No Arabic abstract
We explore the impact of an update to the typical approximation for the shape noise term in the analytic covariance matrix for cosmic shear experiments that assumes the absence of survey boundary and mask effects. We present an exact expression for the number of galaxy pairs in this term based on the the survey mask, which leads to more than a factor of three increase in the shape noise on the largest measured scales for the Kilo-Degree Survey (KIDS-450) real-space cosmic shear data. We compare the result of this analytic expression to several alternative methods for measuring the shape noise from the data and find excellent agreement. This update to the covariance resolves any internal model tension evidenced by the previously large cosmological best-fit $chi^2$ for the KiDS-450 cosmic shear data. The best-fit $chi^2$ is reduced from 161 to 121 for 118 degrees of freedom. We also apply a correction to how the multiplicative shear calibration uncertainty is included in the covariance. This change, along with a previously known update to the reported effective angular values of the data vector, jointly shift the inferred amplitude of the correlation function to higher values. We find that this improves agreement of the KiDS-450 cosmic shear results with Dark Energy Survey Year 1 and Planck results.
Exploiting the full statistical power of future cosmic shear surveys will necessitate improvements to the accuracy with which the gravitational lensing signal is measured. We present a framework for calibrating shear with image simulations that demonstrates the importance of including realistic correlations between galaxy morphology, size and more importantly, photometric redshifts. This realism is essential so that selection and shape measurement biases can be calibrated accurately for a tomographic cosmic shear analysis. We emulate Kilo-Degree Survey (KiDS) observations of the COSMOS field using morphological information from {it Hubble} Space Telescope imaging, faithfully reproducing the measured galaxy properties from KiDS observations of the same field. We calibrate our shear measurements from lensfit, and find through a range of sensitivity tests that lensfit is robust and unbiased within the allowed 2 per cent tolerance of our study. Our results show that the calibration has to be performed by selecting the tomographic samples in the simulations, consistent with the actual cosmic shear analysis, because the joint distributions of galaxy properties are found to vary with redshift. Ignoring this redshift variation could result in misestimating the shear bias by an amount that exceeds the allowed tolerance. To improve the calibration for future cosmic shear analyses, it will be essential to also correctly account for the measurement of photometric redshifts, which requires simulating multi-band observations.
Recent cosmic shear studies have reported discrepancies of up to $1sigma$ on the parameter ${S_{8}=sigma_{8}sqrt{Omega_{rm m}/0.3}}$ between the analysis of shear power spectra and two-point correlation functions, derived from the same shear catalogs. It is not a priori clear whether the measured discrepancies are consistent with statistical fluctuations. In this paper, we investigate this issue in the context of the forthcoming analyses from the third year data of the Dark Energy Survey (DES-Y3). We analyze DES-Y3 mock catalogs from Gaussian simulations with a fast and accurate importance sampling pipeline. We show that the methodology for determining matching scale cuts in harmonic and real space is the key factor that contributes to the scatter between constraints derived from the two statistics. We compare the published scales cuts of the KiDS, Subaru-HSC and DES surveys, and find that the correlation coefficients of posterior means range from over 80% for our proposed cuts, down to 10% for cuts used in the literature. We then study the interaction between scale cuts and systematic uncertainties arising from multiple sources: non-linear power spectrum, baryonic feedback, intrinsic alignments, uncertainties in the point-spread function, and redshift distributions. We find that, given DES-Y3 characteristics and proposed cuts, these uncertainties affect the two statistics similarly; the differential biases are below a third of the statistical uncertainty, with the largest biases arising from intrinsic alignment and baryonic feedback. While this work is aimed at DES-Y3, the tools developed can be applied to Stage-IV surveys where statistical errors will be much smaller.
We carry out a multi-probe self-consistency test of the flat $Lambda$CDM model with the aim of exploring potential causes of the reported tensions between high- and low-redshift cosmological observations. We divide the model into two theory regimes determined by the smooth background (geometry) and the evolution of matter density fluctuations (growth), each governed by an independent set of Lambda Cold Dark Matter ($Lambda$CDM) cosmological parameters. This extended model is constrained by a combination of weak gravitational lensing measurements from the Kilo-Degree Survey, galaxy clustering signatures extracted from Sloan Digital Sky Survey campaigns and the Six-Degree Field Galaxy Survey, and the angular baryon acoustic scale and the primordial scalar fluctuation power spectrum measured in $textit{Planck}$ cosmic microwave background (CMB) data. We find strong consistency between the geometry and growth parameters, and with the posterior of standard $Lambda$CDM analysis. Tension in the amplitude of matter density fluctuations as measured by the parameter $S_8$ persists at around 3$sigma$, with a $1.5,%$ constraint of $S_8 = 0.776_{-0.008}^{+0.016}$ for the combined probes. We also observe a less significant preference (at least $2sigma$) for higher values of the Hubble constant, $H_0 = 70.5^{+0.7}_{-1.5},{rm km, s^{-1} Mpc^{-1}}$, as well as for lower values of the total matter density parameter $Omega_{rm{m}} = 0.289^{+0.007}_{-0.005}$ compared to the full $textit{Planck}$ analysis. Including the subset of the CMB information in the probe combination enhances these differences rather than alleviate them, which we link to the discrepancy between low and high multipoles in $textit{Planck}$ data.
With the advent of large-scale weak lensing surveys there is a need to understand how realistic, scale-dependent systematics bias cosmic shear and dark energy measurements, and how they can be removed. Here we describe how spatial variations in the amplitude and orientation of realistic image distortions convolve with the measured shear field, mixing the even-parity convergence and odd-parity modes, and bias the shear power spectrum. Many of these biases can be removed by calibration to external data, the survey itself, or by modelling in simulations. The uncertainty in the calibration must be marginalised over and we calculate how this propagates into parameter estimation, degrading the dark energy Figure-of-Merit. We find that noise-like biases affect dark energy measurements the most, while spikes in the bias power have the least impact, reflecting their correlation with the effect of cosmological parameters. We argue that in order to remove systematic biases in cosmic shear surveys and maintain statistical power effort should be put into improving the accuracy of the bias calibration rather than minimising the size of the bias. In general, this appears to be a weaker condition for bias removal. We also investigate how to minimise the size of the calibration set for a fixed reduction in the Figure-of-Merit. These results can be used to model the effect of biases and calibration on a cosmic shear survey accurately, assess their impact on the measurement of modified gravity and dark energy models, and to optimise surveys and calibration requirements.