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arXiv 0812.2478astro-ph
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从WMAP-5数据的Needlet分析看原始非高斯性的约束

Constraints on Primordial Non-Gaussianity from a Needlet Analysis of the WMAP-5 Data

Davide Pietrobon, Paolo Cabella, Amedeo Balbi, Giancarlo de Gasperis, Nicola Vittorio

摘要:

我们寻找一个非高斯信号的WMAP 5年的温度各向异性图进行针为基础的数据分析。我们使用WMAP团队通过W,V和Q通道的最佳组合获得的前景缩减地图,并进行现实的非高斯模拟,以约束非线性耦合参数$\fnl$。我们应用三阶估计的针状系数偏度和计算其分布的$χ^2$统计。我们得到$-80<\fnl<120$在95%的置信水平,这是一致的高斯分布和以前的非线性耦合的约束。然后,我们开发了一个估计的$\fnl$基于相同的模拟,我们发现一致的约束原始非高斯。最后,我们计算了针状空间中的三点关联函数:在95%的置信水平下,$\fnl$上的约束改进为$-50<\fnl<110$。

英文摘要:

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 $χ^2$ 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.

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