Intrinsic alignments in the FLAMINGO simulations with two-point statistics

¹ Leiden Observatory, Leiden University, Niels Bohrweg 2, 2333 CA, Leiden, The Netherlands
² Institute for Theoretical Physics, Utrecht University, Princetonplein 5, 3584 CC, Utrecht, The Netherlands
³ Lorentz Institute for Theoretical Physics, Leiden University, PO box 9506, 2300 RA, Leiden, The Netherlands

^★ Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Received: 22 January 2026
Accepted: 15 May 2026

Abstract

Intrinsic alignments are a major astrophysical contaminant for next generation large-sky surveys such as Euclid and LSST. Large hydrodynamic simulations are crucial for informing the alignment modelling for these surveys. We measured the 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 modelled 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 compared the measured A₁ amplitude to observational data and found a good agreement. We measured the dependence of the NLA and TATT free parameters on halo mass. We also introduced a mass-dependent TATT model, TATT-M, by establishing empirical relations between the halo mass and the TATT parameters. This allowed us to fit TATT with only one parameter, A₁, with A₂/A₁ being a constant and A_1δ/A₁ 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 tested whether the TATT parameters are sensitive to feedback. Variations in the AGN and supernova feedback do not significantly change the alignment amplitude beyond the level 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.