CMB-S4: Iterative Internal Delensing and $r$ Constraints
ApJ 964 148 (2024) The tightest constraints on the tensor-to-scalar ratio $r$ can only be obtained after removing a substantial fraction of the lensing $B$-mode sample variance. The planned CMB-S4 experiment will remove the lensing $B$-mode signal internally by reconstructing the gravitational lense...
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Zusammenfassung: | ApJ 964 148 (2024) The tightest constraints on the tensor-to-scalar ratio $r$ can only be
obtained after removing a substantial fraction of the lensing $B$-mode sample
variance. The planned CMB-S4 experiment will remove the lensing $B$-mode signal
internally by reconstructing the gravitational lenses from high-resolution
observations. We document here a first lensing reconstruction pipeline able to
achieve this optimally for arbitrary sky coverage. We make it part of a
map-based framework to test CMB-S4 delensing performance and its constraining
power on $r$, including inhomogeneous noise and two non-Gaussian Galactic
polarized foreground models. The framework performs component-separation of the
high-resolution maps, followed by the construction of lensing $B$-mode
templates, which are then included in a parametric small-aperture maps
cross-spectra-based likelihood for $r$. We find that the lensing reconstruction
and framework achieve the expected performance, compatible with the target
$\sigma(r) \simeq 5\cdot 10^{-4}$ in the absence of a tensor signal, after an
effective removal of $92\%$ to $93\%$ of the lensing $B$-mode variance,
depending on the simulation set. The code for the lensing reconstruction can
also be used for cross-correlation studies with large-scale structures, lensing
spectrum reconstruction, cluster lensing, or other CMB lensing-related
purposes. As part of our tests we also demonstrate joint optimal reconstruction
of the lensing potential with the lensing curl potential mode, second-order in
the density fluctuations. |
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DOI: | 10.48550/arxiv.2310.06729 |