发表机构
Stanford University; California Institute of Technology; Kavli Institute for Particle Astrophysics and Cosmology, Stanford University; SLAC National Accelerator Laboratory; University of Chicago; NSF-Simons AI Institute for the Sky (SkAI); Fermi National Accelerator Laboratory; University of Melbourne（斯坦福大学; 加州理工学院; 斯坦福大学卡弗里粒子天体物理与宇宙学研究所; SLAC国家加速器实验室; 芝加哥大学; NSF-西蒙斯天空人工智能研究所; 费米国家加速器实验室; 墨尔本大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究构建了前景鲁棒的SPT-3G D1引力透镜模板，其去透镜效率为迄今最高，可用于改进原初引力波B模式的搜寻，将应用于BICEP数据的相关分析。
AI 中文摘要
宇宙微波背景（CMB）的引力透镜效应会产生B模式偏振，这是原初引力波（PGW）B模式搜寻的主要污染源。最新的BICEP结果显示，对PGW B模式的最强约束已受到透镜B模式的显著限制。本研究中，我们提出利用SPT-3G和Planck数据构建的CMB透镜B模式模板，该模板可表征透镜B模式，用于改进PGW B模式搜寻。我们使用2019和2020观测季的SPT-3G数据获取E模式及CMB重建的透镜势，并采用Planck提供的宇宙红外背景（CIB）图作为外部透镜示踪剂。为测试透镜模板中的河外前景偏差，我们考虑了具有不同前景免疫水平的CMB透镜重建变体：标准和轮廓硬化的全局最小方差（GMV）二次估计器，以及仅偏振二次估计器。我们利用高斯模拟和包含现实非高斯前景的Agora模拟对模板构建进行验证。模拟结果表明，采用轮廓硬化GMV + CIB示踪剂构建的模板，前景诱导偏差被强烈抑制，残留偏差低于模板功率谱统计不确定性的10%。对该模板的数据差异测试同样未发现显著前景污染的证据。该前景免疫透镜模板在20 ≤ ℓ ≤ 200范围内平均实现了A_lens^res ≃ 0.48的去透镜残留BB功率，是迄今为止去透镜效率最高的透镜模板。这些结果验证了一种构建前景鲁棒透镜模板的方法，该方法将用于即将开展的BICEP数据去透镜PGW B模式分析。
英文摘要
Gravitational lensing of the cosmic microwave background (CMB) generates B-mode polarization that acts as a source of contamination to searches for B modes generated by primordial gravitational waves (PGWs). The strongest constraint on PGW B modes is already significantly limited by lensing B modes, as shown in the most recent BICEP result. In this work, we present CMB lensing B-mode templates constructed using SPT-3G and Planck data, which characterize the lensing B modes and can be used to improve PGW B-mode searches. We use SPT-3G data from the 2019 and 2020 observing seasons for the E modes and the CMB-reconstructed lensing potential, and a cosmic infrared background (CIB) map from Planck as an external lensing tracer. To test for extragalactic foreground biases in the lensing template, we consider CMB lensing reconstruction variants with different levels of foreground immunity: the standard and profile-hardened global minimum variance (GMV) quadratic estimators, and a polarization-only quadratic estimator. We validate the template construction using Gaussian simulations and Agora simulations with realistic non-Gaussian foregrounds. From simulations, we find that foreground-induced biases are strongly suppressed for the template constructed with the profile-hardened GMV + CIB tracer, with residual bias below 10% of the statistical uncertainty on the template power spectrum. Data difference tests on this template similarly show no evidence for significant foreground contamination. This foreground-immune lensing template achieves delensed residual BB power of $A_{\rm lens}^{\rm res} \simeq 0.48$ averaged over $20 \leq \ell \leq 200$, the highest delensing efficiency lensing template to date. These results demonstrate and validate a method to construct foreground-robust lensing templates which will be used in upcoming delensed PGW B-mode analyses of BICEP data.
