<i>Euclid</i> preparation

Context. The Euclid galaxy survey is designed to measure the spectroscopic redshift of emission-line galaxies (ELGs) by identifying the H α emission line in their slitless spectra. The efficacy of this approach crucially depends on the signal-to-noise ratio (S/N) of the line, as sometimes noise fluctuations in the spectrum continuum can be misidentified as H α . In addition, other genuine strong emission lines can be mistaken for H α , depending on the redshift of the source. Both effects lead to ambiguities in the redshift measurement that can result in catastrophic redshift errors and the inclusion of ‘interloper’ galaxies in the sample. Aims. This paper forecasts the impact on the galaxy clustering analysis of the expected redshift errors in the Euclid spectroscopic sample. Specifically, it investigates the effect of the redshift interloper contamination on the galaxy two-point correlation function (2PCF) and, in turn, on the inferred growth rate of structure fσ 8 and Alcock–Paczynski (AP) parameters α ∥ and α ⊥ . Methods. This work is based on the analysis of 1000 synthetic spectroscopic catalogues, the EuclidLargeMocks, which mimic the area and selection function of the Euclid Data Release 1 (DR1) sample. We estimated the 2PCF of contaminated catalogues and separated the different contributions, particularly those coming from galaxies with correctly measured redshift and from contaminants. We explored different models of increasing complexity to describe the measured 2PCF at a fixed cosmology, with the aim of identifying the most efficient model to reproduce the data. Finally, we performed a cosmological inference and evaluated the systematic error on the inferred fσ 8 , α ∥ , and α ⊥ values associated with different models. Results. Our results demonstrate that a minimal modelling approach, which only accounts for an attenuation of the clustering signal regardless of the type of contaminants, is sufficient to recover the correct values of fσ 8 , α ∥ , and α ⊥ at DR1. The accuracy and precision of the estimated AP parameters are largely insensitive to the presence of interlopers. The adoption of a minimal modelling induces a 1%–3% systematic error on the growth rate of structure estimation, depending on the considered redshift. However, this error remains smaller than the statistical error expected for the Euclid DR1 analysis.

Authors

Institutions

Publication Details

Journal
Astronomy and Astrophysics
Published
2025-12-18
DOI
https://doi.org/10.1051/0004-6361/202555402
Citations
1
Primary Topic
Galaxies: Formation, Evolution, Phenomena
Type
article
Field-Weighted Citation Impact
1.15
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Euclid preparation

F Passalacqua, Will J. Percival, S Sacquegna, F. Pasian et al.
1 citations
Astronomy and Astrophysics
Galaxies: Formation, Evolution, Phenomena
1.15
article

