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Title: Maximum a posteriori CMB lensing reconstruction

Abstract

Gravitational lensing of the CMB is a valuable cosmological signal that correlates to tracers of large-scale structure and acts as a important source of confusion for primordial B-mode polarization. State-of-the-art lensing reconstruction analyses use quadratic estimators, which are easily applicable to data. Yet, these estimators are known to be suboptimal, in particular for polarization, and large improvements are expected to be possible for high signal-to-noise polarization experiments. We develop a method and numerical code, LensIt, that is able to find efficiently the most probable lensing map, introducing no significant approximations to the lensed CMB likelihood, and applicable to beamed and masked data with inhomogeneous noise. It works by iteratively reconstructing the primordial unlensed CMB using a deflection estimate and its inverse, and removing residual lensing from these maps with quadratic estimator techniques. Roughly linear computational cost is maintained due to fast convergence of iterative searches, combined with the local nature of lensing. The technique achieves the maximal improvement in signal to noise expected from analytical considerations on the unmasked parts of the sky. Delensing with this optimal map leads to forecast tensor-to-scalar ratio parameter errors improved by a factor ≃2 compared to the quadratic estimator in a CMB stage IVmore » configuration.« less

Authors:
 [1];  [1]
  1. Univ. of Sussex, Brighton (United Kingdom)
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1544371
Alternate Identifier(s):
OSTI ID: 1390357
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Physical Review D
Additional Journal Information:
Journal Volume: 96; Journal Issue: 6; Journal ID: ISSN 2470-0010
Publisher:
American Physical Society (APS)
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS

Citation Formats

Carron, Julien, and Lewis, Antony. Maximum a posteriori CMB lensing reconstruction. United States: N. p., 2017. Web. doi:10.1103/PhysRevD.96.063510.
Carron, Julien, & Lewis, Antony. Maximum a posteriori CMB lensing reconstruction. United States. doi:10.1103/PhysRevD.96.063510.
Carron, Julien, and Lewis, Antony. Thu . "Maximum a posteriori CMB lensing reconstruction". United States. doi:10.1103/PhysRevD.96.063510. https://www.osti.gov/servlets/purl/1544371.
@article{osti_1544371,
title = {Maximum a posteriori CMB lensing reconstruction},
author = {Carron, Julien and Lewis, Antony},
abstractNote = {Gravitational lensing of the CMB is a valuable cosmological signal that correlates to tracers of large-scale structure and acts as a important source of confusion for primordial B-mode polarization. State-of-the-art lensing reconstruction analyses use quadratic estimators, which are easily applicable to data. Yet, these estimators are known to be suboptimal, in particular for polarization, and large improvements are expected to be possible for high signal-to-noise polarization experiments. We develop a method and numerical code, LensIt, that is able to find efficiently the most probable lensing map, introducing no significant approximations to the lensed CMB likelihood, and applicable to beamed and masked data with inhomogeneous noise. It works by iteratively reconstructing the primordial unlensed CMB using a deflection estimate and its inverse, and removing residual lensing from these maps with quadratic estimator techniques. Roughly linear computational cost is maintained due to fast convergence of iterative searches, combined with the local nature of lensing. The technique achieves the maximal improvement in signal to noise expected from analytical considerations on the unmasked parts of the sky. Delensing with this optimal map leads to forecast tensor-to-scalar ratio parameter errors improved by a factor ≃2 compared to the quadratic estimator in a CMB stage IV configuration.},
doi = {10.1103/PhysRevD.96.063510},
journal = {Physical Review D},
number = 6,
volume = 96,
place = {United States},
year = {2017},
month = {9}
}

Journal Article:
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Figures / Tables:

FIG. 1 FIG. 1: A demonstration of how our Wiener filter produces optimal (maximum a posteriori) estimates on the unlensed CMB maps from masked data. The simulated temperature map is comparable to a Planck configuration, and we use the exact input simulated deflection and exact input unlensedmore » $C$$^{TT}_{ℓ}$ spectrum in the filter. The upper-left panel shows the simulated masked temperature data map, with a homogeneous noise level of 35 $µ$K-arcmin and a beam FWHM of 7-arcmin. The (unapodized) mask is built out of a portion of the public Planck lensing mask, to which we have added a band surrounding the patch on all sides. The upper right panel shows the reconstructed unlensed map $T$WF. The residual to the true input CMB map ($T$WF − $T$ input) is shown on the lower-right panel. The lower-left panel shows the residual (on the unmasked pixels) of the result obtained when the Wiener filter instead uses no deflection but the lensed CMB spectrum in place of the unlensed spectrum (as in the standard quadratic estimator). These residuals are several times larger in magnitude (the same colour scale is sometimes saturated), and display the anisotropic swirly patterns generated by the pure gradient deflection field.« less

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