HYMALAIA: a hybrid lagrangian model for intrinsic alignments

Abstract

ABSTRACT The intrinsic alignment of galaxies is an important ingredient for modelling weak-lensing measurements, and a potentially valuable cosmological and astrophysical signal. In this paper, we present HYbrid Model Advected from LAgrangian space for IA (HYMALAIA): a new model to predict the intrinsic alignments of biased tracers. HYMALAIA is based on a perturbative expansion of the statistics of the Lagrangian shapes of objects, which is then advected to Eulerian space using the fully non-linear displacement field obtained from N-body simulations. We demonstrate that HYMALAIA is capable of consistently describing monopole and quadrupole of halo shape–shape and matter–shape correlators, and that, without increasing the number of free parameters, it does so more accurately than other perturbatively inspired models such as the non-linear alignment model and the tidal-alignment-tidal-torquing model.