A demonstration of improved constraints on primordial gravitational waves with delensing

A demonstration of improved constraints on primordial gravitational waves with delensing
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通过去透镜改进对原初引力波的约束的演示

DOI:
10.1103/physrevd.103.022004
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发表时间:
2021
期刊:
影响因子:
5
通讯作者:
Bender, A. N.
Bender, A. N.
中科院分区:
物理与天体物理2区
文献类型:
--
作者:
Ade, P. A. R.;Ahmed, Z.;Amiri, M.;Anderson, A. J.;Austermann, J. E.;Avva, J. S.;Barkats, D.;Thakur, R. Basu;Beall, J. A.;Bender, A. N.

文献摘要

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我们提出了对张量-标量比的约束,该约束来自于对宇宙微波背景(CMB)偏振模式的测量,该测量具有“去色散”,即引力透镜模式的样本方差所带来的不确定性通过与透镜模式模板的交叉相关来减小。该模板是通过结合极化CMB的估计和投影大尺度结构的示踪剂来构建的。使用的大尺度结构示踪剂是来自普朗克卫星数据的宇宙红外背景图,而极化CMB图来自南极望远镜,二头/凯克和普朗克数据的组合。我们扩展了二头肌/Kecklikelihood分析框架,以接受透镜模板,并使用与前面分析相同的参数前景建模将其应用于2014年收集的二头肌/Keckdataset。仿真结果表明,与使用完美透镜模板或无透镜模式时相比,该方法的不确定度减小了0.022。将该技术应用于实际数据,约束精度从(95% C.L.)提高到(95% C.L.)。这是通过去密度来改善约束的第一个演示。
We present a constraint on the tensor-to-scalar ratio,, derived from measurements of cosmic microwave background (CMB) polarization-modes with “delensing,” whereby the uncertainty oncontributed by the sample variance of the gravitational lensing-modes is reduced by cross-correlating against a lensing-mode template. This template is constructed by combining an estimate of the polarized CMB with a tracer of the projected large-scale structure. The large-scale-structure tracer used is a map of the cosmic infrared background derived fromPlancksatellite data, while the polarized CMB map comes from a combination of South Pole Telescope,bicep/Keck, andPlanckdata. We expand thebicep/Kecklikelihood analysis framework to accept a lensing template and apply it to thebicep/Keckdataset collected through 2014 using the same parametric foreground modeling as in the previous analysis. From simulations, we find that the uncertainty onis reduced by, fromto 0.022, which can be compared with areduction obtained when using a perfect lensing template or if there were zero lensing-modes. Applying the technique to the real data, the constraint onis improved fromto(95% C.L.). This is the first demonstration of improvement in anconstraint through delensing.