Quijote PNG: The information content of the halo power spectrum and bispectrum

TL;DR

This paper assesses the potential of small-scale halo field measurements, including power spectrum and bispectrum, to constrain different types of primordial non-Gaussianity using advanced simulations.

Contribution

It is the first to analyze small, non-linear scales up to $k_{max}=0.5 h/Mpc$ for PNG constraints, exploring degeneracies with cosmological parameters.

Findings

Power spectrum measurements tightly constrain local PNG.

Small scales significantly improve bispectrum constraints for equilateral and orthogonal PNG.

Combining power spectrum and bispectrum reduces parameter degeneracies.

Abstract

We investigate how much can be learnt about four types of primordial non-Gaussianity (PNG) from small-scale measurements of the halo field. Using the QUIJOTE-PNG simulations, we quantify the information content accessible with measurements of the halo power spectrum monopole and quadrupole, the matter power spectrum, the halo-matter cross spectrum and the halo bispectrum monopole. This analysis is the first to include small, non-linear scales, up to $k_\mathrm{max}=0.5 \mathrm{h/Mpc}$, and to explore whether these scales can break degeneracies with cosmological and nuisance parameters making use of thousands of N-body simulations. We perform all the halo measurements in redshift space with a single sample comprised of all halos with mass $>3.2 \times 10^{13}~h^{-1}M_\odot$. For local PNG, measurements of the scale dependent bias effect from the power spectrum using sample variance cancellation provide significantly tighter constraints than measurements of the halo bispectrum. In this case measurements of the small scales add minimal additional constraining power. In contrast, the information on equilateral and orthogonal PNG is primarily accessible through the bispectrum. For these shapes, small scale measurements increase the constraining power of the halo bispectrum by up to $\times4$, though the addition of scales beyond $k\approx 0.3 \mathrm{h/Mpc}$ improves constraints largely through reducing degeneracies between PNG and the other parameters. These degeneracies are even more powerfully mitigated through combining power spectrum and bispectrum measurements. However even with combined measurements and small scale information, equilateral non-Gaussianity remains highly degenerate with $\sigma_8$ and our bias model.