Euclid preparation

F Passalacqua, Will J. Percival, S Sacquegna, F. Pasian, Y. Mellier, J. Martín-Fleitas, F. Torradeflot, S. Mei, I Tereno, E. Gaztanaga, F. Marulli, I. Ferrero, M. Kunz, A. Secroun, D Sapone, J Brinchmann, E. Bozzo, J. García-Bellido, J. Hjorth, G. Sirri, R Nakajima, S Bardelli, J. Steinwagner, E. Romelli, D. B. Sanders, A.G Ferrari, K. Markovic, A. Venhola, H Hildebrandt, S. Di Domizio, A. Navarro-Alsina, C. Giocoli, P. Schneider, Francesca Lepori, L Patrizii, O. Mansutti, W Gillard, S. Davini, X. Dupac, Carmencita David Padilla, Patrice Simon, Paola Dimauro, Louis Maurin, K. Ganga, Pietro Battaglia, J. Rhodes, F Courbin, P. Tallada-Crespí, Michael D. Brown, M. Crocce, A. Díaz‐Sánchez, E Maiorano, J.J Diaz, E. Sellentin, M Radovich, L. Guzzo, L. Moscardini, F Faustini, Daniele Bertacca, C.J.A.P. Martins, A. Biviano, A.R. Cooray, T. Schrabback, L. Gabarra, C. Surace, J Le Graet, M. Jhabvala, M. Kilbinger, H Degaudenzi, S. V. H. Haugan, V. Scottez, A Enia, A Troja, C.J. Conselice, C. Valieri, G. Castignani, G. Leroy, M Castellano, C. Baccigalupi, B. Camacho Quevedo, S Bruton, M. Moresco, S. Paltani, W.G. Hartley, B. R. Granett, Shahab Joudaki, M. Poncet, S. Pires, J.W Nightingale, A. Fontana, N Auricchio, P. Tallada-Crespí, C. Scarlata, S. Marcin, J. Carretero, D. Maino, T.I Liaudat, S Toft, F Finelli, K. Ganga, N Tessore, M Ballardini, Sébastien Tosi, A. M. Di Giorgio, S Quai, J. Weller, C. Colodro-Conde, Graeme E. Addison, Christophe Benoıst, M Kümmel, M Lembo, H Kurki-Suonio, I Risso, G. Parimbelli, N. Aghanim, K Paterson, B. Joachimi, V. Allevato, D. Vibert, C Sirignano, A. Bonchi, M. Martinelli, D. Karagiannis, S. Escoffier, M. Baldi, T. Castro, L Blot, E Keihänen, D. Potter, S Serrano, G. Meylan, D. Vergani, E. Medinaceli, G. De Lucia, W. Gillard, C. Giocoli, M Sahlén, F. De Paolis, C. Kirkpatrick, A. Finoguenov, R. Maoli, Marco Bonici, Jenny G. Sorce, E. Merlin, R. B. Metcalf, V.F Cardone, B. Sartoris, F. Raison, Sergey Kruk, M. Pöntinen, S. Lee, F. M. Zerbi, N.A. Walton, M. Béthermin, E. Branchini, A. Balestra, Chihiro Tao, R. Saglia, M. Farina, S. Camera, F. Mannucci, M. Magliocchetti, S. Maurogordato, S Dusini, E. Sefusatti, C.A.J Duncan, F. Hormuth, J. Weller, S Borgani, K. George, G. Lavaux, R. Farinelli, L. Legrand, F. Giacomini, A. Balaguera-Antolínez, E. Franceschi, F. Dubath, P.B. Lilje, J.A Schewtschenko, K Jahnke, Yun Wang, M. Brescia, K. Kiiveri, J.M. Diego, P. Monaco, M. Scodeggio, N. Martinet, V Capobianco, M. Miluzio, María Guidi, J. Gracia-Carpio, A. Kiessling, F. Grupp, I.T Andika, M. Viel, R Teyssier, A Amara, A. Cappi, K Tanidis, E. Rossetti, LAURENCE C. SMITH, G.F Lesci, K. C. Chambers, M. Archidiacono, F. Finelli⋆, V. Lindholm, D. Bonino, T. Vassallo, E. Sefusatti, P.-F Rocci, A da Silva, M Roncarelli, S. Cavuoti, B Gillis, P. Hudelot, G. Gozaliasl, P. Liebing, P. Bergamini, R Massey, E Zucca, A. Cappi, Z. Sakr, Yongshui Kang, C. Carbone, Shoubaneh Hemmati, B. Altieri, S. Ligori, Alice Pisani, F Caro, E Sarpa, G. Seidel, A. A. Franco, R. Cabanac, S. Ferriol, A. Renzi, A. Cimatti, M Melchior, A.N. Taylor, M. Douspis, A Veropalumbo, L.A. Popa, Kathryn McCarthy, C. Burigana, A.M.C Le Brun, M. Frailis, M Sereno, Vinay Kansal, L. Stanco, C. S. Carvalho, O. Marggraf, Y. Akrami, S. Kermiche, F. Atrio‐Barandela, S. Andreon, Claudio Moretti, H. M. Courtois, F. Cogato, D Sciotti, Yiming Fang, A. J. Hall, G. Riccio, C. M. Gutiérrez, J.E. Kajava, G. Testera, S Alvi, M Bolzonella, V. Gautard, I. Lloro, V. Pettorino, C Neissner, M. Tucci, M. Tenti, C. Hernández-Monteagudo, G. Mainetti, R. Rebolo, A. Schneider, C Porciani, J. Macias-Perez, G. Zamorani, I Tutusaus, S. Matthew, M. Wiesmann, R. Kohley, K Naidoo, H. Dole, L. Conversi, M. Fumana, G Morgante, G Polenta, K. Pedersen, J.A. Escartin Vigo, D. Di Ferdinando, B. Kubik, N. Mauri, Y. Ascasíbar, J Valiviita, M. Seiffert, A. Grazian, F Oppizzi, S. Casas, S. Fotopoulou, N. Fourmanoit, S. Galeotta, G Verza, L Valenziano, A. Loureiro, W. N. Holmes, F. Gianotti, M. N. Bremer, S. de la Torre, S. Àvila, S.-M Niemi, H. Böhringer, V. Le Brun, G. Congedo, A. Mora, L. Leuzzi, Edoardo Maragliano
article en
1 citations

