Testing the reliability of fast methods for weak lensing simulations: wl-moka on pinocchio. Issue 2 (3rd June 2020)

• Record Type: Journal Article
• Authors: Giocoli, Carlo; Monaco, Pierluigi; Moscardini, Lauro; Castro, Tiago; Meneghetti, Massimo; Metcalf, R Benton; Baldi, Marco
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 496:Issue 2(2020)
• Page Start: 1307
• Page End: 1324
• Publication Date: 2020-06-03
• Subjects: gravitational lensing: weak -- galaxies: haloes -- cosmology: theory -- dark matter; Astronomy -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnras/staa1538
• Languages: English
• ISSNs: 0035-8711

Abstract

ABSTRACT: The generation of simulated convergence maps is of key importance in fully exploiting weak lensing by large-scale structure (LSS) from which cosmological parameters can be derived. In this paper, we present an extension of the pinocchio code that produces catalogues of dark matter haloes so that it is capable of simulating weak lensing by Modify LSS into Large Scale Structures (LSS). Like wl-moka, the method starts with a random realization of cosmological initial conditions, creates a halo catalogue and projects it on to the past light-cone, and paints in haloes assuming parametric models for the mass density distribution within them. Large-scale modes that are not accounted for by the haloes are constructed using linear theory. We discuss the systematic errors affecting the convergence power spectra when Lagrangian perturbation theory at increasing order is used to displace the haloes within pinocchio, and how they depend on the grid resolution. Our approximate method is shown to be very fast when compared to full ray-tracing simulations from an N -body run and able to recover the weak lensing signal, at different redshifts, with a few percent accuracy. It also allows for quickly constructing weak lensing covariance matrices, complementing pinocchio 's ability of generating the cluster mass function and galaxy clustering covariances and thus paving the way for calculating cross-covariances between the different probes. This work advances these approximate methods as tools for simulating and analysing survey data for cosmological purposes.