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Euclid: Validation of the MontePython forecasting tools

S. Casas (1)J. Lesgourgues (1)N. Sch\"oneberg (2) ...+635 France)
Mar 2023
The Euclid mission of the European Space Agency will perform a survey of weaklensing cosmic shear and galaxy clustering in order to constrain cosmologicalmodels and fundamental physics. We expand and adjust the mock Euclidlikelihoods of the MontePython software in order to match the exact recipesused in previous Euclid Fisher matrix forecasts for several probes: weaklensing cosmic shear, photometric galaxy clustering, the cross-correlationbetween the latter observables, and spectroscopic galaxy clustering. We alsoestablish which precision settings are required when running theEinstein-Boltzmann solvers CLASS and CAMB in the context of Euclid. For theminimal cosmological model, extended to include dynamical dark energy, weperform Fisher matrix forecasts based directly on a numerical evaluation ofsecond derivatives of the likelihood with respect to model parameters. Wecompare our results with those of other forecasting methods and tools. We showthat such MontePython forecasts agree very well with previous Fisher forecastspublished by the Euclid Collaboration, and also, with new forecasts produced bythe CosmicFish code, now interfaced directly with the two Einstein-Boltzmannsolvers CAMB and CLASS. Moreover, to establish the validity of the Gaussianapproximation, we show that the Fisher matrix marginal error contours coincidewith the credible regions obtained when running Monte Carlo Markov Chains withMontePython while using the exact same mock likelihoods. The new Euclidforecast pipelines presented here are ready for use with additionalcosmological parameters, in order to explore extended cosmological models.