Effective Field Theory of Intrinsic Alignments at One Loop Order: a Comparison to Dark Matter Simulations

Abstract

We test the regime of validity of the effective field theory (EFT) of intrinsic alignments (IA) at the one-loop level by comparing with 3D halo shape statistics in N-body simulations. This model is based on the effective field theory of large-scale structure (EFT of LSS) and thus a theoretically well-motivated extension of the familiar non-linear alignment (NLA) model and the tidal-alignment-tidal-torquing (TATT) model. It contains a total of 8 free bias parameters. Specifically, we measure the dark matter halo shape-shape multipolesBB (k) as well as the matter-shape multipoles P (0) δE (k), P(2) δE (k) from the simulations and perform a joint fit to determine the largest wavenumber k max up to which the theory predictions from the EFT of IA are consistent with the measurements. We find that the EFT of IA is able to describe intrinsic alignments of dark matter halos up to k max = 0.30 h/Mpc at z = 0. This demonstrates a clear improvement over other existing alignment models like NLA and TATT, which are only accurate up to k max = 0.05 h/Mpc. We examine the posterior distributions of the higher-order bias parameters, and show that their inclusion is necessary to describe intrinsic alignments in the quasi-linear regime. Further, the EFT of IA is able to accurately describe the auto-spectrum of intrinsic alignment B-modes, in contrast to the other alignment models considered.

Quadratic shape biases in three-dimensional halo intrinsic alignments

“…ref. [27] for this direction). However, this method suffers greatly from the cosmic variance and therefore many realizations are required to beat the cosmic variance.…”

“…Fortunately, we can recycle the basic framework developed in the context of galaxy clustering to study these non-linearities, since the underlying physics that governs the intrinsic alignments should be similar. In particular, the perturbative approach to the intrinsic alignments attracts attention given its rigorousness and the success in the galaxy clustering [21][22][23][24][25][26][27][28].…”

“…In particular, the tree-level bispectrum requires the quadratic shape biases and one-loop power spectrum requires quadratic and cubic biases. Although these biases are necessary components to complete spectra beyond the linear power spectrum, varying these biases induces degeneracies between parameters and generally degrades the parameter constrains [27]. Hence, it would be important to obtain prior knowledge of higher-order shape biases both from the theoretical grounding and from comparison with cosmological simulations.…”