Sharpening the Precision of the Sunyaev-Zel'dovich Power Spectrum

TL;DR

Masking the brightest galaxy clusters in SZ maps reduces non-Gaussian variance, improves the accuracy of power spectrum measurements, and enhances sensitivity to cosmological parameters like _8.

Contribution

The paper introduces a simple masking strategy to reduce variance and Gaussianize SZ power spectrum measurements, improving cosmological parameter sensitivity.

Findings

Masking bright clusters halves variance at certain scales.

Conservative masking improves _8 sensitivity by a factor of two.

Method remains effective with foregrounds and noise.

Abstract

Using both halo model calculations and a large sample of simulated SZ maps, we demonstrate that high-mass clusters add significant non-Gaussian variance to measurements of the SZ power spectrum amplitude. The difficulty in correctly accounting theoretically for the contribution of these objects to the uncertainty in C_l leads to a reduced sensitivity to \sigma_8. We show that a simple solution is to mask out the brightest clusters in the map before measuring the power spectrum. We demonstrate that fairly conservative masking can reduce the variance and Gaussianize the statistics significantly, thus increasing the sensitivity to cosmological parameters. Choosing which objects to mask is non-trivial; we found that using a fixed sky density produced a well-defined and well-behaved estimate that can easily be applied to real maps. For example, masking the 10 (90) brightest clusters in a 100 deg^2 SZ map will improve the sensitivity to C_l by a factor of two at l = 1000 (2000) and 1.5 at l = 2000 (4000). We show that even in the presence of astrophysical foregrounds (primary CMB and point sources) and instrument noise, one can increase the precision on measurements of \sigma_8 by masking up to 0.9 clusters/deg^2.