Abstract
Context. The weak gravitational lensing distortion of distant galaxy images (defined as sources) probes the projected large-scale matter distribution in the Universe. The availability of redshift information in galaxy surveys also allows us to recover the radial matter distribution to a certain degree. Aims: To improve quality in the mass mapping, we combine the lensing information with the spatial clustering of a population of galaxies (defined as tracers) that trace the matter density with a known galaxy bias. Methods: We construct a minimum-variance estimator for the 3D matter density that incorporates the angular distribution of galaxy tracers, which are coarsely binned in redshift. Merely the second-order bias of the tracers has to be known, which can in principle be self-consistently constrained in the data by lensing techniques. This synergy introduces a new noise component because of the stochasticity in the matter-tracer density relation. We give a description of the stochasticity noise in the Gaussian regime, and we investigate the estimator characteristics analytically. We apply the estimator to a mock survey based on the Millennium Simulation. Results: The estimator linearly mixes the individual lensing mass and tracer number density maps into a combined smoothed mass map. The weighting in the mix depends on the signal-to-noise ratio (S/N) of the individual maps and the correlation, R, between the matter and galaxy density. The weight of the tracers can be reduced by hand. For moderate mixing, the S/N in the mass map improves by a factor ~2-3 for R ≳ 0.4. Importantly, the systematic offset between a true and apparent mass peak distance (defined as z-shift bias) in a lensing-only map is eliminated, even for weak correlations of R ~ 0.4. Conclusions: If the second-order bias of tracer galaxies can be determined, the synergy technique potentially provides an option to improve redshift accuracy and completeness of the lensing 3D mass map. Herein, the aim is to visualise the spatial distribution of cluster-sized mass peaks. Our noise description of the estimator is accurate in the linear, Gaussian regime. However, its performance on sub-degree scales depends on the details in the galaxy bias mechanism and, hence, on the choice of the tracer population. Nonetheless, we expect that the mapping technique yields qualitatively reasonable results even for arcmin smoothing scales, as observed when this technique is applied to the mock survey with two different tracer populations.
Author
Simon, Patrick
Journal
Astronomy & Astrophysics
Paper Publication Date
December 2013
Paper Type
Astrostatistics