A Bayesian Galaxy Cluster Finder and its Application to DLS and CARS

Details A Bayesian Galaxy Cluster Finder and its Application to DLS and CARS A Bayesian Galaxy Cluster Finder and its Application to DLS and CARS

Jan 2010

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010aas...21543607a&link_type=abstract

American Astronomical Society, AAS Meeting #215, #436.07; Bulletin of the American Astronomical Society, Vol. 42, p.385

Astronomy and Astrophysics

Astronomy

Scientific paper

We present the first sample of optical-selected galaxy clusters in Deep Lens Survey (DLS). A new technique for detecting clusters has been designed basing on a bayesian approach of the Matched Filter Algorithm. The method provides flexibility to determine cluster characteristics such as the redshift or richness through the maximization of a redshift-dependent filter. The sample is complete up to redshift 0.7 and we detect 780 clusters up to redshift 1.1. The algorithm has also been tested on CFHTLS Archive Research Survey data obtaining almost the same detections than they do plus additional clusters that are very probably real. In this work, we present a photometric analysis of the DLS optical cluster sample from local to high resdhift and determine their degree of evolution. Additionally, we compare and discuss the differences between the Weak Lensing and Optical Detections.

Affiliated with

Also associated with

No associations

Rating

A Bayesian Galaxy Cluster Finder and its Application to DLS and CARS does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Bayesian Galaxy Cluster Finder and its Application to DLS and CARS, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Bayesian Galaxy Cluster Finder and its Application to DLS and CARS will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-968594