The covariance of cosmic shear correlation functions and cosmological parameter estimates using redshift information

Cosmological weak lensing by the large scale structure of the Universe, cosmic shear, is coming of age as a powerful probe of the parameters describing the cosmological model and matter power spectrum. It complements Cosmic Microwave Background studies, by breaking degeneracies and providing a cross-check. Furthermore, upcoming cosmic shear surveys with photometric redshift information will enable the evolution of dark matter to be studied, and even a crude separation of sources into redshift bins leads to improved constraints on parameters. An important measure of the cosmic shear signal are the shear correlation functions; these can be directly calculated from data, and compared with theoretical expectations for different cosmological models and matter power spectra. We present a Monte Carlo method to quickly simulate mock cosmic shear surveys. One application of this method is in the determination of the full covariance matrix for the correlation functions; this includes redshift binning and is applicable to arbitrary survey geometries. Terms arising from shot noise and cosmic variance (dominant on small and large scales respectively) are accounted for naturally. As an illustration of the use of such covariance matrices, we consider to what degree confidence regions on parameters are tightened when redshift binning is employed. The parameters considered are those commonly discussed in cosmic shear analyses - the matter density parameter Ωm ,d ark energy density parameter (classical cosmological constant) ΩΛ, power spectrum normalisation σ8 and shape parameter Γ .W e incorporate our covariance matrices into a likelihood treatment, and also use the Fisher formalism to explore a larger region of parameter space. Parameter uncertainties can be decreased by a factor of ∼4− 8( ∼5−10) with 2 (4) redshift bins.

[1]  William H. Press,et al.  Numerical recipes , 1990 .

[2]  Edward J. Wollack,et al.  First-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Preliminary Maps and Basic Results , 2003, astro-ph/0302207.

[3]  Cambridge,et al.  Detection of weak gravitational lensing by large-scale structure , 2000 .

[4]  Martin White,et al.  A New Algorithm for Computing Statistics of Weak Lensing by Large-Scale Structure , 1999 .

[5]  Optimal Weak-Lensing Skewness Measurements , 2003, astro-ph/0304559.

[6]  A. Hamilton,et al.  Reconstructing the primordial spectrum of fluctuations of the universe from the observed nonlinear clustering of galaxies , 1991 .

[7]  David W. Hogg,et al.  Deep Optical Galaxy Counts with the Keck Telescope , 1995, astro-ph/9506095.

[8]  A. Szalay,et al.  The statistics of peaks of Gaussian random fields , 1986 .

[9]  Peter Schneider,et al.  Separating cosmic shear from intrinsic galaxy alignments: Correlation function tomography , 2002 .

[10]  N. Kaiser Weak Lensing and Cosmology , 1996, astro-ph/9610120.

[11]  M. Bartelmann,et al.  Weak gravitational lensing , 2016, Scholarpedia.

[12]  Nicholas J. Higham,et al.  Stable iterations for the matrix square root , 1997, Numerical Algorithms.

[13]  P. Schneider,et al.  B-modes in cosmic shear from source redshift clustering , 2002 .

[14]  Max Tegmark,et al.  Karhunen-Loève Eigenvalue Problems in Cosmology: How Should We Tackle Large Data Sets? , 1996, astro-ph/9603021.

[15]  J. R. Bond,et al.  Cosmic confusion: degeneracies among cosmological parameters derived from measurements of microwave background anisotropies , 1998 .

[16]  Y. Mellier,et al.  Cosmic shear statistics and cosmology , 2001, astro-ph/0101511.

[17]  Bonn,et al.  Analysis of two-point statistics of cosmic shear - I. Estimators and covariances , 2002, astro-ph/0206182.

[18]  S. J. Dodds,et al.  Non-linear evolution of cosmological power spectra , 1996 .

[19]  The distortion of distant galaxy images by large-scale structure , 1991 .

[20]  Uros Seljak,et al.  Ray-tracing Simulations of Weak Lensing by Large-Scale Structure , 1999, astro-ph/9901191.

[21]  Wayne Hu,et al.  � 1999. The American Astronomical Society. All rights reserved. Printed in U.S.A. POWER SPECTRUM TOMOGRAPHY WITH WEAK LENSING , 1999 .

[22]  Y. Mellier,et al.  Astronomy & Astrophysics manuscript no. (will be inserted by hand later) Likelihood Analysis of Cosmic Shear on Simulated and VIRMOS-DESCART Data ⋆ , 2002 .

[23]  Peter Schneider,et al.  A NEW MEASURE FOR COSMIC SHEAR , 1998 .

[24]  D. Huterer,et al.  Weak lensing and dark energy , 2001, astro-ph/0106399.

[25]  Martin White,et al.  Power Spectra Estimation for Weak Lensing , 2000 .

[26]  Nick Kaiser,et al.  Weak gravitational lensing of distant galaxies , 1992 .

[27]  Max Tegmark,et al.  Weak Lensing: Prospects for Measuring Cosmological Parameters , 1998, astro-ph/9811168.

[28]  Analysis of two-point statistics of cosmic shear. II. Optimizing the survey geometry , 2003, astro-ph/0308119.

[29]  J. Miralda-Escudé The correlation function of galaxy ellipticities produced by gravitational lensing , 1991 .

[30]  David M. Wittman,et al.  Detection of weak gravitational lensing distortions of distant galaxies by cosmic dark matter at large scales , 2000, Nature.

[31]  TESTING COSMOLOGICAL MODELS BY GRAVITATIONAL LENSING. I. METHOD AND FIRST APPLICATIONS , 1996, astro-ph/9610096.