Abstract

Context. The Euclid galaxy survey is designed to measure the spectroscopic redshift of emission-line galaxies (ELGs) by identifying the H α emission line in their slitless spectra. The efficacy of this approach crucially depends on the signal-to-noise ratio (S/N) of the line, as sometimes noise fluctuations in the spectrum continuum can be misidentified as H α . In addition, other genuine strong emission lines can be mistaken for H α , depending on the redshift of the source. Both effects lead to ambiguities in the redshift measurement that can result in catastrophic redshift errors and the inclusion of ‘interloper’ galaxies in the sample. Aims. This paper forecasts the impact on the galaxy clustering analysis of the expected redshift errors in the Euclid spectroscopic sample. Specifically, it investigates the effect of the redshift interloper contamination on the galaxy two-point correlation function (2PCF) and, in turn, on the inferred growth rate of structure fσ 8 and Alcock–Paczynski (AP) parameters α ∥ and α ⊥ . Methods. This work is based on the analysis of 1000 synthetic spectroscopic catalogues, the EuclidLargeMocks, which mimic the area and selection function of the Euclid Data Release 1 (DR1) sample. We estimated the 2PCF of contaminated catalogues and separated the different contributions, particularly those coming from galaxies with correctly measured redshift and from contaminants. We explored different models of increasing complexity to describe the measured 2PCF at a fixed cosmology, with the aim of identifying the most efficient model to reproduce the data. Finally, we performed a cosmological inference and evaluated the systematic error on the inferred fσ 8 , α ∥ , and α ⊥ values associated with different models. Results. Our results demonstrate that a minimal modelling approach, which only accounts for an attenuation of the clustering signal regardless of the type of contaminants, is sufficient to recover the correct values of fσ 8 , α ∥ , and α ⊥ at DR1. The accuracy and precision of the estimated AP parameters are largely insensitive to the presence of interlopers. The adoption of a minimal modelling induces a 1%–3% systematic error on the growth rate of structure estimation, depending on the considered redshift. However, this error remains smaller than the statistical error expected for the Euclid DR1 analysis.

