Simultaneous measurement of cosmology and intrinsic alignments using joint cosmic shear and galaxy number density correlations

Abstract

Aims. Cosmic shear is a powerful method to constrain cosmology, provided that any systematic effects are under control. The intrinsic alignment of galaxies is expected to severely bias parameter estimates if not taken into account. We explore the potential of a joint analysis of tomographic galaxy ellipticity, galaxy number density, and ellipticity-number density cross-correlations to simultaneously constrain cosmology and self-calibrate unknown intrinsic alignment and galaxy bias contributions. Methods. We treat intrinsic alignments and galaxy biasing as free functions of scale and redshift and marginalise over the resulting parameter sets. Constraints on cosmology are calculated by combining the likelihoods from all two-point correlations between galaxy ellipticity and galaxy number density. The information required for these calculations is already available in a standard cosmic shear data set. We include contributions to these functions from cosmic shear, intrinsic alignments, galaxy clustering and magnification effects. Results. In a Fisher matrix analysis we compare our constraints with those from cosmic shear alone in the absence of intrinsic alignments. For a potential future large area survey, such as Euclid, the extra information from the additional correlation functions can make up for the additional free parameters in the intrinsic alignment and galaxy bias terms, depending on the flexibility in the models. For example, the dark energy task force figure of merit is recovered even when more than 100 free parameters are marginalised over. We find that the redshift quality requirements are similar to those calculated in the absence of intrinsic alignments.

Constraints on intrinsic alignment contamination of weak lensing surveys using the MegaZ-LRG sample

“…In the following we will refer to correlations of the form ξ(r p , Π, z) as the three-dimensional correlation function. We follow the notation of Joachimi & Bridle (2010) in denoting the different signals that contribute to the observations 8 . As a reminder, for each of the galaxy samples considered, the galaxy pairs used to compute ξ phot gI (r p ,Π,z m ) consist of one galaxy out of the density sample tracing the galaxy distribution and one galaxy out of the subsample with shape information used to trace the intrinsic shear.…”

“…In the weak lensing limit, the measured ellipticity of a galaxy image is the sum of the intrinsic ellipticity and the gravitational shear, while the number density is determined by an intrinsic term (whose two-point correlation is the usual galaxy clustering) plus modifications by lensing magnification effects. Hence, in terms of angular power spectra one can write (for details see Bernstein 2009;Joachimi & Bridle 2010) …”

“…made use of the characteristic redshift dependence of the GI signal to null it in a fully model-independent way, while King (2005), Bridle & King (2007), Bernstein (2009), and Joachimi & Bridle (2010) introduced very general parametrisations of the intrinsic alignment contributions containing parameters that are then marginalised over (see Kirk et al 2010, for an application to data). Both approaches feature a considerable loss of information, substantially weakening constraints on cosmological model parameters.…”

“…Since in contrast to these foregoing works we have to consider various contributing signals, we denote the observable by "galaxy position-shape" correlations and otherwise follow the indexing scheme of Joachimi & Bridle (2010). Throughout we will assume as our cosmological model a spatially flat ΛCDM universe with parameters Ω m = 0.25, Ω b = 0.05, σ 8 = 0.8, h = 0.7, and n s = 1.0.…”

Strongly coupled dark energy cosmologies: preservingΛCDM success and easing low scale problems – I. Linear theory revisited

“…Even assuming a linear expression w = w0 + w1(1 − a) for DE state parameter, however, errors on w0 and w1 can hardly be pushed below 10 % and some 10 %, respectively (e.g. Joachimi & Bridle 2010). Better hopes exist to detect violations of the standard relation between scale factor a and growth factor G time dependences.…”