Catalog extraction in SZ cluster surveys: a matched filter approach
APC, 11 pl. Marcelin Berthelot, 75231 Paris Cedex 05, France (UMR 7164 – CNRS, Université Paris 7, CEA, Observatoire de Paris) e-mail: email@example.com, [bartlett;delabrouille]@apc.univ-paris7.fr
2 Department of Physics, University of California Davis, One Shields Avenue, Davis CA 95616, USA
Accepted: 30 June 2006
We present a method based on matched multifrequency filters for extracting cluster catalogs from Sunyaev-Zel'dovich (SZ) surveys. We evaluate its performance in terms of completeness, contamination rate and photometric recovery for three representative types of SZ survey: a high resolution single frequency radio survey (AMI), a high resolution ground-based multiband survey (SPT), and the Planck all-sky survey. These surveys are not purely flux limited, and they loose completeness significantly before their point-source detection thresholds. Contamination remains relatively low at <5% (less than 30%) for a detection threshold set at (). We identify photometric recovery as an important source of catalog uncertainty: dispersion in recovered flux from multiband surveys is larger than the intrinsic scatter in the relation predicted from hydrodynamical simulations, while photometry in the single frequency survey is seriously compromised by confusion with primary cosmic microwave background anisotropy. The latter effect implies that follow-up observations in other wavebands (e.g., 90 GHz, X-ray) of single frequency surveys will be required. Cluster morphology can cause a bias in the recovered relation, but has little effect on the scatter; the bias would be removed during calibration of the relation. Point source confusion only slightly decreases multiband survey completeness; single frequency survey completeness could be significantly reduced by radio point source confusion, but this remains highly uncertain because we do not know the radio counts at the relevant flux levels.
Key words: large-scale structure of Universe / galaxies: clusters: general / methods: data analysis
© ESO, 2006