Accurate Modeling of Weak Lensing with the sGL Method

TL;DR

The paper improves the stochastic sGL method for modeling weak lensing by incorporating realistic structures, enabling rapid computation of lensing PDFs, and demonstrating its application to cosmological parameter studies and systematic bias analysis.

Contribution

It extends the sGL method with realistic halo and filament modeling, and provides a fast computational tool for weak lensing analysis in inhomogeneous universes.

Findings

sGL method accurately reproduces Millennium Simulation results.

The turboGL code computes lensing PDFs in seconds.

Selection effects can significantly alter observed lensing PDFs.

Abstract

We revise and extend the stochastic approach to cumulative weak lensing (hereafter the sGL method) first introduced in Ref. [1]. Here we include a realistic halo mass function and density profiles to model the distribution of mass between and within galaxies, galaxy groups and galaxy clusters. We also introduce a modeling of the filamentary large-scale structures and a method to embed halos into these structures. We show that the sGL method naturally reproduces the weak lensing results for the Millennium Simulation. The strength of the sGL method is that a numerical code based on it can compute the lensing probability distribution function for a given inhomogeneous model universe in a few seconds. This makes it a useful tool to study how lensing depends on cosmological parameters and its impact on observations. The method can also be used to simulate the effect of a wide array of systematic biases on the observable PDF. As an example we show how simple selection effects may reduce the variance of observed PDF, which could possibly mask opposite effects from very large scale structures. We also show how a JDEM-like survey could constrain the lensing PDF relative to a given cosmological model. The updated turboGL code is available at turboGL.org.