https://doi.org/10.1140/epjc/s10052-025-14386-5
Regular Article - Experimental Physics
Delensing for precision cosmology: optimizing future CMB B-mode surveys to constrain r
1
Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, 100049, Beijing, People’s Republic of China
2
University of Chinese Academy of Sciences, 100049, Beijing, People’s Republic of China
a
liuy92@ihep.ac.cn
b
hongli@ihep.ac.cn
Received:
6
March
2025
Accepted:
22
May
2025
Published online:
26
June
2025
The detection of primordial B-modes, a key probe of cosmic inflation, is increasingly challenged by contamination from weak gravitational lensing B-modes induced by large-scale structure (LSS). We present a delensing pipeline designed to enhance the sensitivity to the inflationary parameter r, minimizing reliance on foreground mitigation during lensing reconstruction. Using simulations of Simons Observatory-like CMB observations and Euclid-like LSS surveys in the Northern hemisphere, we demonstrate that excluding low-
modes (
) effectively mitigates foreground biases, enabling robust lensing potential reconstruction using observed CMB polarization maps. We reconstruct the lensing potential with a minimum-variance (MV) quadratic estimator (QE) applied to CMB polarization data and combine this with external LSS tracers to improve delensing efficiency. Two complementary methods – the gradient-order template and the Inverse-lensing approach – are used to generate lensing B-mode templates, which are cross-correlated with observed B-modes. This achieves a 40% reduction in the uncertainty of r with CMB-only reconstruction, improving to 60% when incorporating external LSS tracers. We validate our results using both the Hamimeche and Lewis likelihood and a Gaussian approximation, finding consistent constraints on r. Our work establishes a streamlined framework for ground-based CMB experiments, demonstrating that synergies with LSS surveys significantly enhance sensitivity to primordial gravitational waves.
© The Author(s) 2025
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Funded by SCOAP3.
