期刊
ASTROPHYSICAL JOURNAL
卷 701, 期 2, 页码 945-954出版社
IOP PUBLISHING LTD
DOI: 10.1088/0004-637X/701/2/945
关键词
cosmology: theory; gravitational lensing; large-scale structure of universe; methods: numerical
资金
- World Premier International Research Center Initiative (WPI Initiative)
- Scientific Research on Priority Areas No. 467, Probing the Dark Energy through an Extremely Wide and Deep Survey with Subaru Telescope
- Nagoya University Global COE Program
- Ministry of Education, Culture, Sports, Science and Technology of Japan
- Grants-in-Aid for Scientific Research [21540263] Funding Source: KAKEN
We study the lensing convergence power spectrum and its covariance for a standard Lambda CDM cosmology. We run 400 cosmological N-body simulations and use the outputs to perform a total of 1000 independent ray-tracing simulations. We compare the simulation results with analytic model predictions. The semianalytic model based on Smith et al. fitting formula underestimates the convergence power by similar to 30% at arcmin angular scales. For the convergence power spectrum covariance, the halo model reproduces the simulation results remarkably well over a wide range of angular scales and source redshifts. The dominant contribution at small angular scales comes from the sample variance due to the number fluctuations of halos in a finite survey volume. The signal-to-noise ratio for the convergence power spectrum is degraded by the non-Gaussian covariances by up to a factor of 5 for a weak lensing survey to z(s) similar to 1. The probability distribution of the convergence power spectrum estimators, among the realizations, is well approximated by chi(2) distribution with broadened variance given by the non-Gaussian covariance, but has a larger positive tail. The skewness and kurtosis have non-negligible values especially for a shallow survey. We argue that a prior knowledge on the full distribution may be needed to obtain an unbiased estimate on the ensemble-averaged band power at each angular scale from a finite volume survey.
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