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CMB lensing reconstruction using cut sky polarization maps and pure-$B$ modes

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arxiv 1403.3911 v2 pith:6WIJ3G74 submitted 2014-03-16 astro-ph.CO

classification astro-ph.CO
keywords lensingestimatorsmodespolarizationreconstructionpure-reduceresolution
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abstract

Detailed measurements of the CMB lensing signal are an important scientific goal of ongoing ground-based CMB polarization experiments, which are mapping the CMB at high resolution over small patches of the sky. In this work we simulate CMB polarization lensing reconstruction for the $EE$ and $EB$ quadratic estimators with current-generation noise levels and resolution, and show that without boundary effects the known and expected zeroth and first order $N^{(0)}$ and $N^{(1)}$ biases provide an adequate model for non-signal contributions to the lensing power spectrum estimators. Small sky areas present a number of additional challenges for polarization lensing reconstruction, including leakage of $E$ modes into $B$ modes. We show how simple windowed estimators using filtered pure-$B$ modes can greatly reduce the mask-induced mean-field lensing signal and reduce variance in the estimators. This provides a simple method (used with recent observations) that gives an alternative to more optimal but expensive inverse-variance filtering.

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Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Impact of Galactic non-Gaussian foregrounds on CMB lensing measurements

    astro-ph.CO 2025-05 conditional novelty 6.0 of 10

    Galactic dust bias on CMB lensing amplitude is below 0.3σ for ACT but can exceed 0.3σ for Simons Observatory with wide masks, depending on the dust model.

  2. Optimal filtering for CMB lensing reconstruction

    astro-ph.CO 2019-09 accept novelty 6.0 of 10

    Optimal anisotropic CMB filtering plus a second-stage filter on the reconstructed lensing convergence map reduces lensing power spectrum variance by factor 2-5 relative to isotropic filtering, with up to 30% additiona...

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