We present measurements of the cosmic shear correlation in the shapes of galaxies in the Suprime-Cam 2.1 deg ^ { 2 } R _ { c } -band imaging data .
As an estimator of the shear correlation originated from the gravitational lensing , we adopt the aperture mass variance , which most naturally decomposes the correlation signal into E and B ( non-gravitational lensing ) modes .
We detect a non-zero E mode variance on scales between \theta _ { ap } = 2 \arcmin and 40′ .
We also detect a small but non-zero B mode variance on scales larger than \theta _ { ap } > 5 \arcmin .
We compare the measured E mode variance to the model predictions in CDM cosmologies using maximum likelihood analysis .
A four-dimensional space is explored , which examines \sigma _ { 8 } , \Omega _ { m } , \Gamma ( the shape parameter of the CDM power spectrum ) and \bar { z } _ { s } ( a mean redshift of galaxies ) .
We include three possible sources of error : statistical noise , the cosmic variance estimated using numerical experiments , and a residual systematic effect estimated from the B mode variance .
We derive joint constraints on two parameters by marginalizing over the two remaining parameters .
We obtain an upper limit of \Gamma < 0.5 for \bar { z } _ { s } > 0.9 ( 68 % confidence ) .
For a prior \Gamma \in [ 0.1 , 0.4 ] and \bar { z } _ { s } \in [ 0.6 , 1.4 ] , we find \sigma _ { 8 } = ( 0.50 _ { -0.16 } ^ { +0.35 } ) \Omega _ { m } ^ { -0.37 } for \Omega _ { m } + \Omega _ { \Lambda } = 1 and \sigma _ { 8 } = ( 0.51 _ { -0.16 } ^ { +0.29 } ) \Omega _ { m } ^ { -0.34 } for \Omega _ { \Lambda } = 0 ( 95 % confidence ) .
If we take the currently popular \Lambda CDM model ( \Omega _ { m } = 0.3 , \Omega _ { \lambda } = 0.7 , \Gamma = 0.21 ) , we obtain a one-dimensional confidence interval on \sigma _ { 8 } for the 95.4 % level , 0.62 < \sigma _ { 8 } < 1.32 for \bar { z } _ { s } \in [ 0.6 , 1.4 ] .
Information on the redshift distribution of galaxies is key to obtaining a correct cosmological constraint .
An independent constraint on \Gamma from other observations is useful to tighten the constraint .