Constraining $f_{NL}$ using the Large-Scale Modulation of Small-Scale Statistics

Understand

We implement a novel formalism to constrain primordial non-Gaussianity of the local type from the large-scale modulation of the small-scale power spectrum.

• Our approach combines information about primordial non-Gaussianity contained in the squeezed bispectrum and the collapsed trispectrum of large-scale structure together in a computationally amenable and consistent way, while avoiding the need to model complicated covariances of higher $N$-point functions.
• This work generalizes our recent work, which used a neural network estimate of local power, to the more conventional local power spectrum statistics, and explores using both matter field and halo catalogues from the Quijote simulations.
• We find that higher $N$-point functions of the matter field can provide strong constraints on $f_{NL}$, but higher $N$-point functions of the halo field, at the halo density of Quijote, only marginally improve constraints from the two-point function.