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Title: Optimal multifrequency weighting for CMB lensing

Abstract

We report that extragalactic foregrounds in cosmic microwave background (CMB) temperature maps lead to significant biases in CMB lensing reconstruction if not properly accounted for. Combinations of multifrequency data have been used to minimize the overall map variance (internal linear combination, or ILC), or specifically null a given foreground, but these are not tailored to CMB lensing. In this paper, we derive an optimal multifrequency combination to jointly minimize CMB lensing noise and bias. We focus on the standard lensing quadratic estimator, as well as the "shear-only"and source-hardened estimators, whose responses to foregrounds differ. We show that an optimal multifrequency combination is a compromise between the ILC and joint deprojection, which nulls the thermal Sunyaev-Zel'dovich (tSZ) and cosmic infrared background (CIB) contributions. In particular, for a Simons Observatory-like experiment with ℓmax,T=3000, we find that profile hardening alone (with the standard ILC) reduces the bias to the lensing power amplitude by 40%, at a 20% cost in noise, while the bias to the cross-correlation with a LSST-like sample is reduced by nearly an order of magnitude at a 10% noise cost, relative to the standard quadratic estimator. With a small amount of joint deprojection the bias to the profile hardened estimatormore » can be further reduced to less than half the statistical uncertainty on the respective amplitudes, at a 20% and 5% noise cost for the auto- and cross-correlation respectively, relative to the profile hardened estimator with the standard ILC weights. Finally, we explore possible improvements with more aggressive masking and varying ℓmax,T.« less

Authors:
ORCiD logo [1]; ORCiD logo [1];  [1]; ORCiD logo [2];  [3]
  1. Univ. of California, Berkeley, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Univ. of Cambridge (United Kingdom)
  3. Univ. of Cambridge (United Kingdom); Kavli Institute for Cosmology Cambridge (United Kingdom)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP); National Science Foundation (NSF)
OSTI Identifier:
1861401
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Physical Review. D.
Additional Journal Information:
Journal Volume: 104; Journal Issue: 12; Journal ID: ISSN 2470-0010
Publisher:
American Physical Society (APS)
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; cosmic microwave background; astrophysical simulations; cosmological simulations

Citation Formats

Sailer, Noah, Schaan, Emmanuel, Ferraro, Simone, Darwish, Omar, and Sherwin, Blake. Optimal multifrequency weighting for CMB lensing. United States: N. p., 2021. Web. doi:10.1103/physrevd.104.123514.
Sailer, Noah, Schaan, Emmanuel, Ferraro, Simone, Darwish, Omar, & Sherwin, Blake. Optimal multifrequency weighting for CMB lensing. United States. https://doi.org/10.1103/physrevd.104.123514
Sailer, Noah, Schaan, Emmanuel, Ferraro, Simone, Darwish, Omar, and Sherwin, Blake. Mon . "Optimal multifrequency weighting for CMB lensing". United States. https://doi.org/10.1103/physrevd.104.123514. https://www.osti.gov/servlets/purl/1861401.
@article{osti_1861401,
title = {Optimal multifrequency weighting for CMB lensing},
author = {Sailer, Noah and Schaan, Emmanuel and Ferraro, Simone and Darwish, Omar and Sherwin, Blake},
abstractNote = {We report that extragalactic foregrounds in cosmic microwave background (CMB) temperature maps lead to significant biases in CMB lensing reconstruction if not properly accounted for. Combinations of multifrequency data have been used to minimize the overall map variance (internal linear combination, or ILC), or specifically null a given foreground, but these are not tailored to CMB lensing. In this paper, we derive an optimal multifrequency combination to jointly minimize CMB lensing noise and bias. We focus on the standard lensing quadratic estimator, as well as the "shear-only"and source-hardened estimators, whose responses to foregrounds differ. We show that an optimal multifrequency combination is a compromise between the ILC and joint deprojection, which nulls the thermal Sunyaev-Zel'dovich (tSZ) and cosmic infrared background (CIB) contributions. In particular, for a Simons Observatory-like experiment with ℓmax,T=3000, we find that profile hardening alone (with the standard ILC) reduces the bias to the lensing power amplitude by 40%, at a 20% cost in noise, while the bias to the cross-correlation with a LSST-like sample is reduced by nearly an order of magnitude at a 10% noise cost, relative to the standard quadratic estimator. With a small amount of joint deprojection the bias to the profile hardened estimator can be further reduced to less than half the statistical uncertainty on the respective amplitudes, at a 20% and 5% noise cost for the auto- and cross-correlation respectively, relative to the profile hardened estimator with the standard ILC weights. Finally, we explore possible improvements with more aggressive masking and varying ℓmax,T.},
doi = {10.1103/physrevd.104.123514},
journal = {Physical Review. D.},
number = 12,
volume = 104,
place = {United States},
year = {Mon Dec 06 00:00:00 EST 2021},
month = {Mon Dec 06 00:00:00 EST 2021}
}

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