SIMULATIONS OF WIDE-FIELD WEAK-LENSING SURVEYS. II. COVARIANCE MATRIX OF REAL-SPACE CORRELATION FUNCTIONS

被引:48
作者
Sato, Masanori [1 ]
Takada, Masahiro [2 ]
Hamana, Takashi [3 ]
Matsubara, Takahiko [1 ,4 ]
机构
[1] Nagoya Univ, Dept Phys, Nagoya, Aichi 4648602, Japan
[2] Univ Tokyo, IPMU, Chiba 2778582, Japan
[3] Natl Astron Observ Japan, Tokyo 1818588, Japan
[4] Nagoya Univ, Kobayashi Maskawa Inst Origin Particles & Univers, Nagoya, Aichi 4648602, Japan
关键词
gravitational lensing: weak; large-scale structure of universe; methods: numerical; DARK ENERGY CONSTRAINTS; PROBE WMAP OBSERVATIONS; COSMIC SHEAR; POWER SPECTRUM; 2-POINT STATISTICS; COSMOLOGY; LIKELIHOOD; UNIVERSE; IMPACT; MATTER;
D O I
10.1088/0004-637X/734/2/76
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
Using 1000 ray-tracing simulations for a Lambda-dominated cold dark model in Sato et al., we study the covariance matrix of cosmic shear correlation functions, which is the standard statistics used in previous measurements. The shear correlation function of a particular separation angle is affected by Fourier modes over a wide range of multipoles, even beyond a survey area, which complicates the analysis of the covariance matrix. To overcome such obstacles we first construct Gaussian shear simulations from the 1000 realizations and then use the Gaussian simulations to disentangle the Gaussian covariance contribution to the covariance matrix we measured from the original simulations. We found that an analytical formula of Gaussian covariance overestimates the covariance amplitudes due to an effect of the finite survey area. Furthermore, the clean separation of the Gaussian covariance allows us to examine the non-Gaussian covariance contributions as a function of separation angles and source redshifts. For upcoming surveys with typical source redshifts of z(s) = 0.6 and 1.0, the non-Gaussian contribution to the diagonal covariance components at 1 arcmin scales is greater than the Gaussian contribution by a factor of 20 and 10, respectively. Predictions based on the halo model qualitatively well reproduce the simulation results, however show a sizable disagreement in the covariance amplitudes. By combining these simulation results we develop a fitting formula to the covariance matrix for a survey with arbitrary area coverage, taking into account effects of the finiteness of survey area on the Gaussian covariance.
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页数:12
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