Improving lognormal models for cosmological fields

TL;DR

This paper introduces methods to improve joint modeling of cosmological fields using lognormal distributions, overcoming previous limitations for more accurate large-scale structure simulations.

Contribution

It proposes two novel approaches to enhance lognormal models for joint clustering and lensing simulations, including power spectrum distortion and improved convergence distribution fitting.

Findings

Achieves sub-percent accuracy in joint simulations

Provides a publicly available simulation toolkit (FLASK)

Demonstrates effective modeling of correlated cosmological fields

Abstract

It is common practice in cosmology to model large-scale structure observables as lognormal random fields, and this approach has been successfully applied in the past to the matter density and weak lensing convergence fields separately. We argue that this approach has fundamental limitations which prevent its use for jointly modelling these two fields since the lognormal distribution's shape can prevent certain correlations to be attainable. Given the need of ongoing and future large-scale structure surveys for fast joint simulations of clustering and weak lensing, we propose two ways of overcoming these limitations. The first approach slightly distorts the power spectra of the fields using one of two algorithms that minimises either the absolute or the fractional distortions. The second one is by obtaining more accurate convergence marginal distributions, for which we provide a fitting function, by integrating the lognormal density along the line of sight. The latter approach also provides a way to determine directly from theory the skewness of the convergence distribution and, therefore, the parameters for a lognormal fit. We present the public code Full-sky Lognormal Astro-fields Simulation Kit (FLASK) which can make tomographic realisations on the sphere of an arbitrary number of correlated lognormal or Gaussian random fields by applying either of the two proposed solutions, and show that it can create joint simulations of clustering and lensing with sub-per-cent accuracy over relevant angular scales and redshift ranges.