Catalog extraction in SZ cluster surveys: a matched filter approach

Abstract

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 S /N = 5 (S /N = 3). 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 Y − M 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 Y − M 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.

Covariance matrices for halo number counts and correlation functions

“…Some 1625 massive clusters out to z = 1 are expected over the whole sky. We assume the selection function by Melin et al (2006), shown in middle panel of Fig We show in Fig. 31 the angular number densities per redshift bin.…”

The galaxy clusterYSZ−LXandYSZ−Mrelations from the WMAP 5-yr data

“…Below, we recall the main features of the multifrequency matched filters. More details can be found in Herranz et al (2002) or Melin et al (2006).…”

“…We build a multifrequency matched filter (Herranz et al 2002;Melin et al 2006) based on the known spectral shape of the thermal SZ effect and the shape of the universal pressure profile of Arnaud et al (2010). This profile was derived from REXCESS (Böhringer et al 2007), a sample expressly designed to measure the structural and scaling properties of the local X-ray cluster population by means of an unbiased, representative sampling in luminosity.…”

Planckintermediate results

“…We extracted the SZ signal using multi-frequency matched filters (MMF, Herranz et al 2002;Melin et al 2006), which optimally filter and combine maps to estimate the SZ signal. As input, the MMF requires information on the instrumental beam, the SZ frequency spectrum, and a cluster profile; noise autoand cross-spectra are estimated directly from the data.…”