Cosmology from Cosmic Shear with DES Science Verification Data

TL;DR

This work delivers the first cosmological constraints from the Dark Energy Survey using cosmic shear measured in 139 deg^2 of Science Verification data. By marginalizing over seven nuisance parameters (shear calibration, photometric redshift biases, and intrinsic alignments) and using a three-bin tomographic analysis with scale cuts to control non-linear/baryonic uncertainties, the authors obtain S_8 = $0.81 \pm 0.06$ and show consistency with both Planck and CFHTLenS. The analysis demonstrates robustness to the choice of data vector (xi_{±} vs C_\ell bandpowers), the shear catalog, and photo-z methods, while highlighting the impact of systematics on the error budget. With only a fraction of the full DES, the results already approach the precision of contemporaries and lay a solid groundwork for future DES data to probe dark energy, neutrino masses, and gravity on cosmological scales.

Abstract

We present the first constraints on cosmology from the Dark Energy Survey (DES), using weak lensing measurements from the preliminary Science Verification (SV) data. We use 139 square degrees of SV data, which is less than 3\% of the full DES survey area. Using cosmic shear 2-point measurements over three redshift bins we find $σ_8 (Ω_{\rm m}/0.3)^{0.5} = 0.81 \pm 0.06$ (68\% confidence), after marginalising over 7 systematics parameters and 3 other cosmological parameters. We examine the robustness of our results to the choice of data vector and systematics assumed, and find them to be stable. About $20$\% of our error bar comes from marginalising over shear and photometric redshift calibration uncertainties. The current state-of-the-art cosmic shear measurements from CFHTLenS are mildly discrepant with the cosmological constraints from Planck CMB data; our results are consistent with both datasets. Our uncertainties are $\sim$30\% larger than those from CFHTLenS when we carry out a comparable analysis of the two datasets, which we attribute largely to the lower number density of our shear catalogue. We investigate constraints on dark energy and find that, with this small fraction of the full survey, the DES SV constraints make negligible impact on the Planck constraints. The moderate disagreement between the CFHTLenS and Planck values of $σ_8 (Ω_{\rm m}/0.3)^{0.5}$ is present regardless of the value of $w$.

Figures (12)

• Figure 1: DES SV shear two-point correlation function $\xi_\pm$ measurements in each of the redshift bin pairings (from Be15). The 3 redshift bins ranges are $0.3<z<0.55$, $0.55<z<0.83$ and $0.83<z<1.3$, and each galaxy is assigned to a redshift bin according to the mean of its photometric redshift probability distribution (or excluded if this value is outside the above ranges). Alternating rows are $\xi_+$ and $\xi_-$, and the redshift bin combination is labelled in the upper right corner of each panel. The non-tomographic measurement is in the bottom left corner. The solid lines show the correlation functions computed for the best-fit Planck 2015 (TT + lowP) base $\Lambda$CDM cosmology, using halofitsmith03takahashi2012 to model the non-linear matter power spectrum. The blue dashed lines (mostly obscured by the black lines) and red dotted lines assume the same cosmology but model nonlinear scales using FrankenEmu heitmann2014 (extended at high $k$ using the 'CEp' presciption from harnois14) and a prescription based on the OWLS 'AGN' simulation schaye10 respectively. Points lying in grey regions are excluded from the analysis because they may be affected by either small-scale matter power spectrum uncertainty or large-scale additive shear bias, as explained in Section \ref{['subsec:scales']}.
• Figure 2: Constraints on the amplitude of fluctuations $\sigma_8$ and the matter density $\Omega_\mathrm m$ from DES SV cosmic shear (purple filled/outlined contours) compared with constraints from Planck (red filled contours) and CFHTLenS (orange filled, using the correlation functions and covariances presented in heymans13, and the 'original conservative scale cuts' described in Section \ref{['subsec:otherlensing']}). DES SV and CFHTLenS are marginalised over the same astrophysical systematics parameters and DES SV is additionally marginalised over uncertainties in photometric redshifts and shear calibration. Planck is marginalised over the 6 parameters of $\Lambda$CDM (the 5 we vary in our fiducial analysis plus $\tau$). The DES SV and CFHTLenS constraints are marginalised over wide flat priors on $n_s$, $\Omega_{\rm b}$ and $h$ (see text), assuming a flat universe. For each dataset, we show contours which encapsulate 68% and 95% of the probability, as is the case for subsequent contour plots.
• Figure 3: Graphical illustration of the 68% confidence limits on $S_8\equiv\sigma_8(\Omega_\mathrm m/0.3)^{0.5}$ values given in Table \ref{['table:om_s8']}, showing the robustness of our results (purple) and comparing with the CFHTLenS and Planck lensing results (orange) and Planck (red). The grey vertical band aligns with the fiducial constraints at the top of the plot. Note that Planck lensing in particular, and other non-DES lensing measurements optimally constrain a different quantity than shown above e.g. see the second and third columns of Table \ref{['table:om_s8']}.
• Figure 4: Comparison of constraints on $\sigma_8$ and $\Omega_\mathrm m$ for various choices of data vector: $\xi_{\pm}$ with no tomography or systematics (purple filled), $C^{ij}_{\ell}$ bandpowers (dashed red lines) and PolSpice-$C_{\ell}$ bandpowers (solid green lines) (both with no tomography or systematics). We do not show our fiducial constraints, or Planck, since we have not marginalised over systematics for the constraints shown here, so agreement is not necessary or meaningful (although Table \ref{['table:om_s8']} suggests there is reasonable agreement).
• Figure 5: The fractional bias on $\sigma_8$ due to ignoring an OWLS AGN baryon model (solid lines) compared to the statistical uncertainty on $\sigma_8$ (dashed lines) as a function of minimum scale used for $\xi_-$ ($\theta_{\rm{min}}^-$, x-axis) or $\xi_+$ ($\theta_{\rm{min}}^+$, colours). Whereas the statistical error is minimised by using small scales, the bias is significant for $\theta_{\rm{min}}^-<30'$ and $\theta_{\rm{min}}^+<3'$.