Cosmology without cosmic variance
arXiv:1104.3862 · doi:10.1111/j.1365-2966.2011.19249.x
Abstract
We examine the improvements in constraints on the linear growth factor G and its derivative f=d ln G / dln a that are available from the combination of a large-scale galaxy redshift survey with a weak gravitational lensing survey of background sources. In the linear perturbation theory limit, the bias-modulation method of McDonald & Seljak allows one to distinguish the real-space galaxy clustering from the peculiar velocity signal in each Fourier mode. The ratio of lensing signal to galaxy clustering in transverse modes yields the bias factor b of each galaxy subset (as per Pen 2004), hence calibrating the conversion from galaxy real-space density to matter density in every mode. In combination these techniques permit measure of the growth rate f in each Fourier mode. This yields a measure of the growth rate free of sample variance, i.e. the uncertainty in f can be reduced without bound by increasing the number of redshifts within a finite volume. In practice, the gain from the absence of sample variance is bounded by the limited range of bias modulation among dark-matter halos. Nonetheless, the addition of background weak lensing data to a redshift survey increases information on G and f by an amount equivalent to a 10-fold increase in the volume of a standard redshift-space distortion measurement---if the lensing signal can be measured to sub-percent accuracy. This argues that a combined lensing and redshift survey over a common low-redshift volume is a more powerful test of general relativity than an isolated redshift survey over larger volume at high redshift. An example case is that a survey of ~10^6 redshifts over half the sky in the redshift range can determine the growth exponent γfor the model to an accuracy of , using only modes with k<0.1h/Mpc, but only if a weak lensing survey is conducted in concert. [Abridged]
9 pages, 3 figures, accepted by MNRAS, minor changes to match the accepted version
References in corpus (3)
Cited by in corpus (39)
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