The Spectrum of Mass Fluctuations as Derived from the Weak Lensing of FIRST Radio Sources

Astronomy and Astrophysics – Astronomy

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Scientific paper

Large-scale mass inhomogeneities in the Universe induce correlated distortions in the shapes of background sources via weak gravitational lensing. This effect is on the verge of detectability on scales of 10 arcmin in several recent optical surveys. In most such surveys, however, the mean background galaxy redshifts are much less than 1, limiting the pathlength over which the gravitational lensing signal can accumulate. Furthermore, the angular scales probed are in the nonlinear regime of structure formation, and are thus less cleanly mapped back to the primordial mass fluctuation spectrum. Here, we report on an effort to use the FIRST survey to measure the weak-lensing signal from a large (400,000 member) population of distant radio sources. The mean redshift of FIRST sources is z 1, making them the largest sample of high-redshift objects available. Furthermore, we probe the correlation function of shape distortions on scales of 30 arcmin to 3 degrees, well within the linear growth regime. We calculate the correlation function of the radio source ellipticities and compare it to our theoretical predictions for a variety of cosmologies and assumptions about the radio source redshift distribution. We examine in detail several important systematic effects including the change of the shape of the VLA synthesized beam as a function of declination and the hour-angle of the observation, and the effect of correlated noise in VLA images on the correlation signal. We find the latter effect is from 1 to 2 orders of magnitude smaller than the expected signal, and develop a correction procedure for the former. We present the corrected ellipticity correlation function, discuss its implications for large-scale structure formation, and explore prospects for future improvements in our analysis. This work is supported by grants from the National Geographic Society, the NSF, NASA, and Sun Microsystems.

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