We present a new method for the reconstruction of Sunyaev-Zel\'dovich (SZ) galaxy clusters in future SZ-survey experiments using multiband bolometer cameras such as Olimpo, APEX, or Planck. Our goal is to optimise SZ-Cluster extraction from our observed noisy maps. We wish to emphasize that none of the
algorithms used in the detection chain is tuned on prior knowledge on the SZ-Cluster signal, or other astrophysical sources (Optical Spectrum, Noise Covariance Matrix, or covariance of SZ Cluster wavelet coefficients). First, a blind separation of the different astrophysical components which contribute to the observations is conducted using an Independent Component Analysis (ICA) method. This is a new
application of ICA to multichannel astrophysical data analysis. Then, a recent non linear filtering technique in the wavelet domain, based on multiscale entropy and the False Discovery Rate (FDR) method, is used to detect and reconstruct the galaxy clusters. Finally, we use the Source Extractor software to identify the detected clusters. The proposed method was applied on realistic simulations of observations. Assuming nominal performance for the near future SZ-survey Olimpo, our detection chain recovers 25% of the cluster of mass larger than 10^{14} Solar Mass, with 90% purity. This new method is impressive as it provides comparable results to pierpaoli et al. (2005) in the
high-purity/low completeness region, being however a blind algorithm. |
