Euclid preparation
Authors:   Euclid Collaboration, Blanchard A. , Camera S. , Carbone C. , Cardone V. F. , Casas S. , Clesse S. , Ilić S. , Kilbinger M. , Kitching T. , Kunz M. , Lacasa F. , Linder E. , Majerotto E. , Markovič K. , Martinelli M. , Pettorino V. , Pourtsidou A. , Sakr Z. , Sánchez A. G. , Sapone D. , Tutusaus I. , Yahia-Cherif S. , Yankelevich V. , Andreon S. , Aussel H. , Balaguera-Antolínez A. , Baldi M. , Bardelli S. , Bender R. , Biviano A. , Bonino D. , Boucaud A. , Bozzo E. , Branchini E. , Brau-Nogue S. , Brescia M. , Brinchmann J. , Burigana C. , Cabanac R. , Capobianco V. , Cappi A. , Carretero J. , Carvalho C. S. , Casas R. , Castander F. J. , Castellano M. , Cavuoti S. , Cimatti A. , Cledassou R. , Colodro-Conde C. , Congedo G. , Conselice C. J. , Conversi L. , Copin Y. , Corcione L. , Coupon J. , Courtois H. M. , Cropper M. , Da Silva A. , de la Torre S. , Di Ferdinando D. , Dubath F. , Ducret F. , Duncan C. A. J. , Dupac X. , Dusini S. , Fabbian G. , Fabricius M. , Farrens S. , Fosalba P. , Fotopoulou S. , Fourmanoit N. , Frailis M. , Franceschi E. , Franzetti P. , Fumana M. , Galeotta S. , Gillard W. , Gillis B. , Giocoli C. , Gómez-Alvarez P. , Graciá-Carpio J. , Grupp F. , Guzzo L. , Hoekstra H. , Hormuth F. , Israel H. , Jahnke K. , Keihanen E. , Kermiche S. , Kirkpatrick C. C. , Kohley R. , Kubik B. , Kurki-Suonio H. , Ligori S. , Lilje P. B. , Lloro I. , Maino D. , Maiorano E. , Marggraf O. , Martinet N. , Marulli F. , Massey R. , Medinaceli E. , Mei S. , Mellier Y. , Metcalf B. , Metge J. J. , Meylan G. , Moresco M. , Moscardini L. , Munari E. , Nichol R. C. , Niemi S. , Nucita A. A. , Padilla C. , Paltani S. , Pasian F. , Percival W. J. , Pires S. , Polenta G. , Poncet M. , Pozzetti L. , Racca G. D. , Raison F. , Renzi A. , Rhodes J. , Romelli E. , Roncarelli M. , Rossetti E. , Saglia R. , Schneider P. , Scottez V. , Secroun A. , Sirri G. , Stanco L. , Starck J.-L. , Sureau F. , Tallada-Crespí P. , Tavagnacco D. , Taylor A. N. , Tenti M. , Tereno I. , Toledo-Moreo R. , Torradeflot F. , Valenziano L. , Vassallo T. , Verdoes Kleijn G. A. , Viel M. , Wang Y. , Zacchei A. , Zoubian J. , Zucca E. 
Published: July 2020

Aims. The Euclid space telescope will measure the shapes and redshifts of galaxies to reconstruct the expansion history of the Universe and the growth of cosmic structures. The estimation of the expected performance of the experiment, in terms of predicted constraints on cosmological parameters, has so far relied on various individual methodologies and numerical implementations, which were developed for different observational probes and for the combination thereof. In this paper we present validated forecasts, which combine both theoretical and observational ingredients for different cosmological probes. This work is presented to provide the community with reliable numerical codes and methods for Euclid cosmological forecasts.

Methods. We describe in detail the methods adopted for Fisher matrix forecasts, which were applied to galaxy clustering, weak lensing, and the combination thereof. We estimated the required accuracy for Euclid forecasts and outline a methodology for their development. We then compare and improve different numerical implementations, reaching uncertainties on the errors of cosmological parameters that are less than the required precision in all cases. Furthermore, we provide details on the validated implementations, some of which are made publicly available, in different programming languages, together with a reference training-set of input and output matrices for a set of specific models. These can be used by the reader to validate their own implementations if required.

Results. We present new cosmological forecasts for Euclid. We find that results depend on the specific cosmological model and remaining freedom in each setting, for example flat or non-flat spatial cosmologies, or different cuts at non-linear scales. The numerical implementations are now reliable for these settings. We present the results for an optimistic and a pessimistic choice for these types of settings. We demonstrate that the impact of cross-correlations is particularly relevant for models beyond a cosmological constant and may allow us to increase the dark energy figure of merit by at least a factor of three.