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arXiv 1807.02484astro-ph.CO
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CMB互相关函数的二次估计

Quadratic estimator for CMB cross-correlation

S. Vanneste, S. Henrot-Versillé, T. Louis, M. Tristram

摘要:

二次极大似然估计可用于重建宇宙微波背景(CMB)功率谱,误差条最小。尽管如此,它仍然需要对数据集噪声协方差矩阵进行准确估计,以便校正伪偏差。我们描述了这种方法的扩展互相关,从而消除噪声偏置和减轻系统效应的影响,提供它们是不相关的。在大角度尺度和中等角度尺度下,分别对应于卫星和地面CMB实验,在两个模拟调查上对该估计进行了测试。分析集中在偏振图,在很宽的范围内的噪声水平从0.1到50 μ K.arcmin。我们展示了如何估计最大限度地减少由于E和B模式之间的偏振泄漏的方差的增加。我们比较这种方法与纯伪谱形式主义,这是计算速度更快,但不太理想,特别是在大的角度尺度。

英文摘要:

The Quadratic Maximum Likelihood estimator can be used to reconstruct the Cosmic Microwave Background (CMB) power spectra with minimal error bars. Still, it requires an accurate estimate of the datasets noise covariance matrix in order to be corrected for spurious bias. We describe an extension of this method to cross-correlation, thus removing noise bias and mitigating the impact of systematic effects, providing they are uncorrelated. This estimator is tested on two simulation surveys at large and intermediate angular scales, respectively corresponding to satellite and ground-based CMB experiments. The analysis focuses on polarization maps, over a wide range of noise levels from 0.1 to 50 muK.arcmin. We show how this estimator minimizes the increase of variance due to polarization leakage between E and B modes. We compare this method with the pure pseudo-spectrum formalism which is computationally faster but less optimal, especially on large angular scales.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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