Cosmological parameter estimation using Very Small Array data out to l=1500

Abstract

We estimate cosmological parameters using data obtained by the Very Small Array (VSA) in its extended configuration, in conjunction with a variety of other CMB data and external priors. Within the flat $Λ$CDM model, we find that the inclusion of high resolution data from the VSA modifies the limits on the cosmological parameters as compared to those suggested by WMAP alone, while still remaining compatible with their estimates. We find that $Ω_{\rm b}h^2=0.0234^{+0.0012}_{-0.0014}$, $Ω_{\rm dm}h^2=0.111^{+0.014}_{-0.016}$, $h=0.73^{+0.09}_{-0.05}$, $n_{\rm S}=0.97^{+0.06}_{-0.03}$, $10^{10}A_{\rm S}=23^{+7}_{-3}$ and $τ=0.14^{+0.14}_{-0.07}$ for WMAP and VSA when no external prior is included.On extending the model to include a running spectral index of density fluctuations, we find that the inclusion of VSA data leads to a negative running at a level of more than 95% confidence ($n_{\rm run}=-0.069\pm 0.032$), something which is not significantly changed by the inclusion of a stringent prior on the Hubble constant. Inclusion of prior information from the 2dF galaxy redshift survey reduces the significance of the result by constraining the value of $Ω_{\rm m}$. We discuss the veracity of this result in the context of various systematic effects and also a broken spectral index model. We also constrain the fraction of neutrinos and find that $f_ν< 0.087$ at 95% confidence which corresponds to $m_ν<0.32{\rm eV}$ when all neutrino masses are the equal. Finally, we consider the global best fit within a general cosmological model with 12 parameters and find consistency with other analyses available in the literature. The evidence for $n_{\rm run}<0$ is only marginal within this model.

Figures (9)

• Figure 1: Marginalized distributions for the standard 6-parameter flat $\Lambda$CDM model with no external priors (that is, CMB alone) using COBE+VSA (solid-line), WMAP alone (dotted line) and WMAP+VSA (dashed line).
• Figure 2: Marginalized distributions for $n_{\rm S}$ and $n_{\rm run}$ in the flat $\Lambda$CDM model with a running spectral index. Line-styles are as in Fig. \ref{['fig:lcdm']}. The external priors adopted are: none (top row), HST (middle row), 2dF (bottom row).
• Figure 3: As for Fig. \ref{['fig:nsnrun']}, but for the parameters $\Omega_{\rm m}$ and $\Omega_\Lambda$.
• Figure 4: Marginalized distributions for $n_1$ and $n_2$ in the flat $\Lambda$CDM model with a broken power-law index. The line styles are as in Fig. \ref{['fig:lcdm']}. The left-hand column assumes the HST prior and the right-hand column assumed the 2dF prior.
• Figure 5: Marginalized distributions for $f_\nu$, $n_s$ and $n_{\rm run}$ in the extended flat $\Lambda$CDM model, using the 2dF external prior and COBE+VSA (solid-line), WMAP alone (dotted line) and WMAP+VSA (dashed line).