Euclid preparation

Author:

,Jelic-Cizmek G.ORCID,Sorrenti F.ORCID,Lepori F.,Bonvin C.ORCID,Camera S.ORCID,Castander F. J.ORCID,Durrer R.ORCID,Fosalba P.,Kunz M.ORCID,Lombriser L.ORCID,Tutusaus I.ORCID,Viglione C.,Sakr Z.,Aghanim N.,Amara A.,Andreon S.,Baldi M.,Bardelli S.,Bodendorf C.,Bonino D.,Branchini E.,Brescia M.,Brinchmann J.,Capobianco V.,Carbone C.,Cardone V. F.,Carretero J.,Casas S.,Castellano M.,Cavuoti S.,Cimatti A.,Congedo G.,Conselice C. J.,Conversi L.,Copin Y.,Corcione L.,Courbin F.,Courtois H. M.,Cropper M.,Degaudenzi H.,Di Giorgio A. M.,Dinis J.,Dubath F.,Dupac X.,Dusini S.,Farina M.,Farrens S.,Ferriol S.,Frailis M.,Franceschi E.,Fumana M.,Galeotta S.,Garilli B.,Gillis B.,Giocoli C.,Grazian A.,Grupp F.,Haugan S. V. H.,Hoekstra H.,Holmes W.,Hormuth F.,Hornstrup A.,Jahnke K.,Keihänen E.,Kermiche S.,Kiessling A.,Kilbinger M.,Kubik B.,Kurki-Suonio H.,Lilje P. B.,Lindholm V.,Lloro I.,Mansutti O.,Marggraf O.,Markovic K.,Martinet N.,Marulli F.,Massey R.,Medinaceli E.,Mei S.,Meneghetti M.,Merlin E.,Meylan G.,Moscardini L.,Munari E.,Niemi S.-M.,Padilla C.,Paltani S.,Pasian F.,Pedersen K.,Percival W. J.,Pettorino V.,Polenta G.,Poncet M.,Popa L. A.,Raison F.,Rebolo R.,Renzi A.,Rhodes J.,Riccio G.,Romelli E.,Roncarelli M.,Rossetti E.,Saglia R.,Sapone D.,Sartoris B.,Schneider P.,Schrabback T.,Secroun A.,Seidel G.,Serrano S.,Sirignano C.,Sirri G.,Stanco L.,Starck J.-L.,Surace C.,Tallada-Crespí P.,Tavagnacco D.,Taylor A. N.,Tereno I.,Toledo-Moreo R.,Torradeflot F.,Valentijn E. A.,Valenziano L.,Vassallo T.,Veropalumbo A.,Wang Y.,Weller J.,Zamorani G.,Zoubian J.,Zucca E.,Biviano A.,Boucaud A.,Bozzo E.,Colodro-Conde C.,Di Ferdinando D.,Graciá-Carpio J.,Liebing P.,Mauri N.,Neissner C.,Scottez V.,Tenti M.,Viel M.,Wiesmann M.,Akrami Y.,Allevato V.,Anselmi S.,Baccigalupi C.,Balaguera-Antolínez A.,Ballardini M.,Bruton S.,Burigana C.,Cabanac R.,Cappi A.,Carvalho C. S.,Castignani G.,Castro T.,Cañas-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.,Díaz-Sánchez A.,Escartin Vigo J. A.,Escoffier S.,Ferreira P. G.,Ferrero I.,Finelli F.,Gabarra L.,Ganga K.,García-Bellido J.,Giacomini F.,Gozaliasl G.,Guinet D.,Hildebrandt H.,Ilić S.,Jimenez Muñoz A.,Joudaki S.,Kajava J. J. E.,Kansal V.,Kirkpatrick C. C.,Legrand L.,Loureiro A.,Magliocchetti M.,Mainetti G.,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.,Patrizii L.,Pezzotta A.,Popa V.,Porciani C.,Potter D.,Pöntinen M.,Reimberg P.,Rocci P.-F.,Sánchez A. G.,Schneider A.,Schultheis M.,Sefusatti E.,Sereno M.,Silvestri A.,Simon P.,Spurio Mancini A.,Steinwagner J.,Testera G.,Tewes M.,Teyssier R.,Toft S.,Tosi S.,Troja A.,Tucci M.,Valiviita J.,Vergani D.,Tanidis K.

Abstract

In this paper we investigate the impact of lensing magnification on the analysis of Euclid’s spectroscopic survey using the multipoles of the two-point correlation function for galaxy clustering. We determine the impact of lensing magnification on cosmological constraints as well as the expected shift in the best-fit parameters if magnification is ignored. We considered two cosmological analyses: (i) a full-shape analysis based on the Λ cold dark matter (CDM) model and its extension w0waCDM and (ii) a model-independent analysis that measures the growth rate of structure in each redshift bin. We adopted two complementary approaches in our forecast: the Fisher matrix formalism and the Markov chain Monte Carlo method. The fiducial values of the local count slope (or magnification bias), which regulates the amplitude of the lensing magnification, have been estimated from the Euclid Flagship simulations. We used linear perturbation theory and modelled the two-point correlation function with the public code coffe. For a ΛCDM model, we find that the estimation of cosmological parameters is biased at the level of 0.4–0.7 standard deviations, while for a w0waCDM dynamical dark energy model, lensing magnification has a somewhat smaller impact, with shifts below 0.5 standard deviations. For a model-independent analysis aimed at measuring the growth rate of structure, we find that the estimation of the growth rate is biased by up to 1.2 standard deviations in the highest redshift bin. As a result, lensing magnification cannot be neglected in the spectroscopic survey, especially if we want to determine the growth factor, one of the most promising ways to test general relativity with Euclid. We also find that, by including lensing magnification with a simple template, this shift can be almost entirely eliminated with minimal computational overhead.

Publisher

EDP Sciences

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