Weaklensing statistics from the Coyote Universe
Abstract
Analysing future weaklensing data sets from KIDS, Dark Energy Survey (DES), LSST, Euclid and WFIRST requires precise predictions for the weaklensing measures. In this paper, we present a weaklensing prediction code based on the Coyote Universe emulator. The Coyote Universe emulator predicts the (nonlinear) power spectrum of density fluctuations (P_{δ}) to high accuracy for k∈[0.002; 3.4] h Mpc^{1} within the redshift interval z∈[0; 1]; outside this regime, we extend P_{δ} using a modified HALOFIT code.
This pipeline is used to calculate various secondorder cosmic shear statistics, e.g., shear power spectrum, shearshear correlation function, ring statistics and Complete Orthogonal Set of EBmode Integrals (COSEBIs), and we examine how the upper limit in k (and z), to which P_{δ} is known, impacts on these statistics. For example, we find that k_{max}∼ 8 h Mpc^{1} causes a bias in the shear power spectrum at ℓ∼ 4000 that is comparable to the statistical errors (intrinsic shape noise and cosmic variance) of a DESlike survey, whereas for LSSTlike errors k_{max}∼ 15 h Mpc^{1} is needed to limit the bias at ℓ∼ 4000.
For the most recently developed secondorder shear statistics, the COSEBIs, we find that nine modes can be calculated accurately knowing P_{δ} to k_{max}= 10 h Mpc^{1}. The COSEBIs allow for an EBmode decomposition using a shearshear correlation function measured over a finite range, thereby avoiding any EBmode mixing due to finite survey size. We perform a detailed study in a fivedimensional parameter space in order to examine whether all cosmological information is captured by these nine modes with the result that already 78 modes are sufficient.
 Publication:

Monthly Notices of the Royal Astronomical Society
 Pub Date:
 November 2011
 DOI:
 10.1111/j.13652966.2011.19502.x
 arXiv:
 arXiv:1012.2978
 Bibcode:
 2011MNRAS.418..536E
 Keywords:

 cosmology: theory;
 largescale structure of Universe;
 Astrophysics  Cosmology and Nongalactic Astrophysics
 EPrint:
 9 pages, submitted to MNRAS