Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

physics and astronomy

Measuring lensing ratios with future cosmological surveys

Physical Review D, Volume 102, No. 2, Article 023502, Year 2020

The ratio between the CMB lensing/galaxy counts and the galaxy shear/galaxy counts cross-correlations combines the information from different cosmological probes to infer cosmographic measurements that are less dependent on astrophysical uncertainties and can constrain the geometry of the Universe. We discuss the future perspectives for the measurement of this lensing ratio as previously introduced, i.e., with the use of the Limber and flat-sky approximations and neglecting all the effects on the galaxy survey from observing on the past light cone. We then show how the cosmological information in this estimator is affected by the Limber approximation and by the inclusion of the redshift space distortions (RSD) and lensing magnification contributions to the galaxy number counts. We find that the lensing magnification contribution induces a multipole dependence of the lensing ratio that we show to be detectable at a statistical significant level combining post-Planck CMB surveys and a Euclid-like experiment. We propose an improved estimator which takes into account this angular scale dependence. Using this extended formalism, we present forecasts for upcoming and future cosmological surveys, and we show at which extent the lensing ratio information can improve the CMB constraints on cosmological parameters. We get that for extended cosmological models where the neutrino mass, the spatial curvature and the dark energy equation of state are allowed to vary, the constraints from Planck on these parameters and on H0 can be reduced by ∼40% with the inclusion of a single lensing ratio and by ∼60%-70% adding the joint measurement of 9 lensing ratios with a Euclid-like survey. We also find that neglecting the contribution from lensing magnification can induce a bias on the derived cosmological parameters in a combined analysis.
Statistics
Citations: 4
Authors: 4
Affiliations: 6
Identifiers
Study Design
Cross Sectional Study
Study Approach
Quantitative