A1 Refereed original research article in a scientific journal
Euclid preparation: LXXII. Three-dimensional galaxy clustering in configuration space: Two-point correlation function estimation
Authors: de la Torre, S.; Marulli, F.; Keihänen, E.; Viitanen, A.; Viel, M.; Veropalumbo, A.; Branchini, E.; Tavagnacco, D.; Rizzo, F.; Valiviita, J.; Lindholm, V.; Allevato, V.; Parimbelli, G.; Sarpa, E.; Ghaffari, Z.; Amara, A.; Andreon, S.; Auricchio, N.; Baccigalupi, C.; Baldi, M.; Bardelli, S.; Basset, A.; Bonino, D.; Brescia, M.; Brinchmann, J.; Caillat, A.; Camera, S.; Capobianco, V.; Carbone, C.; Carretero, J.; Casas, S.; Castander, F. J.; Castellano, M.; Castignani, G.; Cavuoti, S.; Cimatti, A.; Colodro-Conde, C.; Congedo, G.; Conselice, C. J.; Conversi, L.; Copin, Y.; Courbin, F.; Courtois, H. M.; Crocce, M.; Da Silva, A.; Degaudenzi, H.; De Lucia, G.; Di Giorgio, A. M.; Dinis, J.; Dubath, F.; Duncan, C. A. J.; Dupac, X.; Dusini, S.; Farina, M.; Farrens, S.; Faustini, F.; Ferriol, S.; Fourmanoit, N.; Frailis, M.; Franceschi, E.; Franzetti, P.; Fumana, M.; Galeotta, S.; George, K.; Gillard, W.; Gillis, B.; Giocoli, C.; Gómez-Alvarez, P.; Granett, B. R.; Grazian, A.; Grupp, F.; Guzzo, L.; Haugan, S. V. H.; Holmes, W.; Hormuth, F.; Hornstrup, A.; Ilić, S.; Jahnke, K.; Jhabvala, M.; Joachimi, B.; Kermiche, S.; Kiessling, A.; Kilbinger, M.; Kubik, B.; Kunz, M.; Kurki-Suonio, H.; Ligori, S.; Lilje, P. B.; Lloro, I.; Mainetti, G.; Maino, D.; Maiorano, E.; Mansutti, O.; Marggraf, O.; Markovic, K.; Martinelli, M.; Martinet, N.; Massey, R.; Maurogordato, S.; Medinaceli, E.; Mei, S.; Melchior, M.; Mellier, Y.; Meneghetti, M.; Merlin, E.; Meylan, G.; Moresco, M.; Morin, B.; 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.; Pozzetti, L.; Raison, F.; Renzi, A.; Rhodes, J.; Riccio, G.; Romelli, E.; Roncarelli, M.; Rossetti, E.; Saglia, R.; Sakr, Z.; Sánchez, A. G.; Sapone, D.; Sartoris, B.; Schneider, P.; Schrabback, T.; Scodeggio, M.; Secroun, A.; Sefusatti, E.; Seidel, G.; Seiffert, M.; Serrano, S.; Sirignano, C.; Sirri, G.; Stanco, L.; Steinwagner, J.; Surace, C.; Tallada-Crespí, P.; Taylor, A. N.; Tereno, I.; Toledo-Moreo, R.; Torradeflot, F.; Tsyganov, A.; Tutusaus, I.; Valenziano, L.; Vassallo, T.; Wang, Y.; Weller, J.; Zacchei, A.; Zamorani, G.; Zucca, E.; Biviano, A.; Bolzonella, M.; Bozzo, E.; Burigana, C.; Calabrese, M.; Di Ferdinando, D.; Escartin Vigo, J. A.; Farinelli, R.; Finelli, F.; Gabarra, L.; Gracia-Carpio, J.; Matthew, S.; Mauri, N.; Mora, A.; Pezzotta, A.; Pöntinen, M.; Scottez, V.; Simon, P.; Spurio Mancini, A.; Tenti, M.; Wiesmann, M.; Akrami, Y.; Andika, I. T.; Anselmi, S.; Archidiacono, M.; Atrio-Barandela, F.; Balaguera-Antolinez, A.; Bertacca, D.; Bethermin, M.; Blanchard, A.; Blot, L.; Böhringer, H.; Borgani, S.; Brown, M. L.; Bruton, S.; Cabanac, R.; Calabro, A.; Camacho Quevedo, B.; Cañas-Herrera, G.; Cappi, A.; Caro, F.; Carvalho, C. S.; Castro, T.; Chambers, K. C.; Cogato, F.; Contarini, S.; Cooray, A. R.; Cucciati, O.; Davini, S.; De Paolis, F.; Desprez, G.; Díaz-Sánchez, A.; Di Domizio, S.; Dole, H.; Escoffier, S.; Ferrari, A. G.; Ferreira, P. G.; Finoguenov, A.; Fontana, A.; Ganga, K.; García-Bellido, J.; Gasparetto, T.; Gautard, V.; Gaztanaga, E.; Giacomini, F.; Gianotti, F.; Gozaliasl, G.; Gregorio, A.; Guidi, M.; Gutierrez, C. M.; Hall, A.; Hemmati, S.; Hildebrandt, H.; Hjorth, J.; Jimenez Muñoz, A.; Joudaki, S.; Kajava, J. J. E.; Kang, Y.; Kansal, V.; Karagiannis, D.; Kirkpatrick, C. C.; Kruk, S.; Lattanzi, M.; Le Brun, A. M. C.; 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.; Murray, C.; Nadathur, S.; Naidoo, K.; Navarro-Alsina, A.; Nesseris, S.; Paterson, K.; Patrizii, L.; Pisani, A.; Popa, V.; Potter, D.; Reimberg, P.; Risso, I.; Rocci, P.-F.; Sahlén, M.; Schneider, A.; Schultheis, M.; Sciotti, D.; Sellentin, E.; Sereno, M.; Silvestri, A.; Smith, L. C.; Tanidis, K.; Tao, C.; Tessore, N.; Testera, G.; Teyssier, R.; Toft, S.; Tosi, S.; Troja, A.; Tucci, M.; Valieri, C.; Vergani, D.; Verza, G.; Vielzeuf, P.; Walton, N. A.; Euclid Collaboration
