Intrinsic alignments in the FLAMINGO simulations with two-point statistics

TL;DR

This study uses hydrodynamic simulations to measure and model intrinsic galaxy alignments, providing constraints and a new mass-dependent TATT model to improve contamination mitigation in future large-sky surveys.

Contribution

It introduces a mass-dependent TATT model fitted to hydrodynamic simulation data, offering improved alignment modeling for cosmological surveys.

Findings

Both NLA and TATT models fit the data well.

TATT-M model is strongly preferred over NLA.

Feedback variations do not significantly affect alignment amplitude.

Abstract

Intrinsic alignments are a major astrophysical contaminant for next generation large-sky surveys like Euclid and LSST. Large hydrodynamic simulations are crucial for informing the alignment modelling for these surveys. We measure position-position and position-shape correlations of a Luminous Red Galaxy sample from the FLAMINGO suite of hydrodynamical simulations, measuring the alignment signal for more than 4.9 million galaxies at redshift 0. We jointly model the clustering and alignment correlations to provide the tightest constraints on the alignment amplitude to date from a hydrodynamic simulation. We find that both the Non-Linear Alignment (NLA) and the more complex Tidal Alignment Tidal Torquing (TATT) models provide good fits to the data. We compare the measured $A_1$ amplitude to observational data and find good agreement. We measure the dependence of the NLA and TATT free parameters on halo mass. We also introduce a mass-dependent TATT model, TATT-M, by finding empirical relations between the halo mass and the TATT parameters. This allows us to fit TATT with only one parameter, $A_1$, with $A_2/A_1$ being a constant and $A_{1\delta}/A_1$ being a function of halo mass. Using a Bayesian approach, we find that TATT-M is very strongly preferred by the data over NLA. Using the baryonic feedback variations of the FLAMINGO simulation suite, we test whether the TATT parameters are sensitive to feedback. Variations in AGN and supernova feedback do not significantly change the alignment amplitude beyond the change associated with the dependence of galaxy stellar mass on the strength of feedback. Our results inform the IA modelling for upcoming surveys by providing guidance on model choices, priors and sensitivities to feedback.