Quijote-PNG: Simulations of primordial non-Gaussianity and the information content of the matter field power spectrum and bispectrum

TL;DR

This paper introduces a large suite of N-body simulations to analyze the information content of matter power spectrum and bispectrum measurements for primordial non-Gaussianity, especially on non-linear scales, enhancing constraints on early Universe models.

Contribution

The study provides the first joint analysis of PNG and cosmological information from power spectrum and bispectrum on non-linear scales using new simulations.

Findings

Significant improvement in PNG constraints up to k_max ≈ 0.3 h/Mpc.

Diminishing returns in information gain beyond this scale.

Combining power spectrum and bispectrum helps break degeneracies with ΛCDM parameters.

Abstract

Primordial non-Gaussianity (PNG) is one of the most powerful probes of the early Universe and measurements of the large scale structure of the Universe have the potential to transform our understanding of this area. However relating measurements of the late time Universe to the primordial perturbations is challenging due to the non-linear processes that govern the evolution of the Universe. To help address this issue we release a large suite of N-body simulations containing four types of PNG: \textsc{quijote-png}. These simulations were designed to augment the \textsc{quijote} suite of simulations that explored the impact of various cosmological parameters on large scale structure observables. Using these simulations we investigate how much information on PNG can be extracted by extending power spectrum and bispectrum measurements beyond the perturbative regime at $z=0.0$. This is the first joint analysis of the PNG and cosmological information content accessible with power spectrum and bispectrum measurements of the non-linear scales. We find that the constraining power improves significantly up to $k_\mathrm{max}\approx 0.3 h/{\rm Mpc}$, with diminishing returns beyond as the statistical probes signal-to-noise ratios saturate. This saturation emphasizes the importance of accurately modelling all the contributions to the covariance matrix. Further we find that combining the two probes is a powerful method of breaking the degeneracies with the $\Lambda$CDM parameters.