论文标题
在存在银河前景和系统效果的情况下,用于分析下一代,两极分化的CMB数据集的框架
Framework for analysis of next generation, polarised CMB data sets in the presence of galactic foregrounds and systematic effects
论文作者
论文摘要
达到足够的灵敏度来检测原始B模型,需要现代的CMB极化实验才能依靠新技术,这对于部署了数千个具有广泛频率覆盖的阵列所必需的,并长时间操作它们。不可避免地,实验设计的复杂性不可避免地引入了新的仪器和系统效果,这可能会影响新工具的性能。在这项工作中,我们通过在数据模型中直接包含(参数)仪器效应的(参数)模型来扩展标准数据分析管道。然后,我们在分析中为它们纠正,考虑了最终结果中的其他不确定性。我们将这些技术嵌入到一般的端到端形式主义中,用于估计仪器和前景模型对原始B模式信号振幅的影响的影响。我们专注于参数组件分离方法,我们将其推广,以同时估算仪器和前景参数。 我们通过研究由成年半波板(HWP)引起的效果来证明框架,该效果导致仪器极化角的频率变化以及定义观察频带的实验带通道。我们假设一个典型的3级CMB极化实验,并表明从每个频带收集的原始数据中恢复的地图将不可避免地是Q和U Stokes参数的线性混合物。然后,我们得出适用于此类情况的新的通用数据模型,并扩展了组件分离方法来考虑它。我们发现,某些仪器参数,尤其是描述HWP的仪器参数可以通过数据本身成功限制,而无需外部信息,而其他仪器(例如带通路)则需要先精确地知道。
Reaching the sufficient sensitivity to detect primordial B-modes requires modern CMB polarisation experiments to rely on new technologies, necessary for the deployment of arrays thousands of detectors with a broad frequency coverage and operating them for extended periods of time. This increased complexity of experimental design unavoidably introduces new instrumental and systematic effects, which may impact performance of the new instruments. In this work we extend the standard data analysis pipeline by including a (parametric) model of instrumental effects directly in the data model. We then correct for them in the analysis, accounting for the additional uncertainty in the final results. We embed these techniques within a general, end-to-end formalism for estimating the impact of the instrument and foreground models on constraints on the amplitude of the primordial B-mode signal. We focus on the parametric component separation approach which we generalize to allow for simultaneous estimation of instrumental and foreground parameters. We demonstrate the framework by studying the effects induced by an achromatic half-wave plate (HWP), which lead to a frequency-dependent variation of the instrument polarisation angle, and experimental bandpasses which define observational frequency bands. We assume a typical Stage-3 CMB polarisation experiment, and show that maps recovered from raw data collected at each frequency band will unavoidably be linear mixtures of the Q and U Stokes parameters. We then derive a new generalized data model appropriate for such cases, and extend the component separation approach to account for it. We find that some of the instrumental parameters, in particularly those describing the HWP can be successfully constrained by the data themselves without need for external information, while others, like bandpasses, need to be known with good precision in advance.