Mitigating Nonlinear Systematics in Weak Lensing Surveys: The Bernardeau-Nishimichi-Taruya Approach
Shiming Gu, Ludovic van Waerbeke, Francis Bernardeau, Roohi Dalal

TL;DR
This paper introduces the BNT transform and an $ ext{ell}$-cut method to better handle nonlinear scale biases in weak lensing surveys, improving the accuracy of cosmological parameter estimation.
Contribution
It proposes the BNT transform combined with an $ ext{ell}$-cut to reduce scale leakage from nonlinear biases, enhancing the reliability of weak lensing analyses.
Findings
BNT transform reduces scale leakage effects.
The $ ext{ell}$-cut method effectively controls nonlinear bias influence.
BNT outperforms traditional approaches in preserving cosmological constraints.
Abstract
Weak lensing surveys, along with most other late-Universe probes, have consistently measured a lower amplitude of the matter fluctuation spectrum, denoted by the parameter , compared to predictions from early-Universe measurements in cosmic microwave background data. Improper modelling of nonlinear scales may partially explain these discrepancies in lensing surveys. This study investigates whether the conventional approach to addressing small-scale biases remains optimal for Stage-IV lensing surveys. We demonstrate that conventional weak lensing estimators are affected by scale leakage from theoretical biases at nonlinear scales, which influence all observed scales. Using the BNT transform, we propose an -cut methodology that effectively controls this leakage. The Bernardeau-Nishimichi-Taruya (BNT) transform reorganises weak lensing data in space, aligning it with …
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