Mitigating foreground biases in CMB lensing reconstruction using cleaned gradients
Mitigating foreground biases in CMB lensing reconstruction using cleaned gradients
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DOI：
10.1103/physrevd.98.023534
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发表时间：
2018-02
影响因子：
5
通讯作者：
M. Madhavacheril;J. Hill
中科院分区：
文献类型：
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作者：
M. Madhavacheril;J. Hill
宇宙微波背景（CMB）透镜汇聚的重建图将在未来几年的精密宇宙学中发挥重要作用。 CMB透镜图将能够校准高红移星系团的质量，并通过与星系巡天的互相关来精确测量宇宙结构的增长。在接下来的十年中，宇宙微波背景透镜重建将严重依赖于温度数据，而不是偏振数据，因此需要详细了解河外前景造成的偏差。短期内，其中最显着的偏差是由于热 Sunyaev-Zel'dovich (tSZ) 效应造成的。此外，高分辨率观测仅在少数频率下可用，这使得全面的前景清理具有挑战性。在本文中，我们演示了一种前景偏差问题的解决方案，该解决方案涉及仅清理 CMB 温度图的大尺度梯度。我们表明，tSZ 无偏差 CMB 透镜图所需的数据已经以普朗克和 WMAP 卫星实验跨多个频率的 CMB 大规模测量的形式存在。具体来说，我们表明，通过利用从涉及普朗克和 WMAP 数据的多频率分量分离获得的干净梯度，可以消除从 CMB 透镜推断出的光晕质量的偏差，并且可以准备星系互相关的特殊透镜图，而只需在信噪比方面做出很小的损失，同时不需要对 tSZ 偏差进行掩蔽、修复、建模或模拟工作。在我们关注互相关的同时，我们还表明梯度清理可以减轻由于温度和偏振前景的存在而引起的 CMB 透镜自谱偏差，同时信噪比损失最小。
Reconstructed maps of the lensing convergence of the cosmic microwave background (CMB) will play a major role in precision cosmology in coming years. CMB lensing maps will enable calibration of the masses of high-redshift galaxy clusters and will yield precise measurements of the growth of cosmic structure through cross-correlations with galaxy surveys. During the next decade, CMB lensing reconstruction will rely heavily on temperature data, rather than polarization, thus necessitating a detailed understanding of biases due to extragalactic foregrounds. In the near term, the most significant bias among these is that due to the thermal Sunyaev-Zel'dovich (tSZ) effect. Moreover, high-resolution observations will be available at only a few frequencies, making full foreground cleaning challenging. In this paper, we demonstrate a solution to the foreground bias problem that involves cleaning only the large-scale gradients of the CMB temperature map. We show that the data necessary for tSZ-bias-free CMB lensing maps already exist in the form of large-scale measurements of the CMB across multiple frequencies by the Planck and WMAP satellite experiments. Specifically, we show that the bias to halo masses inferred from CMB lensing is eliminated by the utilization of clean gradients obtained from multi-frequency component separation involving Planck and WMAP data, and that special lensing maps for galaxy cross-correlations can be prepared with only a small penalty in signal-to-noise while requiring no masking, in-painting, modeling, or simulation effort for the tSZ bias. While we focus on cross-correlations, we also show that gradient cleaning can mitigate biases to the CMB lensing autospectrum that arise from the presence of foregrounds in temperature and polarization with minimal loss of signal-to-noise.