, J.; Vergani, D.; Euclid Collaboration
Publisher: EDP SCIENCES S A
Publishing place: LES ULIS CEDEX A
Publication year: 2024
Journal: Astronomy and Astrophysics
Journal name in source: ASTRONOMY & ASTROPHYSICS
Journal acronym: ASTRON ASTROPHYS
Article number: A275
Volume: 689
Number of pages: 29
ISSN: 0004-6361
eISSN: 1432-0746
DOI: https://doi.org/10.1051/0004-6361/202348784
Web address : https://doi.org/10.1051/0004-6361/202348784
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/477043528
Context. The Euclid space satellite mission will measure the large-scale clustering of galaxies at an unprecedented precision, providing a unique probe of modifications to the Lambda CDM model.
Aims. We investigated the approximations needed to efficiently predict the large-scale clustering of matter and dark matter halos in the context of modified gravity and exotic dark energy scenarios. We examined the normal branch of the Dvali-Gabadadze-Porrati model, the Hu-Sawicki f(R) model, a slowly evolving dark energy model, an interacting dark energy model, and massive neutrinos. For each, we tested approximations for the perturbative kernel calculations, including the omission of screening terms and the use of perturbative kernels based on the Einstein-de Sitter universe; we explored different infrared-resummation schemes, tracer bias models and a linear treatment of massive neutrinos; we investigated various approaches for dealing with redshift-space distortions and modelling the mildly nonlinear scales, namely the Taruya-Nishimishi-Saito prescription and the effective field theory of large-scale structure. This work provides a first validation of the various codes being considered by Euclid for the spectroscopic clustering probe in beyond-Lambda CDM scenarios.
Methods. We calculated and compared the chi 2 statistic to assess the different modelling choices. This was done by fitting the spectroscopic clustering predictions to measurements from numerical simulations and perturbation theory-based mock data. We compared the behaviour of this statistic in the beyond-Lambda CDM cases, as a function of the maximum scale included in the fit, to the baseline Lambda CDM case.
Results. We find that the Einstein-de Sitter approximation without screening is surprisingly accurate for the modified gravity cases when comparing to the halo clustering monopole and quadrupole obtained from simulations and mock data. Further, we find the same goodness-of-fit for both cases - the one including and the one omitting non-standard physics in the predictions. Our results suggest that the inclusion of multiple redshift bins, higher-order multipoles, higher-order clustering statistics (such as the bispectrum), and photometric probes such as weak lensing, will be essential to extract information on massive neutrinos, modified gravity and dark energy. Additionally, we show that the three codes used in our analysis, namely, PBJ, Pybird and MG-Copter, exhibit sub-percent agreement for k <= 0.5 h Mpc(-1) across all the models. This consistency underscores their value as reliable tools.
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Funding information in the publication:
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). BB was supported by a UK Research and Innovation Stephen Hawking Fellowship (EP/W005654/2). AP is a UK Research and Innovation Future Leaders Fellow [grant MR/S016066/2]. CM and PC’s research for this project was supported by a UK Research and Innovation Future Leaders Fellowship [grant MR/S016066/2]. CM’s work is supported by the Fondazione ICSC, Spoke 3 Astrophysics and Cosmos Observations, National Recovery and Resilience Plan (Piano Nazionale di Ripresa e Resilienza, PNRR) Project ID CN_00000013 “Italian Research Center on High-Performance Computing, Big Data and Quantum Computing” funded by MUR Missione 4 Componente 2 Investimento 1.4: Potenziamento strutture di ricerca e creazione di “campioni nazionali di R&S (M4C2-19 )” – Next Generation EU (NGEU). MP acknowledges support by the MIUR ‘Progetti di Ricerca di Rilevante Interesse Nazionale’ (PRIN) Bando 2022 – grant 20228RMX4A. FV acknowledges partial support by the ANR Project COLSS (ANR-21-CE31-0029). NF is supported by the Italian Ministry of University and Research (MUR) through the Rita Levi Montalcini project “Tests of gravity on cosmic scales” with reference PGR19ILFGP and she also acknowledges the FCT project with ref. number PTDC/FIS-AST/0054/2021. CC acknowledges a generous CPU and storage allocation by the Italian Super-Computing Resource Allocation (ISCRA) as well as from the coordination of the “Accordo Quadro MoU per lo svolgimento di attivitá congiunta di ricerca Nuove frontiere in Astrofisica: HPC e Data Exploration di nuova generazione”, together with storage from INFN-CNAF and INAF-IA2. FP acknowledges partial support from the INFN grant InDark, the Departments of Excellence grant L.232/2016 of the Italian Ministry of Education, University and Research (MUR) and from the European Union – Next Generation EU. FP also acknowledges the FCT project with ref. number PTDC/FIS-AST/0054/2021. We acknowledge the hospitality of the Institute for Fundamental Physics of the Universe (IFPU) of Trieste for the group meeting held there in December 2022. For the purpose of open access, the author(s) has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising.
