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Hauptverfasser: Bianchini, Federico, Beck, Dominic, Wu, W. L. Kimmy, Ahmed, Zeeshan, Belkner, Sebastian, Carron, Julien, Hensley, Brandon S., Pryke, Clement L., Umilta, Caterina
Format: Preprint
Veröffentlicht: 2025
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Online-Zugang:https://arxiv.org/abs/2502.04300
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author Bianchini, Federico
Beck, Dominic
Wu, W. L. Kimmy
Ahmed, Zeeshan
Belkner, Sebastian
Carron, Julien
Hensley, Brandon S.
Pryke, Clement L.
Umilta, Caterina
author_facet Bianchini, Federico
Beck, Dominic
Wu, W. L. Kimmy
Ahmed, Zeeshan
Belkner, Sebastian
Carron, Julien
Hensley, Brandon S.
Pryke, Clement L.
Umilta, Caterina
contents We compare multiple foreground-cleaning pipelines for estimating the tensor-to-scalar ratio, $r$, using simulated maps of the planned CMB-S4 experiment within the context of the South Pole Deep Patch. To evaluate robustness, we analyze bias and uncertainty on $r$ across various foreground suites using map-based simulations. The foreground-cleaning methods include: a parametric maximum likelihood approach applied to auto- and cross-power spectra between frequency maps; a map-based parametric maximum-likelihood method; and a harmonic-space internal linear combination using frequency maps. We summarize the conceptual basis of each method to highlight their similarities and differences. To better probe the impact of foreground residuals, we implement an iterative internal delensing step, leveraging a map-based pipeline to generate a lensing $B$-mode template from the Large Aperture Telescope frequency maps. Our results show that the performance of the three approaches is comparable for simple and intermediate-complexity foregrounds, with $σ(r)$ ranging from 3 to 5 $\times 10^{-4}$. However, biases at the $1-2σ$ level appear when analyzing more complex forms of foreground emission. By extending the baseline pipelines to marginalize over foreground residuals, we demonstrate that contamination can be reduced to within statistical uncertainties, albeit with a pipeline-dependent impact on $σ(r)$, which translates to a detection significance between 2 and 4$σ$ for an input value of $r = 0.003$. These findings suggest varying levels of maturity among the tested pipelines, with the auto- and cross-spectra-based approach demonstrating the best stability and overall performance. Moreover, given the extremely low noise levels, mutual validation of independent foreground-cleaning pipelines is essential to ensure the robustness of any potential detection.
format Preprint
id arxiv_https___arxiv_org_abs_2502_04300
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle CMB-S4: Foreground-Cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves
Bianchini, Federico
Beck, Dominic
Wu, W. L. Kimmy
Ahmed, Zeeshan
Belkner, Sebastian
Carron, Julien
Hensley, Brandon S.
Pryke, Clement L.
Umilta, Caterina
Cosmology and Nongalactic Astrophysics
We compare multiple foreground-cleaning pipelines for estimating the tensor-to-scalar ratio, $r$, using simulated maps of the planned CMB-S4 experiment within the context of the South Pole Deep Patch. To evaluate robustness, we analyze bias and uncertainty on $r$ across various foreground suites using map-based simulations. The foreground-cleaning methods include: a parametric maximum likelihood approach applied to auto- and cross-power spectra between frequency maps; a map-based parametric maximum-likelihood method; and a harmonic-space internal linear combination using frequency maps. We summarize the conceptual basis of each method to highlight their similarities and differences. To better probe the impact of foreground residuals, we implement an iterative internal delensing step, leveraging a map-based pipeline to generate a lensing $B$-mode template from the Large Aperture Telescope frequency maps. Our results show that the performance of the three approaches is comparable for simple and intermediate-complexity foregrounds, with $σ(r)$ ranging from 3 to 5 $\times 10^{-4}$. However, biases at the $1-2σ$ level appear when analyzing more complex forms of foreground emission. By extending the baseline pipelines to marginalize over foreground residuals, we demonstrate that contamination can be reduced to within statistical uncertainties, albeit with a pipeline-dependent impact on $σ(r)$, which translates to a detection significance between 2 and 4$σ$ for an input value of $r = 0.003$. These findings suggest varying levels of maturity among the tested pipelines, with the auto- and cross-spectra-based approach demonstrating the best stability and overall performance. Moreover, given the extremely low noise levels, mutual validation of independent foreground-cleaning pipelines is essential to ensure the robustness of any potential detection.
title CMB-S4: Foreground-Cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves
topic Cosmology and Nongalactic Astrophysics
url https://arxiv.org/abs/2502.04300