Euclid Mission: Scientific Forecasts Using the CLOE Pipeline

This study presents the first scientific forecasts using CLOE (Cosmology Likelihood for Observables in Euclid), a dedicated Euclid cosmological pipeline. The forecasts are based on advanced Bayesian inference techniques applied to synthetic Euclid-like data, sampling the posterior distribution of cosmological and nuisance parameters across a variety of cosmological models and Euclid primary probes: cosmic shear, angular photometric galaxy clustering, galaxy-galaxy lensing, and spectroscopic galaxy clustering. The results validate the capability of CLOE to produce reliable cosmological forecasts, showcasing Euclid's potential to achieve a figure of merit for the dark energy parameters exceeding 400 when combining all primary probes. The authors also emphasize the importance of addressing computational challenges, proposing further exploration of innovative data science techniques to efficiently navigate the Euclid high-dimensional parameter space in upcoming cosmological data releases. This work demonstrates the readiness of the Euclid mission to provide unprecedented constraints on the nature of dark matter and dark energy.

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