论文标题

较低的偏差,较低的噪声CMB镜头,带有前景硬化的估计器

Lower bias, lower noise CMB lensing with foreground-hardened estimators

论文作者

Sailer, Noah, Schaan, Emmanuel, Ferraro, Simone

论文摘要

宇宙微波背景(CMB)温度图中的外层状前景严重限制了标准估计器重建弱透镜潜力的能力。这些前景无法通过多频清洁或掩盖完全解除,如果不正确的话,可能会导致巨大的偏见。对于由多个未簇的点源制成的前景,可以得出和去除源振幅的估计器,从而消除了对镜头重建的任何偏差。我们通过模拟显示,温度下的所有外层状前景都可以通过具有相同曲线的来源来近似,并且一种简单的偏置硬化技术可有效地减少任何偏见,以最低的噪声成本来减少镜头。我们将性能和偏见与其他方法(例如“仅剪切”重建)进行比较,并讨论如何共同删除任何任意数量的前景,每种前景具有任意概况。特别是,对于西蒙斯天文台样实验,前景硬化的估计器使我们能够扩展重建中使用的最大多极,从而超过了标准的二次估计器$ \ sim 50 \%$,无论是在汽车和交叉上方的标准二次估计器。我们得出的结论是,源硬化在自动和互相关方面的标准镜头二次估计器以及镜头信噪比和前景偏置方面都超过了标准的镜头二次估计器。

Extragalactic foregrounds in temperature maps of the Cosmic Microwave Background (CMB) severely limit the ability of standard estimators to reconstruct the weak lensing potential. These foregrounds are not fully removable by multi-frequency cleaning or masking and can lead to large biases if not properly accounted for. For foregrounds made of a number of unclustered point sources, an estimator for the source amplitude can be derived and deprojected, removing any bias to the lensing reconstruction. We show with simulations that all of the extragalactic foregrounds in temperature can be approximated by a collection of sources with identical profiles, and that a simple bias hardening technique is effective at reducing any bias to lensing, at a minimal noise cost. We compare the performance and bias to other methods such as "shear-only" reconstruction, and discuss how to jointly deproject any arbitrary number of foregrounds, each with an arbitrary profile. In particular, for a Simons Observatory-like experiment foreground-hardened estimators allow us to extend the maximum multipole used in the reconstruction, increasing the overall statistical power by $\sim 50\%$ over the standard quadratic estimator, both in auto and cross-correlation. We conclude that source hardening outperforms the standard lensing quadratic estimator both in auto and cross-correlation, and in terms of lensing signal-to-noise and foreground bias.

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