Improving three-dimensional mass mapping with weak gravitational lensing using galaxy clustering
Patrick Simon

TL;DR
This paper proposes a method to enhance 3D mass mapping with weak gravitational lensing by combining lensing data with galaxy clustering, reducing biases and improving signal-to-noise ratio.
Contribution
It introduces a combined estimator that leverages galaxy clustering and lensing, accounting for stochasticity and bias, to improve 3D mass maps in cosmological surveys.
Findings
S/N in mass map improves by 2-3 times for certain correlations
Eliminates systematic z-shift bias in lensing-only maps
Potential to improve redshift accuracy and completeness
Abstract
The weak gravitational lensing distortion of distant galaxy images (defined as sources) probes the projected large-scale matter distribution in the Universe. To improve quality in the 3D mass mapping using 3D-lensing, we combine the lensing information with the spatial clustering of a population of galaxies that trace the matter density with a known galaxy bias (defined as tracers). For our minimum variance estimator, merely all 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…
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