Optimal surveys for weak-lensing tomography

131Citations
Citations of this article
34Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Weak-lensing surveys provide a powerful probe of dark energy through the measurement of the mass distribution of the local Universe. A number of ground-based and space-based surveys are being planned for this purpose. Here, we study the optimal strategy for these future surveys using the joint constraints on the equation-of-state parameter wn and its evolution wa as a figure of merit by considering power spectrum tomography. For this purpose, we first consider an 'ideal' survey which is both wide and deep and exempt from systematics. We find that such a survey has great potential for dark energy studies, reaching 1σ precisions of 1 and 10 per cent on the two parameters, respectively. We then study the relative impact of various limitations by degrading this ideal survey. In particular, we consider the effect of sky coverage, survey depth, shape measurement systematics, photometric redshift systematics and uncertainties in the non-linear power spectrum predictions. We find that, for a given observing time, it is always advantageous to choose a wide rather than a deep survey geometry. We also find that the dark energy constraints from power spectrum tomography are robust to photometric redshift errors and catastrophic failures, if a spectroscopic calibration sample of 104-105 galaxies are available. The impact of these systematics is small compared to the limitations that come from potential uncertainties in the power spectrum, due to shear measurement and theoretical errors. To help the planning of future surveys, we summarize our results with comprehensive scaling relations which avoid the need for full Fisher matrix calculations. © 2007 RAS.

Cite

CITATION STYLE

APA

Amara, A., & Réfrégier, A. (2007). Optimal surveys for weak-lensing tomography. Monthly Notices of the Royal Astronomical Society, 381(3), 1018–1026. https://doi.org/10.1111/j.1365-2966.2007.12271.x

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free