A1 Refereed original research article in a scientific journal
Euclid preparation: LXXXII. Predicting star-forming galaxy scaling relations with the spectral stacking code SpectraPyle; 
Authors: Quai, S.; Pozzetti, L.; Talia, M.; Mancini, C.; Cassata, P.; Gabarra, L.; Le Brun, V.; Bolzonella, M.; Rossetti, E.; Kruk, S.; Granett, B. R.; Scarlata, C.; Moresco, M.; Zamorani, G.; Mao, Z.; Vergani, D.; Lopez Lopez, X.; Enia, A.; Daddi, E.; Allevato, V.; Zinchenko, I. A.; Magliocchetti, M.; Siudek, M.; Bisigello, L.; De Lucia, G.; Dickinson, H. J.; Lusso, E.; Hirschmann, M.; Cimatti, A.; Wang, L.; Sorce, J. G.; Huertas-Company, M.; Aghanim, N.; Amara, A.; Andreon, S.; Auricchio, N.; Baccigalupi, C.; Baldi, M.; Bardelli, S.; Biviano, A.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Cañas-Herrera, G.; Capobianco, V.; Carbone, C.; Carretero, J.; Casas, S.; Castellano, M.; Castignani, G.; Cavuoti, S.; Chambers, K. C.; Colodro-Conde, C.; Congedo, G.; Conselice, C. J.; Conversi, L.; Copin, Y.; Courbin, F.; Courtois, H. M.; Da Silva, A.; Degaudenzi, H.; de la Torre, S.; Dole, H.; Douspis, M.; Dubath, F.; Dupac, X.; Dusini, S.; Ealet, A.; Escoffier, S.; Farina, M.; Farinelli, R.; Faustini, F.; Ferriol, S.; Finelli, F.; Fourmanoit, N.; Frailis, M.; Franceschi, E.; Galeotta, S.; George, K.; Gillard, W.; Gillis, B.; Giocoli, C.; Gracia-Carpio, J.; Grazian, A.; Grupp, F.; Guzzo, L.; Haugan, S. V. H.; Holmes, W.; Hook, I. M.; Hormuth, F.; Hornstrup, A.; Hudelot, P.; Jahnke, K.; Jhabvala, M.; Joachimi, B.; Keihänen, E.; Kermiche, S.; Kiessling, A.; 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.; Marcin, S.; Marggraf, O.; Martinelli, M.; Martinet, N.; Marulli, F.; Massey, R. J.; Medinaceli, E.; Mei, S.; Melchior, M.; Mellier, Y.; Meneghetti, M.; Merlin, E.; Meylan, G.; Mora, A.; Moscardini, L.; 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.; Raison, F.; Rebolo, R.; Renzi, A.; Rhodes, J.; Riccio, G.; Romelli, E.; Roncarelli, M.; 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.; Simon, P.; Sirignano, C.; Sirri, G.; Stanco, L.; Starck, J.-L.; Steinwagner, J.; Tallada-Crespí, P.; Tavagnacco, D.; Taylor, A. N.; Teplitz, H. I.; Tereno, I.; Toft, S.; Toledo-Moreo, R.; Torradeflot, F.; Tutusaus, I.; Valenziano, L.; Valiviita, J.; Vassallo, T.; Verdoes Kleijn, G.; Veropalumbo, A.; Vibert, D.; Wang, Y.; Weller, J.; Zucca, E.; Ballardini, M.; Bozzo, E.; Burigana, C.; Cabanac, R.; Cappi, A.; Di Ferdinando, D.; Escartin Vigo, J. A.; Martín-Fleitas, J.; Matthew, S.; Mauri, N.; Metcalf, B. R.; Pezzotta, A.; Pöntinen, M.; Porciani, C.; Risso, I.; Scottez, V.; Sereno, M.; Tenti, M.; Viel, M.; Wiesmann, M.; Akrami, Y.; Andika, I. T.; Anselmi, S.; Archidiacono, M.; Atrio-Barandela, F.; Bergamini, P.; Bertacca, D.; Bethermin, M.; Blanchard, A.; Blot, L.; Borgani, S.; Brown, M. L.; Bruton, S.; Calabro, A.; Camacho Quevedo, B.; Caro, F.; Carvalho, C. S.; Castro, T.; Cogato, F.; Conseil, S.; Contini, T.; Cooray, A. R.; Cucciati, O.; Davini, S.; Desprez, G.; Díaz-Sánchez, A.; Diaz, J. J.; Di Domizio, S.; Diego, J. M.; Fang, Y.; Ferrari, A. G.; Finoguenov, A.; Fontana, A.; Fontanot, F.; Franco, A.; Ganga, K.; García-Bellido, J.; Gasparetto, T.; Gautard, V.; Gaztanaga, E.; Giacomini, F.; Gianotti, F.; Gozaliasl, G.; Guidi, M.; Gutierrez, C. M.; Hall, A.; Hemmati, S.; Hernández-Monteagudo, C.; Hildebrandt, H.; Hjorth, J.; Kajava, J. J. E.; Kang, Y.; Kansal, V.; Karagiannis, D.; Kiiveri, K.; Kirkpatrick, C. C.; Legrand, L.; Lembo, M.; Lepori, F.; Leroy, G.; Lesci, G. F.; Lesgourgues, J.; Leuzzi, L.; Liaudat, T. I.; Liu, S. J.; Loureiro, A.; Macias-Perez, J.; Maggio, G.; Mannucci, F.; Maoli, R.; Martins, C. J. A. P.; Maurin, L.; Miluzio, M.; Monaco, P.; Moretti, C.; Morgante, G.; Nadathur, S.; Naidoo, K.; Navarro-Alsina, A.; Nesseris, S.; Passalacqua, F.; Paterson, K.; Patrizii, L.; Pisani, A.; Potter, D.; Radovich, M.; Rocci, P.-F.; Rodighiero, G.; Sacquegna, S.; Sahlén, M.; Sanders, D. B.; Sarpa, E.; Schneider, A.; Sciotti, D.; Sellentin, E.; Shankar, F.; Smith, L. C.; Tanidis, K.; Tao, C.; Testera, G.; Teyssier, R.; Tosi, S.; Troja, A.; Tucci, M.; Valieri, C.; Venhola, A.; Verza, G.; Vielzeuf, P.; Walton, N. A.; Euclid Collaboration
Publisher: EDP Sciences
Publication year: 2026
