Clusters Hiding Under Millimeter Sources (CHUMS) I: Extreme CHUMS

TL;DR

This paper demonstrates that active galactic nuclei (AGN) contamination significantly affects millimeter-wave galaxy cluster detection via the Sunyaev-Zeldovich effect, and shows methods to mitigate this issue for improved survey accuracy.

Contribution

It introduces a method to subtract AGN emission from millimeter-wave data, improving cluster detection and bias correction in SZ surveys.

Findings

AGN emission can overwhelm SZ signals, causing non-detections.

Subtracting AGN signals from data restores high SNR cluster detections.

AGN variability is low over time, aiding in modeling contamination.

Abstract

Galaxy cluster abundance provides a powerful probe of the $\Lambda$CDM model and enables precise constraints on cosmological parameters. Millimeter-wavelength surveys detect clusters through the Sunyaev-Zeldovich (SZ) effect, and are particularly effective at high redshifts. However, the SZ signal can be significantly contaminated by emission from Active Galactic Nuclei (AGN), particularly AGN within the Central Galaxies (CGs). This contamination reduces the SZ signal strength at the frequencies most accessible from the ground, which reduces detection significances or converts cluster detections to non-detections, thereby diminishing survey completeness and introducing biases in cosmological analyses. In this work, we analyze three clusters that host bright AGN in their CGs using 30 and 90 GHz observations from the Combined Array for Research in Millimeter-wave Astronomy (CARMA). In each case the AGN emission overwhelms the cluster SZ signal, resulting in non-detections in the Atacama Cosmology Telescope (ACT) survey. We present signal to noise ratio (SNR) estimates for the clusters after subtracting the AGN signal from 90 GHz ACT maps using the CARMA measurements, demonstrating high SNR cluster detections once this contaminating emission is removed. Using cluster pressure profiles derived from Chandra X-ray data, we subtract the expected SZ signal from the 150 GHz ACT maps to estimate the flux density of the AGN in that band. Leveraging the time-asynchronous CARMA observations, we also assess temporal variability in the AGN emission, and find low fractional variability for our sample. Finally, we discuss the importance of modeling and mitigating AGN contamination in SZ cluster surveys.