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Optimizing foreground mitigation for CMB lensing with combined multifrequency and geometric methods

Journal Article · · Physical Review. D.
 [1];  [1];  [2];  [3];  [3]
  1. Univ. of Cambridge (United Kingdom)
  2. Univ. of California, Berkeley, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
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Here, a key challenge for current and upcoming cosmic microwave background lensing measurements is their sensitivity to biases from extragalactic foregrounds, such as Sunyaev-Zel'dovich signals or cosmic infrared background emission. Several methods have been developed to mitigate these lensing foreground biases, dividing broadly into multifrequency cleaning approaches and modifications to the estimator geometry, but how to optimally combine these methods has not yet been explored in detail. In this paper, we examine which combination of lensing foreground mitigation strategies is best able to reduce the impact of foreground contamination for a Simons Observatory-like experiment while preserving maximal signal-to-noise. Although the optimal combination obtained depends on whether bias reduction or variance reduction is prioritized and on whether polarization data is used, generally, we find that combinations involving both geometric (profile hardening, source hardening, or shear) and multifrequency (symmetric cleaning) methods perform best. For lensing power spectrum measurements from temperature (polarization and temperature), our combined estimator methods are able to reduce the bias below σ/4 or 0.3% (0.1%), a factor of 16 (30) lower than the standard quadratic estimator bias, at a modest signal-to-noise cost of only 18% (12%). In contrast, single-method foreground-mitigation approaches struggle to reduce the bias to a negligible level below σ/2 without incurring a large noise penalty. For upcoming and current experiments, our combined methods therefore represent a promising approach for making lensing measurements with negligible foreground bias.
Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); USDOE Office of Science (SC), High Energy Physics (HEP)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1967355
Journal Information:
Physical Review. D., Journal Name: Physical Review. D. Journal Issue: 4 Vol. 107; ISSN 2470-0010
Publisher:
American Physical Society (APS)Copyright Statement
Country of Publication:
United States
Language:
English

References (26)

Planck 2018 results: IV. Diffuse component separation journal September 2020
A full sky, low foreground, high resolution CMB map from WMAP journal November 2008
Mass Reconstruction with Cosmic Microwave Background Polarization journal August 2002
Simulations of the Microwave sky journal January 2010
Cmb Lensing Power Spectrum Biases from Galaxies and Clusters Using High-Angular Resolution Temperature maps journal April 2014
Cluster mass estimators from CMB temperature and polarization lensing journal December 2007
The Atacama Cosmology Telescope: likelihood for small-scale CMB data journal July 2013
Extragalactic foreground contamination in temperature-based CMB lens reconstruction journal March 2014
The Simons Observatory: science goals and forecasts journal February 2019
The Websky extragalactic CMB simulations journal October 2020
The Atacama Cosmology Telescope: a CMB lensing mass map over 2100 square degrees of sky and its cross-correlation with BOSS-CMASS galaxies journal November 2020
Bias-hardened CMB lensing journal February 2013
Atacama Cosmology Telescope: Component-separated maps of CMB temperature and the thermal Sunyaev-Zel’dovich effect journal July 2020
Lower bias, lower noise CMB lensing with foreground-hardened estimators journal September 2020
Partially constrained internal linear combination: A method for low-noise CMB foreground mitigation journal May 2021
Optimal multifrequency weighting for CMB lensing journal December 2021
Detection of gravitational lensing in the cosmic microwave background journal August 2007
CMB lensing constraints on neutrinos and dark energy journal March 2009
Bias to CMB lensing reconstruction from temperature anisotropies due to large-scale galaxy motions journal January 2018
Mitigating foreground biases in CMB lensing reconstruction using cleaned gradients journal July 2018
Dark Energy Survey Year 1 results: Methodology and projections for joint analysis of galaxy clustering, galaxy lensing, and CMB lensing two-point functions journal January 2019
Detection of the Power Spectrum of Cosmic Microwave Background Lensing by the Atacama Cosmology Telescope journal July 2011
Foreground-Immune Cosmic Microwave Background Lensing with Shear-Only Reconstruction journal May 2019
CMB and SZ effect separation with constrained Internal Linear Combinations: CMB and SZ separation with constrained ILC journal November 2010
Filling in cosmic microwave background map missing data using constrained Gaussian realizations: Filling in missing CMB data journal June 2012
CMB/kSZ and Compton-y Maps from 2500 deg2 of SPT-SZ and Planck Survey Data journal February 2022

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Related Subjects

79 ASTRONOMY AND ASTROPHYSICS
Astrophysical & cosmological simulations
Cosmic microwave background