Limits on Primordial Non-Gaussianity from Minkowski Functionals of the WMAP Temperature Anisotropies

TL;DR

This paper uses Minkowski Functionals to analyze WMAP data and constrain primordial non-Gaussianity, finding that the non-Gaussianity parameter fNL is limited to between -70 and 91 at 95% confidence.

Contribution

It introduces a method applying perturbative Minkowski Functional formulas directly to observational data to constrain primordial non-Gaussianity without extensive simulations.

Findings

Constraints on fNL: -70 to 91 at 95% confidence.

Analytical formulas agree well with simulated maps including observational effects.

Method enables direct application to observational data for non-Gaussianity analysis.

Abstract

We present an analysis of the Minkowski Functionals (MFs) describing the WMAP three-year temperature maps to place limits on possible levels of primordial non-Gaussianity. In particular, we apply perturbative formulae for the MFs to give constraints on the usual non-linear coupling constant fNL. The theoretical predictions are found to agree with the MFs of simulated CMB maps including the full effects of radiative transfer. The agreement is also very good even when the simulation maps include various observational artifacts, including the pixel window function, beam smearing, inhomogeneous noise and the survey mask. We find accordingly that these analytical formulae can be applied directly to observational measurements of fNL without relying on non-Gaussian simulations. Considering the bin-to-bin covariance of the MFs in WMAP in a chi-square analysis, we find that the primordial non-Gaussianity parameter is constrained to lie in the range -70<fNL<91 at 95% C.L. using the Q+V+W co-added maps.