标题： 宇宙微波背景双谱的多种估计方法及其在MAXIMA数据中的应用 显示英文标题

标题： Multiple Methods for Estimating the Bispectrum of the Cosmic Microwave Background with Application to the MAXIMA Data

摘要： 我们描述了用于估算宇宙微波背景数据双谱的不同方法。特别是，我们构建了平天空极限下的最小方差估计器，并将其结果与之前研究过的频率学方法进行了比较。应用于MAXIMA数据集的结果显示与原初高斯性一致。二次弱非高斯性由一个可调参数$f_{NL}$表征，对应于非高斯项与高斯项的比例$\sim 10^{-5}f_{NL}$，我们发现最小方差估计器的限制为$|f_{NL}|<950$，而通常的频率学估计器的限制为$|f_{NL}|<1650$。这些是对原初非高斯性的最严格的限制，包含了辐射传递函数的所有影响。 显示英文摘要

摘要： We describe different methods for estimating the bispectrum of Cosmic Microwave Background data. In particular we construct a minimum variance estimator for the flat-sky limit and compare results with previously-studied frequentist methods. Application to the MAXIMA dataset shows consistency with primordial Gaussianity. Weak quadratic non-Gaussianity is characterised by a tunable parameter $f_{NL}$, corresponding to non-Gaussianity at a level $\sim 10^{-5}f_{NL}$ (ratio of non-Gaussian to Gaussian terms), and we find limits of $|f_{NL}|<950$ for the minimum-variance estimator and $|f_{NL}|<1650$ for the usual frequentist estimator. These are the tightest limits on primordial non-Gaussianity which include the full effects of the radiation transfer function.