arXiv · 1801.08331
Cosmology in the era of Euclid and the Square Kilometre Array
Abstract
Theoretical uncertainties on non-linear scales are among the main obstacles to exploit the sensitivity of forthcoming galaxy and hydrogen surveys like Euclid or the Square Kilometre Array (SKA). Here, we devise a new method to model the theoretical error that goes beyond the usual cut-off on small scales. The advantage of this more efficient implementation of the non-linear uncertainties is tested through a Markov-Chain-Monte-Carlo (MCMC) forecast of the sensitivity of Euclid and SKA to the parameters of the standard $Λ$CDM model, including massive neutrinos with total mass $M_ν$, and to 3 extended scenarios, including 1) additional relativistic degrees of freedom ($Λ$CDM + $M_ν$ + $N_\mathrm{eff}$), 2) a deviation from the cosmological constant ($Λ$CDM + $M_ν$ + $w_0$), and 3) a time-varying dark energy equation of state parameter ($Λ$CDM + $M_ν$ + $\left(w_0,w_a \right)$). We compare the sensitivity of 14 different combinations of cosmological probes and experimental configurations. For Euclid combined with Planck, assuming a plain cosmological constant, our method gives robust predictions for a high sensitivity to the primordial spectral index $n_{\rm s}$ ($σ(n_s)=0.00085$), the Hubble constant $H_0$ ($σ(H_0)=0.141 \, {\rm km/s/Mpc}$), the total neutrino mass $M_ν$ ($σ(M_ν)=0.020 \, {\rm eV}$). Assuming dynamical dark energy we get $σ(M_ν)=0.030 \, {\rm eV}$ for the mass and $(σ(w_0), σ(w_a)) = (0.0214, 0.071)$ for the equation of state parameters. The predicted sensitivity to $M_ν$ is mostly stable against the extensions of the cosmological model considered here. Interestingly, a significant improvement of the constraints on the extended model parameters is also obtained when combining Euclid with a low redshift HI intensity mapping survey by SKA1, demonstrating the importance of the synergy of Euclid and SKA.
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Tim Sprenger, Maria Archidiacono, Thejs Brinckmann, Sébastien Clesse, Julien Lesgourgues. 2019-02-05. Cosmology in the era of Euclid and the Square Kilometre Array. https://doi.org/10.1088/1475-7516%2F2019%2F02%2F047
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