论文标题
CMB交叉功率谱的标量二次最大似然估计器
Scalar quadratic maximum likelihood estimators for the CMB cross power spectrum
论文作者
论文摘要
估计宇宙微波背景（CMB）的互相关功率谱，尤其是T B和EB光谱，对于测试宇宙学和诊断隐藏仪器系统系统的均等对称性非常重要。二次最大似然（QML）估计器提供了功率光谱的最佳估计值，但计算上非常昂贵。混合伪CL估计器的计算快速，但在大尺度上的性能很差。作为先前工作的自然扩展（Chen等，2021），在本文中，我们提出了一个新的无偏估计量，基于E-Zaldarriaga（SZ）的E-B分离方法和标量QML方法，用于重建跨交易功率谱，称为QML-SZ估计器。我们的新估计器依赖于构建标量图的能力，这使我们能够使用标量QML估计器获得互相关功率谱。通过降低像素数和算法复杂性，计算成本几乎较小一个数量级，并且在测试情况下，运行时间差不多两个数量级。
Estimating the cross-correlation power spectra of cosmic microwave background (CMB), in particular, the T B and EB spectra, is important for testing parity symmetry in cosmology and diagnosing insidious instruments systematics. The Quadratic Maximum Likelihood (QML) estimator provides the optimal estimates of power spectra, but it is computationally very expensive. The hybrid pseudo-Cl estimator is computationally fast but performs poorly on large scales. As a natural extension of previous work (Chen et al. 2021), in this article, we present a new unbiased estimator based on the Smith-Zaldarriaga (SZ) approach of E-B separation and scalar QML approach to reconstruct the cross-correlation power spectrum, called QML-SZ estimator. Our new estimator relies on the ability to construct scalar maps, which allows us to use a scalar QML estimator to obtain the cross-correlation power spectrum. By reducing the pixel number and algorithm complexity, the computational cost is nearly one order of magnitude smaller and the running time is nearly two orders of magnitude faster in the test situations.
