Mass Calibration of Optically Selected DES clusters using a Measurement of CMB-Cluster Lensing with SPTpol Data
S. Raghunathan, S. Patil, E. Baxter, B. A. Benson, L. E. Bleem, T. L., Chou, T. M. Crawford, G. P. Holder, T. McClintock, C. L. Reichardt, E. Rozo,, T. N. Varga, T. M. C. Abbott, P. A. R. Ade, S. Allam, A. J. Anderson, J., Annis, J. E. Austermann, S. Avila, J. A. Beall

TL;DR
This paper measures the lensing convergence of DES galaxy clusters using CMB data from SPTpol, employing a novel tSZ-free estimator to calibrate cluster masses with high significance.
Contribution
It introduces a modified quadratic estimator to unbiasedly measure CMB-cluster lensing, enabling precise mass calibration of galaxy clusters.
Findings
Detected lensing at 8.7σ significance for flux-limited sample.
Estimated average cluster masses around 1.3-1.6×10^{14} solar masses.
Systematic uncertainties are smaller than statistical errors, dominated by cluster centroid uncertainties.
Abstract
We use cosmic microwave background (CMB) temperature maps from the 500 deg SPTpol survey to measure the stacked lensing convergence of galaxy clusters from the Dark Energy Survey (DES) Year-3 redMaPPer (RM) cluster catalog. The lensing signal is extracted through a modified quadratic estimator designed to be unbiased by the thermal Sunyaev-Zel{'}dovich (tSZ) effect. The modified estimator uses a tSZ-free map, constructed from the SPTpol 95 and 150 GHz datasets, to estimate the background CMB gradient. For lensing reconstruction, we employ two versions of the RM catalog: a flux-limited sample containing 4003 clusters and a volume-limited sample with 1741 clusters. We detect lensing at a significance of 8.7(6.7) with the flux(volume)-limited sample. By modeling the reconstructed convergence using the Navarro-Frenk-White profile, we find the average lensing masses to…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
