S. Casas, J. Lesgourgues, N. Schöneberg, V. M. Sabarish, L. Rathmann, M. Doerenkamp, M. Archidiacono, E. Bellini, S. Clesse, N. Frusciante, M. Martinelli, F. Pace, D. Sapone, Z. Sakr, A. Blanchard, T. Brinckmann, S. Camera, C. Carbone, S. Ilic, K. Markovic, V. Pettorino, I. Tutusaus, N. Aghanim, A. Amara, L. Amendola, N. Auricchio, M. Baldi, D. Bonino, E. Branchini, M. Brescia, J. Brinchmann, V. Capobianco, V. F. Cardone, J. Carretero, M. Castellano, S. Cavuoti, A. Cimatti, R. Cledassou, G. Congedo, L. Conversi, Y. Copin, L. Corcione, F. Courbin, M. Cropper, H. Degaudenzi, J. Dinis, M. Douspis, F. Dubath, X. Dupac, S. Dusini, S. Farrens, M. Frailis, E. Franceschi, M. Fumana, S. Galeotta, B. Garilli, B. R. Gillis, C. Giocoli, A. Grazian, F. Grupp, L. Guzzo, S. V. H. Haugan, F. Hormuth, A. Hornstrup, K. Jahnke, M. Kümmel, A. Kiessling, M. Kilbinger, T. D. Kitching, M. Kunz, H. Kurki-Suonio, S. Ligori, P. B. Lilje, I. Lloro, O. Mansutti, O. Marggraf, F. Marulli, R. Massey, E. Medinaceli, S. Mei, M. Meneghetti, E. Merlin, G. Meylan, M. Moresco, L. Moscardini, E. Munari, S. -. Niemi, C. Padilla, S. Paltani, F. Pasian, K. Pedersen, W. J. Percival, S. Pires, G. Polenta, M. Poncet, L. A. Popa, F. Raison, A. Renzi, J. D. Rhodes, G. Riccio, E. Romelli, M. Roncarelli, E. Rossetti, R. Saglia, B. Sartoris, P. Schneider, A. Secroun, G. Seidel, S. Serrano, C. Sirignano, G. Sirri, L. Stanco, J. -. Starck, C. Surace, P. Tallada-Crespí, A. N. Taylor, I. Tereno, R. Toledo-Moreo, F. Torradeflot, E. A. Valentijn, L. Valenziano, T. Vassallo, Y.-T. Wang, J. Weller, G. Zamorani, J. Zoubian, V. Scottez, A. Veropalumbo
Abstract
CLASS
and CAMB
in the context of Euclid.MontePython
forecasts agree very well with previous Fisher forecasts published by the Euclid Collab oration, and also, with new forecasts produced by the CosmicFish
code, now interfaced directly with the two Einstein–Boltzmann solvers CAMB
and CLASS
. Moreover, to establish the validity of the Gaussian approximation, we show that the Fisher matrix marginal error contours coincide with the credible regions obtained when running Monte Carlo Markov chains with MontePython while using the exact same mock likelihoods.Keywords
cosmology: theory / surveys / cosmology: observations / large-scale structure of Universe / cosmological parameters
Astronomy & Astrophysics
Volume 682, Article Number A90, Number of pages 33
2024 February