An Automated Cluster Finder: The Adaptive Matched Filter

We describe an automated method for detecting clusters of galaxies in imagingand redshift galaxy surveys. The Adaptive Matched Filter (AMF) method utilizesgalaxy positions, magnitudes, and---when available---photometric orspectroscopic redshifts to find clusters and determine their redshift andrichness. The AMF can be applied to most types of galaxy surveys: fromtwo-dimensional (2D) imaging surveys, to multi-band imaging surveys withphotometric redshifts of any accuracy (2.5D), to three-dimensional (3D)redshift surveys. The AMF can also be utilized in the selection of clusters incosmological N-body simulations. The AMF identifies clusters by finding thepeaks in a cluster likelihood map generated by convolving a galaxy survey witha filter based on a model of the cluster and field galaxy distributions. Intests on simulated 2D and 2.5D data with a magnitude limit of r' ~ 23.5,clusters are detected with an accuracy of Delta z ~ 0.02 in redshift and ~10%in richness to z < 0.5. Detecting clusters at higher redshifts is possible withdeeper surveys. In this paper we present the theory behind the AMF and describetest results on synthetic galaxy catalogs.Comment: 32 pages, 12 figures, accepted to Ap