Suppressing the thermal SZ-induced variance in CMB-cluster lensing estimators

TL;DR

This paper proposes a method to reduce thermal SZ-induced variance in CMB-cluster lensing estimators by projecting out an SZ template, improving signal-to-noise for massive clusters in upcoming surveys.

Contribution

The authors introduce a template fitting technique to suppress SZ variance in CMB lensing measurements, enhancing accuracy for high-mass clusters.

Findings

Template fitting increases lensing signal-to-noise by 40% for massive clusters.

Residual SZ signals after fitting are uncorrelated with gradient maps, avoiding bias.

Method is effective for upcoming high-sensitivity CMB experiments like CMB-S4.

Abstract

Accurate galaxy cluster mass measurements from the gravitational lensing of the cosmic microwave background temperature maps depend on mitigating potential biases from the cluster's own thermal Sunyaev-Zel'dovich (SZ) effect signal. Quadratic lensing estimators use a pair of maps to extract the lensing signal: a large scale gradient map and a small scale lensing map. The SZ bias can be eliminated by using an SZ-free map in the pair, with the gradient map being favored for signal-to-noise reasons. However, while this approach eliminates the bias, the SZ power in small scale lensing map adds extra variance that can become significant for high mass clusters and low noise surveys. In this work, we propose projecting out an SZ template to reduce the SZ variance. Any residual SZ signal after template fitting is uncorrelated with the SZ-free gradient map, and thus does not bias the mass measurements. For massive clusters above $4\times 10^{14}$ $M_{\odot}$ observed by the upcoming CMB-S4 or Simons Observatory experiments, we find that the template fitting approach would increase the cluster lensing signal-to-noise by a factor of 1.4.