Constraints on Primordial Non-Gaussianity from a Needlet Analysis of the WMAP-5 Data
arXiv:0812.2478 · doi:10.1111/j.1365-2966.2009.14847.x
Abstract
We look for a non-Gaussian signal in the WMAP 5-year temperature anisotropy maps by performing a needlet-based data analysis. We use the foreground-reduced maps obtained by the WMAP team through the optimal combination of the W, V and Q channels, and perform realistic non-Gaussian simulations in order to constrain the non-linear coupling parameter $\fnl$. We apply a third-order estimator of the needlet coefficients skewness and compute the statistics of its distribution. We obtain $-80<\fnl<120$ at 95% confidence level, which is consistent with a Gaussian distribution and comparable to previous constraints on the non-linear coupling. We then develop an estimator of $\fnl$ based on the same simulations and we find consistent constraints on primordial non-Gaussianity. We finally compute the three point correlation function in needlet space: the constraints on $\fnl$ improve to $-50<\fnl<110$ at 95% confidence level.
9 pages, 6 figures. MNRAS in press, updated to accepted version
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