Primordial non-Gaussianity: large-scale structure signature in the perturbative bias model
Patrick McDonald (CITA)

TL;DR
This paper investigates how primordial non-Gaussianity affects large-scale structure clustering, revealing the necessity of a new bias term and demonstrating the potential for precise future measurements of non-Gaussianity parameters.
Contribution
It introduces a new bias term proportional to phi in the perturbative bias model, generalizes the effect to various halo models, and discusses implications for measuring primordial non-Gaussianity.
Findings
A new bias term proportional to phi is necessary.
Future surveys can measure fNL to within ±1 at z<2.
Renormalization removes infinite corrections in the power spectrum.
Abstract
I compute the effect on the power spectrum of tracers of the large-scale mass-density field (e.g., galaxies) of primordial non-Gaussianity of the form Phi=phi+fNL (phi-<phi^2>)+gNL phi^3+..., where Phi is proportional to the initial potential fluctuations and phi is a Gaussian field, using beyond-linear-order perturbation theory. I find that the need to eliminate large higher-order corrections necessitates the addition of a new term to the bias model, proportional to phi, i.e., delta_g=b_delta delta+b_phi fNL phi+..., with all the consequences this implies for clustering statistics, e.g., P_gg(k)=b_delta^2 P_deltadelta(k)+2 b_delta b_phi fNL P_phidelta(k)+b_phi^2 fNL^2 P_phiphi(k)+... . This result is consistent with calculations based on a model for dark matter halo clustering, showing that the form is quite general, not requiring assumptions about peaks, or the formation or existence…
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