Point Source Confusion in SZ Cluster Surveys

Abstract

We examine the effect of point source confusion on cluster detection in Sunyaev-Zel'dovich (SZ) surveys. A filter matched to the spatial and spectral characteristics of the SZ signal optimally extracts clusters from the astrophysical backgrounds. We calculate the expected confusion (point source and primary cosmic microwave background [CMB]) noise through this filter and quantify its effect on the detection threshold for both single and multiple frequency surveys. Extrapolating current radio counts, we estimate that confusion from sources below 100 microJy limits single-frequency surveys to 1-sigma detection thresholds of Y 3.10^{-6} arcmin^2 at 30 GHz and Y 10^{-5} arcmin^2 at 15 GHz (for unresolved clusters in a 2 arcmin beam); these numbers are highly uncertain, and an extrapolation with flatter counts leads to much lower confusion limits. Bolometer surveys must contend with an important population of infrared point sources. We find that a three-band matched filter with 1 arcminute resolution (in each band) efficiently reduces confusion, but does not eliminate it: residual point source and CMB fluctuations contribute significantly the total filter noise. In this light, we find that a 3-band filter with a low-frequency channel (e.g, 90+150+220 GHz) extracts clusters more effectively than one with a high frequency channel (e.g, 150+220+300 GHz).

Accepted for publication in Astronomy & Astrophysics; Updated grant information in acknowledgements

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Cited by in corpus (4)

• Reconstructing mass profiles of simulated galaxy clusters by combining Sunyaev-Zeldovich and X-ray images
• Joint deprojection of Sunyaev-Zeldovich and X-ray images of galaxy clusters
• De-Confusing blended field images using graphs and bayesian priors
• Introducing constrained matched filters for improved separation of point sources from galaxy clusters