The effect of imperfect corrections of PSF anisotropy on cosmic shear measurements

Current measurements of the weak lensing signal induced by large scale structure provide useful constraints on a range of cosmological parameters. However, the ultimate succes of this technique depends on the accuracy with which one can correct for the effect of the Point Spread Function (PSF). In this paper we examine the accuracy of the PSF anisotropy correction using images of fields with a large number of stars. The ellipticity correlation function of the residuals is studied to quantify the effect of imperfect corrections for PSF anisotropy on cosmic shear studies. These imperfections occur on the chip scale and consequently the systematic signal decreases rapidly with increasing angular scale. Separation of the signal into ``E'' (curl-free) and ``B'' (curl) components can help to identify the presence of residual systematics, but in general, the amplitude of the ``B''-mode is different from that of the ``E''-mode. The study of fields with many stars can be beneficial in finding a proper description of the variation of PSF anisotropy, and consequently help to significantly improve the accuracy with which the cosmic shear signal can be measured. We show that with such an approach it is feasible that the accuracy of future cosmic shear studies is limited by the statistical noise introduced by the intrinsic shapes of the sources. In particular, the prospects for accurate measurements of the cosmic shear signal on scales larger than ~10 arcminutes are excellent.Comment: submitted to MNRAS, 8 page

Non-Gaussian Foreground Residuals of the WMAP First Year Maps

We investigate the effect of foreground residuals in the WMAP data (Bennet et al. 2004) by adding foreground contamination to Gaussian ensembles of CMB signal and noise maps. We evaluate a set of non-Gaussian estimators on the contaminated ensembles to determine with what accuracy any residual in the data can be constrained using higher order statistics. We apply the estimators to the raw and cleaned Q, V, and W band first year maps. The foreground subtraction method applied to clean the data in Bennet et al. (2004a) appears to have induced a correlation between the power spectra and normalized bispectra of the maps which is absent in Gaussian simulations. It also appears to increase the correlation between the dl=1 inter-l bispectrum of the cleaned maps and the foreground templates. In a number of cases the significance of the effect is above the 98% confidence level.Comment: 9 pages, 4 figure