Modeling Intrinsic Galaxy Alignment in the MICE Simulation

TL;DR

This paper develops a realistic model of galaxy intrinsic alignments using the MICE simulation, calibrates it against observations, and assesses its impact on weak lensing measurements, finding good agreement with observed data.

Contribution

It introduces an advanced IA model incorporating galaxy shape distributions and luminosity-dependent alignments, calibrated with observational data, and evaluates its effect on shear statistics.

Findings

Both NLA and TATT models fit large-scale measurements well.

TATT outperforms NLA at smaller scales.

Predicted IA contamination is within measurement uncertainties.

Abstract

The intrinsic alignment (IA) of galaxies is potentially a major limitation in deriving cosmological constraints from weak lensing surveys. In order to investigate this effect we assign intrinsic shapes and orientations to galaxies in the light-cone output of the MICE simulation, spanning $\sim5000\,{\rm deg}^2$ and reaching redshift $z=1.4$. This assignment is based on a 'semi-analytic' IA model that uses photometric properties of galaxies as well as the spin and shape of their host halos. Advancing on previous work, we include more realistic distributions of galaxy shapes and a luminosity dependent galaxy-halo alignment. The IA model parameters are calibrated against COSMOS and BOSS LOWZ observations. The null detection of IA in observations of blue galaxies is accounted for by setting random orientations for these objects. We compare the two-point alignment statistics measured in the simulation against predictions from the analytical IA models NLA and TATT over a wide range of scales, redshifts and luminosities for red and blue galaxies separately. We find that both models fit the measurements well at scales above $8\,h^{-1}{\rm Mpc}$, while TATT outperforms NLA at smaller scales. The IA parameters derived from our fits are in broad agreement with various observational constraints from red galaxies. Lastly, we build a realistic source sample, mimicking DES Year 3 observations and use it to predict the IA contamination to the observed shear statistics. We find this prediction to be within the measurement uncertainty, which might be a consequence of the random alignment of blue galaxies in the simulation.