Publisher: EDP Sciences
Publication year: 2025
Journal: Astronomy and Astrophysics
Journal name in source: Astronomy & Astrophysics
Article number: A78
Volume: 700
ISSN: 0004-6361
eISSN: 1432-0746
DOI: https://doi.org/10.1051/0004-6361/202553927
Web address : https://doi.org/10.1051/0004-6361/202553927
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/499840563
The two-point correlation function of the galaxy spatial distribution is a major cosmological observable that enables constraints on the dynamics and geometry of the Universe. The Euclid mission is aimed at performing an extensive spectroscopic survey of approximately 20 30 million Hα-emitting galaxies up to a redshift of about 2. This ambitious project seeks to elucidate the nature of dark energy by mapping the three-dimensional clustering of galaxies over a significant portion of the sky. This paper presents the methodology and software developed for estimating the three-dimensional two-point correlation function within the Euclid Science Ground Segment. The software is designed to overcome the significant challenges posed by the large and complex Euclid dataset, which involves millions of galaxies. The key challenges include efficient pair counting, managing computational resources, and ensuring the accuracy of the correlation function estimation. The software leverages advanced algorithms, including k-d tree, octree, and linked-list data partitioning strategies, to optimise the pair-counting process. These methods are crucial for handling the massive volume of data efficiently. The implementation also includes parallel processing capabilities using shared-memory open multi-processing to further enhance performance and reduce computation times. Extensive validation and performance testing of the software are presented. Those have been performed by using various mock galaxy catalogues to ensure that it meets the stringent accuracy requirement of the Euclid mission. The results indicate that the software is robust and can reliably estimate the two-point correlation function, which is essential for deriving cosmological parameters with high precision. Furthermore, the paper discusses the expected performance of the software during different stages of Euclid Wide Survey observations and forecasts how the precision of the correlation function measurements will improve over the mission's timeline, highlighting the software's capability to handle large datasets efficiently.
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Funding information in the publication:
This work was supported by the ASI/INAF agreement n. 2018-23-HH.0 “Scientific activity for Euclid mission, Phase D”, the MIUR, PRIN 2017 research grant ‘From Darklight to DM: understanding the galaxy/matter connection to measure the Universe’ and the INFN project “InDark”. FM acknowledges the financial contribution from the grant PRIN-MUR 2022 20227RNLY3 ‘The concordance cosmological model: stress-tests with galaxy clusters’ supported by Next Generation EU and from the grant ASI n. 2024-10-HH.0 ‘Attività scientifiche per la missione Euclid – fase E’. This work has made use of CosmoHub. CosmoHub is developed and maintained by PIC, IFAE, CIEMAT, in collaboration with ICE-CSIC. It is partially financed by the European Union NextGenerationEU(PRTR-C17.I1) and by Generalitat de Catalunya, as well as by the grant EQC2021-007479-P funded by MCIN/AEI/10.13039/501100011033 and by the “European Union NextGenerationEU/PRTR”. 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 (https://www.euclid-ec.org).
