swMATH ID: 44416
Software Authors: Mikolaj Borzyszkowski, Daniele Bertacca, Cristiano Porciani (Argelander-Institut für Astronomie, Bonn, Germany)
Description: LIGER: mock relativistic light-cones from Newtonian simulations. We introduce a method to create mock galaxy catalogues in redshift space including general relativistic effects to linear order in the cosmological perturbations. We dub our method LIGER, short for ‘light cones with general relativity’. LIGER takes a (N-body or hydrodynamic) Newtonian simulation as an input and outputs the distribution of galaxies in comoving redshift space. This result is achieved making use of a coordinate transformation and simultaneously accounting for lensing magnification. The calculation includes both local corrections and terms that have been integrated along the line of sight. Our fast implementation allows the production of many realizations that can be used to forecast the performance of forthcoming wide-angle surveys and to estimate the covariance matrix of the observables. To facilitate this use, we also present a variant of LIGER designed for large-volume simulations with low mass resolution. In this case, the galaxy distribution on large scales is obtained by biasing the matter-density field. Finally, we present two sample applications of LIGER. First, we discuss the impact of weak gravitational lensing onto the angular clustering of galaxies in a Euclid-like survey. In agreement with previous analytical studies, we find that magnification bias can be measured with high confidence. Second, we focus on two generally neglected Doppler-induced effects: magnification and the change of number counts with redshift. We show that the corresponding redshift-space distortions can be detected at 5.5σ significance with the completed Square Kilometre Array.
Homepage: https://astro.uni-bonn.de/~porciani/LIGER/
Source Code:  https://gitlab.com/cosmology-aifa/ligerv2
Keywords: Cosmology and Nongalactic Astrophysics; arXiv_astro-ph.CO
Related Software: CLASS; GADGET; CONCEPT; PKDGRAV3; gevolution; RAMSES; CAMB; ASCL; fRevolution; ECOSMOG; CLASSgal; xPand
Cited in: 4 Documents

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