Scale-dependent bias with higher order primordial non-Gaussianity: Use of the Integrated Perturbation Theory

TL;DR

This paper develops an improved analytical model for the scale-dependent bias of biased objects considering higher order primordial non-Gaussianity parameters, using the integrated perturbation theory framework.

Contribution

It introduces a more accurate formula for the power spectrum incorporating fNL, gNL, and tauNL, and discusses the inequality between fNL and tauNL in the context of bias.

Findings

Derived a formula for the power spectrum with higher order non-Gaussianity parameters.

Analyzed the inequality between fNL and tauNL in scale-dependent bias.

Discussed higher order loop corrections to bias scale-dependency.

Abstract

We analytically derive a more accurate formula for the power spectrum of the biased objects with the primordial non-Gaussianity parameterized not only by the non-linearity parameter fNL, but also by gNL and tauNL which characterize the trispectrum of the primordial curvature perturbations. We adopt the integrated perturbation theory which was constructed in Matsubara (2011). We discuss an inequality between fNL and tauNL in the context of the scale-dependent bias, by introducing a stochasticity parameter. We also mention higher order loop corrections into the scale-dependency of the bias parameter.