Papers › An Inpainting Approach to Tackle the Kinematic and Thermal SZ Induced Biases in...
An Inpainting Approach to Tackle the Kinematic and Thermal SZ Induced Biases in CMB-Cluster Lensing Estimators
Srinivasan Raghunathan, Gilbert P. Holder, James G. Bartlett, SanjayKumar Patil, Christian L. Reichardt, Nathan Whitehorn
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
A galaxy cluster's own Sunyaev-Zel{'}dovich (SZ) signal is known to be a major contaminant when reconstructing the cluster's underlying lensing potential using cosmic microwave background (CMB) temperature maps. In this work, we develop a modified quadratic estimator (QE) that is designed to mitigate the lensing biases due to the kinematic and thermal SZ effects. The idea behind the approach is to use inpainting to eliminate the cluster's own emission from the large-scale CMB gradient map. In this inpainted gradient map, we fill the pixel values at the cluster location using a constrained Gaussian realization based on the information from surrounding regions. We show that the noise induced due to inpainting process is small compared to other noise sources for upcoming surveys and has minimal impact on the final lensing signal-to-noise. Without any foreground cleaning, we find a stacked mass uncertainty of 6.5% for the CMB-S4 experiment on a cluster sample containing 5000 clusters with M_(200c) = 2 ×10¹⁴ M_⊙ at z = 0.7. In addition to the SZ-induced lensing biases, we also quantify the low mass bias arising due to the contamination of the CMB gradient by the cluster convergence. For the fiducial cluster sample considered in this work, we find that bias is negligible compared to the statistical uncertainties for both the standard and the modified QE even when modes up to ∼2700 are used for the gradient estimation. With more gradient modes, we demonstrate that the sensitivity can be increased by 14% compared to the fiducial result above with gradient modes up to 2000
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections