Quijote-PNG: Quasi-maximum likelihood estimation of Primordial Non-Gaussianity in the non-linear halo density field

Abstract

We study primordial non-Gaussian signatures in the redshift-space halo field on non-linear scales, using a quasi-maximum likelihood estimator based on optimally compressed power spectrum and modal bispectrum statistics. We train and validate the estimator on a suite of halo catalogues constructed from the Quijote-PNG N-body simulations, which we release to accompany this paper. We verify its unbiasedness and near optimality, for the three main types of primordial non-Gaussianity (PNG): local, equilateral, and orthogonal. We compare the modal bispectrum expansion with a $k$-binning approach, showing that the former allows for faster convergence of numerical derivatives in the computation of the score-function, thus leading to better final constraints. We find, in agreement with previous studies, that the local PNG signal in the halo-field is dominated by the scale-dependent bias signature on large scales and saturates at $k\sim 0.2h{\mathrm{Mpc}}^{-1}$, whereas the small-scale bispectrum is the main source of information for equilateral and orthogonal PNG. Combining power spectrum and bispectrum on non-linear scales plays an important role in breaking degeneracies between cosmological and PNG parameters; such degeneracies remain however strong for equilateral PNG. We forecast that PNG parameters can be constrained with $\Delta f_{\mathrm{NL}}^{\mathrm{local}}=45$, $\Delta f_{\mathrm{NL}}^{\mathrm{equil}}=570$, $\Delta f_{\mathrm{NL}}^{\mathrm{ortho}}=110$, on a cubic volume of $1{\left(\mathrm{Gpc}/\mathrm{h}\right)}^3$, at $z=1$, considering scales up to $k_{\max }=0.5h{\mathrm{Mpc}}^{-1}$.

17 pages, 10 figures. v2: minor updates to match published version

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