"A Bayesian Galaxy Cluster Finder and its Application to Large Surveys"

Conferenciant: Dra. Begoña Ascaso
Lloc de procedència del conferenciant: University of California, Davis
Organitzador: Dept.d' Astronomia i Meteorologia
e-mail de contacte: eduardarrobaam.ub.es (Eduard Salvador)
Data: Dijous, 23 de desembre de 2010
Hora: 12:00
Lloc: Sala de Seminaris, Planta 7

Resum: I will present a new technique for detecting galaxy clusters
based on the Matched Filter Algorithm from a Bayesian point of
view. The method is able to determine the position, redshift and
richness of the cluster through the maximization of a filter depending
on galaxy luminosity, density and photometric redshift combined with a
galaxy cluster prior. I will introduce the simulations that we
performed to test the algorithm through realistic mock galaxy catalogs
and discuss their completeness and purity in terms of mass and
redshift of the cluster. In addition, I will show the results of
testing this algorithm in the CFHTLS Archive Research Survey (CARS)
data, where we recovered similar detections as previous works by using
the same or deeper data plus additional clusters that look
real. Finally, I will display the results of applying this algorithm
to the Deep Lens Survey (DLS) for the first time. I will compare the
results with already available Weak Lensing detections in the same
survey and go through their applications to obtain reliable
mass-to-light ratios and study the large scale structure.