论文标题
推理重力镜头和斑点电离与未来CMB数据
Inference of gravitational lensing and patchy reionization with future CMB data
论文作者
论文摘要
我们开发了一种最佳的贝叶斯解决方案，用于在宇宙微波背景（CMB）中共同推断出源自重力透镜和在电离时期内的斑块筛选。该方法能够从数据中提取完整的信息内容，从而改善了先前考虑的二次估计器用于镜头和筛选。我们使用边际无偏分扩展（MUSE）方法预测约束，并表明它们在很大程度上由CMB极化主导，并取决于电离的确切细节。对于与产生最大筛选信号的当前数据一致的模型，使用SPT-3G使用镜头和筛选之间的互相关检测（3 \，$σ$），而CMB-S4可以检测自动相关的检测。筛选信号最低的模型逃避了SPT-3G的灵敏度，但仍然可以通过透镜互相关使用CMB-S4检测。
We develop an optimal Bayesian solution for jointly inferring secondary signals in the Cosmic Microwave Background (CMB) originating from gravitational lensing and from patchy screening during the epoch of reionization. This method is able to extract full information content from the data, improving upon previously considered quadratic estimators for lensing and screening. We forecast constraints using the Marginal Unbiased Score Expansion (MUSE) method, and show that they are largely dominated by CMB polarization, and depend on the exact details of reionization. For models consistent with current data which produce the largest screening signals, a detection (3\,$σ$) of the cross-correlation between lensing and screening is possible with SPT-3G, and a detection of the auto-correlation is possible with CMB-S4. Models with the lowest screening signals evade the sensitivity of SPT-3G, but are still possible to detect with CMB-S4 via their lensing cross-correlation.
