Bias-hardened estimators of patchy screening profiles

Detecting anisotropic screening of the cosmic microwave background (CMB) holds the promise of revealing the distribution of gas in the Universe, characterizing the complex processes of galaxy formation and feedback, and studying the epoch of reionization. Estimators for inhomogeneous screening, including some recently proposed small-scale (stacked) estimators, are quadratic or higher order in the CMB temperature or polarization fields and are therefore subject to contamination from CMB lensing. We review the origin of this lensing bias and show that, when stacking on unWISE galaxies, the expected lensing bias dominates the signal if left unmitigated. Hardening techniques that null the lensing bias have been proposed for standard quadratic estimators, whereas only approximate methods have been proposed for stacked estimators. We review these techniques and apply the former to stacked estimators, presenting several strategies (including the optimal strategy) to null lensing contamination when stacking on any large-scale structure tracer.

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Publication Details

Journal
Physical review. D/Physical review. D.
Published
2025-10-17
DOI
https://doi.org/10.1103/hw1x-n17q
Citations
1
Primary Topic
Financial Risk and Volatility Modeling
Type
article
Field-Weighted Citation Impact
2.21
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article

Bias-hardened estimators of patchy screening profiles

Noah Sailer, Simone Ferraro, Boryana Hadzhiyska
1 citations
Physical review. D/Physical review. D.
Financial Risk and Volatility Modeling
2.21
article

Bias-hardened estimators of patchy screening profiles

Noah Sailer, Simone Ferraro, Boryana Hadzhiyska
article en
1 citations

Abstract

Detecting anisotropic screening of the cosmic microwave background (CMB) holds the promise of revealing the distribution of gas in the Universe, characterizing the complex processes of galaxy formation and feedback, and studying the epoch of reionization. Estimators for inhomogeneous screening, including some recently proposed small-scale (stacked) estimators, are quadratic or higher order in the CMB temperature or polarization fields and are therefore subject to contamination from CMB lensing. We review the origin of this lensing bias and show that, when stacking on unWISE galaxies, the expected lensing bias dominates the signal if left unmitigated. Hardening techniques that null the lensing bias have been proposed for standard quadratic estimators, whereas only approximate methods have been proposed for stacked estimators. We review these techniques and apply the former to stacked estimators, presenting several strategies (including the optimal strategy) to null lensing contamination when stacking on any large-scale structure tracer.

Physical review. D/Physical review. D.Vol. 112(8)
Lawrence Berkeley National Laboratory (US), University of California System (US)
Openalex Percentile: Top 10%
Financial Risk and Volatility Modeling
2.21
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