Weak Lensing Observables in the Halo Model

TL;DR

This paper explores the use of the halo model combined with stochastic gravitational lensing to efficiently predict lensing observables and their dependence on cosmology, aiding in cosmological parameter estimation.

Contribution

It provides exact integral expressions for lensing convergence statistics within the halo model and compares these predictions with Millennium Simulation results.

Findings

Exact integral formulas for lensing convergence mean and variance.

Incorporation of observational biases into lensing predictions.

Good agreement between model predictions and simulation data.

Abstract

The halo model (HM) describes the inhomogeneous universe as a collection of halos. The full nonlinear power spectrum of the universe is well approximated by the HM, whose prediction can be easily computed without lengthy numerical simulations. This makes the HM a useful tool in cosmology. Here we explore the lensing properties of the HM by use of the stochastic gravitational lensing (sGL) method. We obtain for the case of point sources exact and simple integral expressions for the expected value and variance of the lensing convergence, which encode detailed information about the internal halo properties. In particular a wide array of observational biases can be easily incorporated and the dependence of lensing on cosmology is properly taken into account. This simple setup should be useful for a quick calculation of the power spectrum and the related lensing observables, which can play an important role in the extraction of cosmological parameters from, e.g., SNe observations. Finally, we discuss the probability distribution function of the HM which encodes more information than the first two moments and can more strongly constrain the large-scale structures of the universe. To check the accuracy of our modelling we compare our predictions to the results from the Millennium Simulation.