Journal: Astronomy and Astrophysics
Article number: A232
Volume: 707
ISSN: 0004-6361
eISSN: 1432-0746
DOI: https://doi.org/10.1051/0004-6361/202557329
Publication's open availability at the time of reporting: Open Access
Publication channel's open availability : Open Access publication channel
Web address : https://doi.org/10.1051/0004-6361/202557329
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/523415642
Self-archived copy's licence: CC BY
Self-archived copy's version: Publisher`s PDF
We introduce SpectraPyle, a versatile spectral stacking pipeline developed for the Euclid mission's NISP spectroscopic surveys, aimed at extracting faint emission lines and spectral features from large galaxy samples in the Wide and Deep Surveys. Designed for computational efficiency and flexible configuration, SpectraPyle supports the processing of extensive datasets critical to Euclid's non-cosmological science goals. We validated the pipeline using simulated spectra processed to match Euclid's expected final data quality. Stacking enables robust recovery of key emission lines, including Hα, Hβ, [O III], and [N II], below individual detection limits. However, the measurement of galaxy properties such as star formation rate, dust attenuation, and gas-phase metallicity are biased at stellar mass below log10(M/ M⊙) ∼9 due to the flux-limited nature of Euclid spectroscopic samples, where spectra below the detection threshold lack reliable redshift measurements, preventing effective stacking. The star formation rate- stellar mass relation of the parent sample is recovered reliably only in the deep survey for log10(M/ M⊙) ≲10, whereas the metallicity- mass relation is recovered more accurately over a wider mass range. These limitations are caused by the increased fraction of redshift measurement errors at lower masses and fluxes. We examined the impact of residual redshift contaminants that arises from mis-identified emission lines and noise spikes, on stacked spectra. Even after stringent quality selections, low-level contamination (< 6%) has minimal impact on line fluxes due to the systematically weaker emission of contaminants. A percentile-based analysis of stacked spectra provides a sensitive diagnostic for detecting contamination via coherent spurious features at characteristic wavelengths. While our simulations include most instrumental effects, real Euclid data will require a further refinement of contamination mitigation strategies.
Keywords:
galaxies: general, galaxies: star formation, techniques: spectroscopic
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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 BMIMI, 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 (www.euclid-ec.org). S.Q., L.P., M.T., B.G., A.E., E.D., V.A., G.D.L., H.D. acknowledge support from the ELSA project. ‘ELSA: Euclid Legacy Science Advanced analysis tools’ (Grant Agreement no. 101135203) is 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 or Innovate UK. Neither the European Union nor the granting authority can be held responsible for them. UK participation is funded through the UK HORIZON guarantee scheme under Innovate UK grant 10093177. V.A. and E.L. acknowledge the support from the INAF Large Grant ‘AGN & Euclid: a close entanglement’ Ob. Fu. 01.05.23.01.14. C.S. acknowledges the support of NASA ROSES Grant 12-EUCLID11-0004 M.S. acknowledges support by the State Research Agency of the Spanish Ministry of Science and Innovation under the grants ‘Galaxy Evolution with Artificial Intelligence’ (PGC2018-100852-A-I00) and ‘BASALT’ (PID2021-126838NB-I00) and the Polish National Agency for Academic Exchange (Bekker grant BPN/BEK/2021/1/00298/DEC/1). This work was partially supported by the European Union’s Horizon 2020 Research and Innovation program under the Maria Sklodowska-Curie grant agreement (No. 754510). L.R. acknowledges support from the Next Generation EU funds within the National Recovery and Resilience Plan (PNRR), Mission 4 – Education and Research, Component 2 – From Research to Business (M4C2), Investment Line 3.1 – Strengthening and creation of Research Infrastructures, Project IR0000034 – “STILES - Strengthening the Italian Leadership in ELT and SKA”.
