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Quijote-PNG: Simulations of primordial non-Gaussianity and the information content of the matter field power spectrum and bispectrum
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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.
Forward citations
Cited by 2 Pith papers
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Ab Initio Cosmological Simulations: From Inflation to Present-Day Structure Formation
Nonlinear axion-U(1) inflation, simulated on a lattice and fed into N-body simulations, boosts small-scale structure and high-redshift halo counts by up to ~200% relative to standard single-field initial conditions.
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$\texttt{GENGARS}$: Accurate non-Gaussian initial conditions with arbitrary bispectrum for N-body simulations
GENGARS uses a Schwinger-parameterized reduced bispectrum kernel to generate N-body initial conditions for arbitrary separable PNG shapes, reducing spurious power-spectrum contributions relative to 2LPT-PNG.
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