List of Tables

Table 1:
Strength of evidence disfavoring the three benchmark models against a cosmological constant model, using an indicative accuracy on w = − 1 from present data, σ ∼ 0.1.
Table 2:
Required accuracy for future surveys in order to disfavor the three benchmark models against w = − 1 for two different strengths of evidence.
Table 3:
Expected galaxy number densities in units of (h∕Mpc )3 for Euclid survey. Let us notice that the galaxy number densities n(z) depend on the fiducial cosmology adopted in the computation of the survey volume, needed for the conversion from the galaxy numbers dN ∕dz to n(z).
Table 4:
1σ marginalized errors for the bias and the growth rates in each redshift bin.
Table 5:
Numerical values for 1σ constraints on parameters in Figure 16View Image and figures of merit. Here we have fixed Ω k to its fiducial value, Ω = 0 k.
Table 6:
Numerical values for 1σ constraints on parameters γ and w (assumed constant), relative to the red ellipses in Figures 17View Image, 18View Image and figures of merit. Here we have marginalized over Ωk.
Table 7:
Numerical values for marginalized 1σ constraints on cosmological parameters using constant γ and w.
Table 8:
1σ marginalized errors for parameters γ and w expressed through γ and η parameterizations. Columns γ ,w 0,marg1 0,marg1 refer to marginalization over γ ,w 1 1 (Figure 17View Image) while columns γ0,marg2,w0,marg2 refer to marginalization over η,w1 (Figure 18View Image).
Table 9:
Numerical values for 1σ constraints on parameters in right panel of Figure 16View Image and figures of merit.
Table 10:
Numerical values for 1σ constraints on parameters in Figure 19View Image and figures of merit.
Table 11:
1σ marginalized errors for the parameters w0 and w1, obtained with three different methods (reference case, see Figure 20View Image).
Table 12:
Values used in our computation. The values of the fiducial model (WMAP7, on the left) and the survey parameters (on the right).
Table 13:
1-σ errors for the set Θ ≡ {β2, α,Ωc,h, Ωb,nsσ8,log(A )} of cosmological parameters, combining CMB + P (k) (left column) and CMB + P (k) + WL (right column).
Table 14:
1-σ errors for β2, for CMB, P (k), WL and CMB + P(k ) + WL. For each line, only the parameter in the left column has been fixed to the reference value. The first line corresponds to the case in which we have marginalized over all parameters. Table reproduced by permission from [42], copyright by APS.
Table 15:
R, la, Ωbh2 and ns estimated from Planck simulated data. Table reproduced by permission from [676], copyright by APS.
Table 16:
Covariance matrix for (R, la,Ωbh2, ns) from Planck. Table reproduced by permission from [676], copyright by APS.
Table 17:
Fisher matrix for (w0, wa, ΩDE, Ωk, ωm, ωb, nS) derived from the covariance matrix for (R,l ,Ω h2,n ) a b s from Planck. Table reproduced by permission from [676], copyright by APS.
Table 18:
σ (M ν) and σ(Ne ff) marginalized errors from LSS+CMB
Table 19:
Instrument specifics for the Planck satellite with 30 months of integration.
Table 20:
Cosmological parameters
Table 21:
Specifications of the surveys used in the Euclid forecasts given in Table 22. The redshift distributions of the different galaxy samples are as in Section 1.8.2 (see also [393]).
Table 22:
Forecast 1σ errors for the nonlinearity parameter fNL based on two-point statistics (power spectra) of the Euclid redshift and weak-lensing surveys. Results are obtained using the Fisher-matrix formalism and marginalizing over eight cosmological parameters (Ω Λ, Ωm, Ωb, h, ns, σ8, w0, wa) plus a large number of nuisance parameters to account for galaxy biasing, nonlinear redshift-space distortions and shot noise (see [393] for details). Results within parentheses include the forecast priors for the cosmological parameters from the power spectrum of CMB temperature anisotropies measured with the Planck satellite (note that no prior is assumed on fNL). The label “Galaxy clustering” refers to the anisotropic power spectrum P (k∥,k⊥) for spectroscopic data and to the angular power spectrum C ℓ for photometric data. The combined analysis of clustering and lensing data is based on angular power spectra and includes all possible cross-correlations between different redshift bins and probes. nonlinear power spectra are computed using the halo model. This introduces possible inaccuracies in the forecasts for weak lensing data in the equilateral and orthogonal shapes (see main text for details).
Table 23:
Forecast 1σ errors for a scale-dependent local model of primordial non-Gaussianity [393]. Details of the forecasts are as in the previous Table 22.
Table 24:
Bianchi models containing FRW limit and their structure constants.