Euclid preparation: VII. Forecast validation for Euclid cosmological probes

Euclid Collaboration, A. Blanchard, S. Camera, C. Carbone, V. F. Cardone +149 more
10/21/2019
astro-ph.CO

Official code: euclidist-forecasting/fisher_for_public (9 stars, last commit 2020-05-14).

Abstract

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. Estimation of the expected performance of the experiment, in terms of predicted constraints on cosmological parameters, has so far relied on different methodologies and numerical implementations, developed for different observational probes and for their combination. In this paper we present validated forecasts, that combine both theoretical and observational expertise for different cosmological probes. This is presented to provide the community with reliable numerical codes and methods for Euclid cosmological forecasts. We describe in detail the methodology adopted for Fisher matrix forecasts, applied to galaxy clustering, weak lensing and their combination. We estimate 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 that can be used by the reader to validate their own codes if required. We present new cosmological forecasts for Euclid. We find that results depend on the specific cosmological model and remaining freedom in each setup, i.e. flat or non-flat spatial cosmologies, or different cuts at nonlinear scales. The validated numerical implementations can now be reliably used for any setup. We present results for an optimistic and a pessimistic choice of such 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.

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Code Implementations(1)

euclidist-forecasting/fisher_for_publicOfficial100%

This repository contains representative Fisher matrices and plotting scripts created by the IST:Forecasts.

92Shell, PythonMar 20, 20196 years ago

Cite this paper

@article{collaboration2019euclid,
  title  = {Euclid preparation: VII. Forecast validation for Euclid cosmological probes},
  author = {Euclid Collaboration and A. Blanchard and S. Camera and C. Carbone and V. F. Cardone and S. Casas and S. Clesse and S. Ilić and M. Kilbinger and T. Kitching and M. Kunz and F. Lacasa and E. Linder and E. Majerotto and K. Markovič and M. Martinelli and V. Pettorino and A. Pourtsidou and Z. Sakr and A. G. Sánchez and D. Sapone and I. Tutusaus and S. Yahia-Cherif and V. Yankelevich and S. Andreon and H. Aussel and A. Balaguera-Antolínez and M. Baldi and S. Bardelli and R. Bender and A. Biviano and D. Bonino and A. Boucaud and E. Bozzo and E. Branchini and S. Brau-Nogue and M. Brescia and J. Brinchmann and C. Burigana and R. Cabanac and V. Capobianco and A. Cappi and J. Carretero and C. S. Carvalho and R. Casas and F. J. Castander and M. Castellano and S. Cavuoti and A. Cimatti and R. Cledassou and C. Colodro-Conde and G. Congedo and C. J. Conselice and L. Conversi and Y. Copin and L. Corcione and J. Coupon and H. M. Courtois and M. Cropper and A. Da Silva and S. de la Torre and D. Di Ferdinando and F. Dubath and F. Ducret and C. A. J. Duncan and X. Dupac and S. Dusini and G. Fabbian and M. Fabricius and S. Farrens and P. Fosalba and S. Fotopoulou and N. Fourmanoit and M. Frailis and E. Franceschi and P. Franzetti and M. Fumana and S. Galeotta and W. Gillard and B. Gillis and C. Giocoli and P. Gómez-Alvarez and J. Graciá-Carpio and F. Grupp and L. Guzzo and H. Hoekstra and F. Hormuth and H. Israel and K. Jahnke and E. Keihanen and S. Kermiche and C. C. Kirkpatrick and R. Kohley and B. Kubik and H. Kurki-Suonio and S. Ligori and P. B. Lilje and I. Lloro and D. Maino and E. Maiorano and O. Marggraf and N. Martinet and F. Marulli and R. Massey and E. Medinaceli and S. Mei and Y. Mellier and B. Metcalf and J. J. Metge and G. Meylan and M. Moresco and L. Moscardini and E. Munari and R. C. Nichol and S. Niemi and A. A. Nucita and C. Padilla and S. Paltani and F. Pasian and W. J. Percival and S. Pires and G. Polenta and M. Poncet and L. Pozzetti and G. D. Racca and F. Raison and A. Renzi and J. Rhodes and E. Romelli and M. Roncarelli and E. Rossetti and R. Saglia and P. Schneider and V. Scottez and A. Secroun and G. Sirri and L. Stanco and J. -L. Starck and F. Sureau and P. Tallada-Crespí and D. Tavagnacco and A. N. Taylor and M. Tenti and I. Tereno and R. Toledo-Moreo and F. Torradeflot and L. Valenziano and T. Vassallo and G. A. Verdoes Kleijn and M. Viel and Y. Wang and A. Zacchei and J. Zoubian and E. Zucca},
  year   = {2019},
  eprint = {1910.09273},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1910.09273}
}

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