Constraining higher-order parameters for primordial non-Gaussianities from power spectra and bispectra of imaging survey

TL;DR

This paper explores how upcoming imaging surveys can significantly improve constraints on primordial non-Gaussianity parameters using higher-order statistics and cross-correlations, surpassing current CMB limits.

Contribution

It demonstrates that bispectra and cross-correlation statistics can break parameter degeneracies and tighten constraints on $f_{NL}$, $g_{NL}$, and $ au_{NL}$ from galaxy clustering and lensing data.

Findings

Bispectra break degeneracies between non-Gaussian parameters.

Cross-correlation statistics double the constraint precision.

Upcoming surveys can outperform Planck in constraining primordial non-Gaussianity.

Abstract

We investigate the statistical power of higher-order statistics and cross-correlation statistics to constrain the primordial non-Gaussianity from the imaging surveys. In particular, we consider the local-type primordial non- Gaussianity and discuss how well one can tightly constrain the higher-order non-Gaussian parameters ($g_{\rm NL}$ and $\tau_{\rm NL}$) as well as the leading order parameter $f_{\rm NL}$ from the halo/galaxy clustering and weak gravitational lensing measurements. Making use of a strong scale-dependent behavior in the galaxy/halo clustering, Fisher matrix analysis reveals that the bispectra can break the degeneracy between non-Gaussian parameters ($f_{\rm NL}$, $g_{\rm NL}$ and $\tau_{\rm NL}$) and this will give simultaneous constraints on those three parameters. The combination of cross-correlation statistics further improves the constraints by factor of 2. As a result, upcoming imaging surveys like the Large Synoptic Survey Telescope have the potential to improve the constraints on the primordial non-Gaussianity much tighter than those obtained from the CMB measurement by Planck, giving us an opportunity to test the single-sourced consistency relation, $\tau_{\rm NL} \ge (36/25) f_{\rm NL}^2$.