Astronomy and AstrophysicsVol. 707
Université Claude Bernard Lyon 1 (FR), Institut polytechnique de Grenoble (FR), University of Geneva (CH), Institució Catalana de Recerca i Estudis Avançats (ES), Leiden University (NL), California Institute of Technology (US), University of Copenhagen (DK), Centre National de la Recherche Scientifique (FR), University of Minnesota (US), Goddard Space Flight Center (US), University of Hawaii System (US), Jet Propulsion Laboratory (US), Université Toulouse III - Paul Sabatier (FR), Consejo Superior de Investigaciones Científicas (ES), University of Bonn (DE), Scuola Internazionale Superiore di Studi Avanzati (IT), University of Padua (IT), University of Lisbon (PT), University of Salento (IT), Johns Hopkins University (US), University of Waterloo (CA), Universidad de La Laguna (ES), Stockholm University (SE), University of Groningen (NL), Université Fédérale de Toulouse Midi-Pyrénées (FR), Lyon College (US), Université Catholique de Lille (FR), Universidade do Porto (PT), Perimeter Institute (CA), University of Oslo (NO), Universidad de Salamanca (ES), Institute for High Energy Physics (ES), University of Milan (IT), Durham University (GB), Universität Innsbruck (AT), University of Saint Joseph (US), Princeton University (US), University of Ferrara (IT), Université Côte d'Azur (FR), University of Zurich (CH), University of California, Irvine (US), Université Paris Cité (FR), Aix-Marseille Université (FR), Heidelberg University (DE), University of Cambridge (GB), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), Université Paris Sciences et Lettres (FR), Université Paris-Saclay (FR), Centre National d'Études Spatiales (FR), Arcetri Astrophysical Observatory (IT), Helsinki Institute of Physics (FI), Astronomical Observatory of Rome (IT), Trieste Astronomical Observatory (IT), Institut d'Astrophysique de Paris (FR), Astronomical Observatory of Capodimonte (IT), European Space Agency (FR), Laboratoire AstroParticule et Cosmologie (FR), Observatoire astronomique de Strasbourg (FR), Brera Astronomical Observatory (IT), University of Surrey (GB), FHNW University of Applied Sciences and Arts Northwestern Switzerland (CH), United Kingdom Space Agency (GB), Universidad Politécnica de Cartagena (ES), Department of Space (IN), University of Bristol (GB), Sorbonne Université (FR), University of Oxford (GB), Park University (US), Osservatorio astronomico di Bologna (IT), Astrophysique, Instrumentation et Modélisation (FR), Max Planck Institute for Physics (DE), Valongo Observatory (BR), Institute of Astrophysics and Space Sciences (PT), ARC Centre of Excellence for Dark Matter Particle Physics (AU), Max Planck Institute for Extraterrestrial Physics (DE), Institut d'Estudis Espacials de Catalunya (ES), Istituto Nazionale di Fisica Nucleare, Sezione di Lecce (IT), Istituto Nazionale di Fisica Nucleare, Sezione di Torino (IT), Institute for Space Astrophysics and Planetology (IT), Institut d'Astrophysique Spatiale (FR), Max Planck Institute for Astrophysics (DE), International University of Beirut (LB), Institut Català de Ciències del Clima (ES), Istituto Nazionale di Fisica Nucleare, Sezione di Padova (IT), Osservatorio Astrofisico di Torino (IT), Royal Observatory (GB), Istituto Nazionale di Fisica Nucleare, Sezione di Ferrara (IT), SKA Observatory (GB), Istituto Nazionale di Fisica Nucleare, Sezione di Napoli (IT), Centro de Astrofísica da Universidade do Porto (PT), Max Planck Institute for Astronomy (DE), Institute of Space Sciences (ES), Laboratoire de Physique Théorique (FR), DAWN Center for Independent Living (US), Centre for Theoretical Physics and Astrophysics (UZ), Istituto di Radioastronomia di Bologna (IT), Kavli Institute for the Physics and Mathematics of the Universe (JP), Federico II University Hospital (IT), Unidades Centrales Científico-Técnicas (ES), Mathematical Institute of the Slovak Academy of Sciences (SK), Institute of Astronomy (RU), Institute of Theoretical Physics (CN), Istituto Nazionale di Fisica Nucleare, Sezione di Genova (IT), Observatoire de la Côte d’Azur (FR), CEA Paris-Saclay (FR), Naples Anesthesia & Physician Associates (US), Instituto de Astrofísica de Canarias (ES), Felix Scholarship (GB), Institut National de Physique Nucléaire et de Physique des Particules (FR), Astronomical Institute of the Slovak Academy of Sciences (SK), Istituto Nazionale di Fisica Nucleare, Sezione di Milano (IT), Institute of Space Science - INFLPR Subsidiary (RO), Computing Center (RU), Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (FR), Engineering Science Analysis (United States) (US), Astronomy and Space (AU), Istituto Nazionale di Fisica Nucleare, Sezione di Bologna (IT), Port d'Informació Científica (ES), Istituto Nazionale di Fisica Nucleare, Sezione di Trieste (IT), Institute for Fundamental Physics of the Universe (IT), Instituto de Física de Cantabria (ES), Flatiron Health (United States) (US), St. Joseph Medical Center (US), Istituto Nazionale di Fisica Nucleare, Sezione di Roma I (IT), Osservatorio Astronomico di Padova (IT), Bristol Robotics Laboratory (GB), European Space Research Institute (IT), Institut de Recherche sur les Lois Fondamentales de l'Univers (FR), Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (ES), Institut de Recherche en Astrophysique et Planétologie (FR), Infrared Processing and Analysis Center (US), Osservatorio di Astrofisica e Scienza dello Spazio, Flatiron Institute (US), European Space Research and Technology Centre (NL), University College London (GB), Imperial College London (GB), École Polytechnique Fédérale de Lausanne (CH), University of Turin (IT), Swinburne University of Technology (AU), Case Western Reserve University (US), Technical University of Munich (DE), University of Portsmouth (GB), University of Chile (CL), Heidelberg Institute for Theoretical Studies (DE), École Centrale de Lille (FR), Ludwig-Maximilians-Universität München (DE), University of Genoa (IT), Newcastle University (GB), Sapienza University of Rome (IT), University of the Western Cape (ZA), National Institute for Astrophysics (IT), RWTH Aachen University (DE), Université Grenoble Alpes (FR), Netherlands Institute for Radio Astronomy (NL), University of Bologna (IT), Technical University of Denmark (DK), University of Edinburgh (GB), Aalto University (FI)
Openalex Percentile: Top 14%
Galaxies: Formation, Evolution, Phenomena
1.15
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.