Extracting clusters and determining the selection function for SZ surveys Jean-Baptiste Melin U.C. Davis J. Bartlett J. Delabrouille APC – College de France

Contents I. Theoretical selection function of SZ cluster surveys II. Fast SZ extraction algorithm III. Selection function results

Contents I. Theoretical selection function of SZ cluster surveys II. Fast SZ extraction algorithm III. Selection function results

The selection function ? Contamination Completeness (c,Y)= Number of false detections Total number of detections (recovered clusters + false detections) (c,Y)= Number of recovered clusters True number of clusters If you don’t know  and y, don’t expect to do science !

Matched filters (1/2) AMPLITUDE ? c NORMALIZED TEMPLATE NOISE Haehnelt & Tegmark 96 Herranz et al. 2002a, 2002b AMPLITUDE ? c c=2 arcmin CMB CMB+beam Instrumental noise NORMALIZED TEMPLATE NOISE

Matched filters (2/2)  in Fourier space  in real space Aest linear estimator unbiased <Aest-A>=0 minimize the variance =<(Aest-A)2>  in Fourier space  in real space [arbitrary unit] [arbitrary unit] Aest (S/N)est= Aest/ single-frequency & multi-frequency

Y = Aest Tc > 5 .  . Tc AMI-like : =15GHz, beam=2arcmin inst. noise=5µK/beam, pt. sources : S<100Jy Aest/>5 Y = Aest Tc > 5 .  . Tc

Contents I. Theoretical selection function of SZ cluster surveys II. Fast SZ extraction algorithm III. Selection function results

Cluster extraction in 3 steps Simulations 3º 3º 15 GHz 30 GHz 90 GHz pix=30’’ Primary CMB anisotropies Instrumental beam (fwhm=2 arcmin) Insrumental white noise (DT=20 K/pix) Radio sources (S<0.1mJy at 15 GHZ) Multifrequency (n=15, 30, 90 GHz) Cosmology : LCDM

Cluster extraction Filtered map sample Step 1 … … c(filter)=3.0 arcmin c(filter)=0.1 arcmin c(filter)=1.6 arcmin

Cluster extraction Cluster candidates Step 2 S/Nthreshold = 3, 5, … S/Ncarte> S/Nthreshold … … c(filter)=3.0 arcmin c(filter)=0.1 arcmin c(filter)=1.6 arcmin

Cluster extraction c and Y recovery Step 3 c given by the node having the highest S/N in a given branch Y derived from the filtered map at scale c c=3.0 arcmin . c=0.3 arcmin c=0.2 arcmin c=0.1 arcmin

Contents I. Theoretical selection function of SZ cluster surveys II. Fast SZ extraction algorithm III. Selection function results

Single frequency – 15 GHz 50 simulations (3 deg × 3 deg each) Cl perfectly known simulations detection theoretical selection fit CBI excess simulations detection theoretical selection fit

Single frequency – 15 GHz Cluster counts Clusters with Y>5.10-5arcmin2

Single frequency – 15 GHz Cosmological parameters BIAS !

Conclusions Multi-frequency/Single-frequency Selection function non-trivial depends on instrument, observation strategy, confusion, cluster physics & data pipeline Bias Additional source of error ‘Survey calibration’ &

The method A Monte Carlo triangle Fast SZ simulation tool Fast SZ detection tool Input catalog Output catalog Comparison Selection function

Single frequency – 15 GHz A non-trivial selection function Clusters with Y>5.10-5arcmin2 Y>10-4arcmin2 Y>3.10-4arcmin2

Single frequency – 15 GHz Theoretical selection curves détecté detected non détecté not detected