Abstract CMBS4—the nextgeneration groundbased cosmic microwave background (CMB) experiment—is set to significantly advance the sensitivity of CMB measurements and enhance our understanding of the origin and evolution of the universe. Among the science cases pursued with CMBS4, the quest for detecting primordial gravitational waves is a central driver of the experimental design. This work details the development of a forecasting framework that includes a powerspectrumbased semianalytic projection tool, targeted explicitly toward optimizing constraints on the tensortoscalar ratio, r , in the presence of Galactic foregrounds and gravitational lensing of the CMB. This framework is unique in its direct use ofmore »
This content will become publicly available on December 1, 2022
Optimal Cosmic Microwave Background Lensing Reconstruction and Parameter Estimation with SPTpol Data
Abstract We perform the first simultaneous Bayesian parameter inference and optimal reconstruction of the gravitational lensing of the cosmic microwave background (CMB), using 100 deg 2 of polarization observations from the SPTpol receiver on the South Pole Telescope. These data reach noise levels as low as 5.8 μ K arcmin in polarization, which are low enough that the typically used quadratic estimator (QE) technique for analyzing CMB lensing is significantly suboptimal. Conversely, the Bayesian procedure extracts all lensing information from the data and is optimal at any noise level. We infer the amplitude of the gravitational lensing potential to be A ϕ = 0.949 ± 0.122 using the Bayesian pipeline, consistent with our QE pipeline result, but with 17% smaller error bars. The Bayesian analysis also provides a simple way to account for systematic uncertainties, performing a similar job as frequentist “bias hardening” or linear bias correction, and reducing the systematic uncertainty on A ϕ due to polarization calibration from almost half of the statistical error to effectively zero. Finally, we jointly constrain A ϕ along with A L , the amplitude of lensinglike effects on the CMB power spectra, demonstrating that the Bayesian method can be used to easily more »
 Authors:
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 Publication Date:
 NSFPAR ID:
 10323320
 Journal Name:
 The Astrophysical Journal
 Volume:
 922
 Issue:
 2
 ISSN:
 0004637X
 Sponsoring Org:
 National Science Foundation
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