Catalog extraction in SZ cluster surveys : a matched filter approach

By J. Melin, J. Bartlett, Jacques Delabrouille. 2006

205 citations recorded by the source corpus.

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.

Subfields: Astronomy and Astrophysics, Instrumentation

View Paper: https://www.semanticscholar.org/paper/7dc17a0408d969059c090f0f7ebcbb4c72e450a6

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Citations in the corpus

The SPTpol Extended Cluster Survey (2019, methodology): “…at the two channels measured by the SPTpolreceiver; for a nonrelativistic thermal SZ spectrum the effective band centers are 95.9 and 148.5GHz.88 To identify candidate galaxy clusters, we use a spatialspectral filter designed to optimally extract thermal SZ cluster signals (Melin et al. 2006).”
GALAXY CLUSTERS DISCOVERED VIA THE SUNYAEV–ZEL’DOVICH EFFECT IN THE FIRST 720 SQUARE DEGREES OF THE SOUTH POLE TELESCOPE SURVEY (2012, background): “Under certain assumptions about the noise, the astrophysical contaminants, and the source profile, it can be shown (e.g., Melin et al. 2006) that the optimal way to extract a cluster-shaped tSZ signal from our data is to construct a simultaneous spatial-spectral filter, given by ψ(kx, ky, νi) = σ…”
GALAXY CLUSTERS DISCOVERED WITH A SUNYAEV–ZEL'DOVICH EFFECT SURVEY (2008, methodology): “We enhance the signal to noise in the SPT maps for sources with morphologies similar to that expected for SZ galaxy clusters through the application of matched spatial filters (Haehnelt & Tegmark 1996; Herranz et al. 2002a,b; Melin et al. 2006).”
Component separation methods for the PLANCK mission (2008, methodology): “The first one uses a single frequency matched filter (Melin et al. 2006) to extract clusters from the needlet-ILC map.”
Planck 2013 results. XX. Cosmology from Sunyaev-Zeldovich cluster counts (2013, methodology): “The noise estimate σY500 (θ500, l, b) is a by-product of the detection algorithm and can be written in the form (see e.g., Melin et al. 2006) σY500 (θ500, l, b) = [∫ d2k Ftθ500 (k) · P −1(k, l, b) · Fθ500 (k) ]−1/2 , (12) with Fθ500 (k) being a vector of dimension Nfreq (the six highest Planck…”
CMB-S4 Science Case, Reference Design, and Project Plan (2019, methodology): “The standard practice for extracting SZ clusters from multifrequency millimeter-wave maps is through the application of a Fourier-domain spatialspectral filter [558].”
GALAXY CLUSTERS DISCOVERED VIA THE SUNYAEV–ZEL'DOVICH EFFECT IN THE 2500-SQUARE-DEGREE SPT-SZ SURVEY (2014, methodology): “Given the known spatial and spectral characteristics of galaxy clusters as well as the sources of noise in the maps, we construct a filter designed to maximize our sensitivity to galaxy clusters (Melin et al. 2006).”
X-RAY PROPERTIES OF THE FIRST SUNYAEV–ZEL'DOVICH EFFECT SELECTED GALAXY CLUSTER SAMPLE FROM THE SOUTH POLE TELESCOPE (2010, methodology): “Cluster candidates were identified in the SPT maps by using a matched spatial filter technique (Haehnelt & Tegmark 1996; Melin et al. 2006).”
The MCXC: a meta-catalogue of x-ray detected clusters of galaxies (2010, background): “The X-ray properties allow a better characterisation of the SZ signal (e.g., Melin et al. 2006; Andersson et al. 2010) and yield the calibration of the scaling relations needed for cosmological studies with SZ-selected cluster samples (e.g., Majumdar & Mohr 2003).”
Scaling relations for galaxy clusters in the Millennium-XXL simulation (2012, methodology): “Matched filters are often applied to data in order to maximise the signal-to-noise ratio of, for instance, weak lensing or tSZ detections (e.g. Schneider 1996; Melin et al. 2006; Rozo et al. 2011).”
COSMOLOGICAL CONSTRAINTS FROM SUNYAEV–ZEL'DOVICH-SELECTED CLUSTERS WITH X-RAY OBSERVATIONS IN THE FIRST 178 deg2 OF THE SOUTH POLE TELESCOPE SURVEY (2011, methodology): “As discussed in V10 and Melin et al. (2006), primary CMB temperature anisotropies provide a source of astrophysical confusion that add significant uncertainty in determining the integrated Comptonization, YSZ, for a given cluster.”
Cluster Cosmology Constraints from the 2500 deg2 SPT-SZ Survey: Inclusion of Weak Gravitational Lensing Data from Magellan and the Hubble Space Telescope (2018, methodology): “Galaxy clusters are extracted using a multiscale matched-filter approach (Melin et al. 2006) applied to the multiband data as described in Williamson et al. (2011) and Reichardt et al. (2013).”
THE ATACAMA COSMOLOGY TELESCOPE: COSMOLOGY FROM GALAXY CLUSTERS DETECTED VIA THE SUNYAEV–ZEL'DOVICH EFFECT (2010, unknown): “We adopt a matched filter of the form ψ(k) = [ 1 (2π )2 ∫ |τ (k′)|2 P (k′) d2k′ ]−1 τ (k) P (k) (3) following Haehnelt & Tegmark (1996), Herranz et al. (2002a, 2002b), and Melin et al. (2006).”
THE ATACAMA COSMOLOGY TELESCOPE: SUNYAEV–ZEL'DOVICH-SELECTED GALAXY CLUSTERS AT 148 GHz IN THE 2008 SURVEY (2010, methodology): “This confusion for singlefrequency data was observed by Melin et al. (2006) as well as Vanderlinde et al. (2010).”
The Atacama Cosmology Telescope: A Catalog of >4000 Sunyaev–Zel’dovich Galaxy Clusters (2020, methodology): “We search for clusters using a multifrequency matched filter (e.g., Melin et al. 2006; Williamson et al. 2011), applied to the 98 and 150 GHz maps, åy n n n= -Nk k A k k f S k k, , , , , .”
The Simons Observatory: science goals and forecasts (2018, methodology): “…use are described in Madhavacheril et al. (2017), which include a matched filter technique that exploits the unique spectral shape of the tSZ signal (Herranz et al. 2002; Melin et al. 2006) and empirical calibrations of the tSZ signal-to-mass relations via optical weak lensing and CMB halo lensing.”