The MaxBCG algorithm finds galaxy clusters in the Sloan Digital Sky Survey (SDSS)
It searches for galaxy clusters over a wide range of redshifts and masses. The
search relies on the fact that the brightest cluster galaxies (BCG) in most clusters
have remarkably similar luminosities and colors. The MaxBCG algorithm works on a
5-dimensional space and calculates the cluster likelihood of each galaxy. The 5-space
is defined by two spatial dimensions, Right Ascension, and Declination; two color
dimensions, g-r and r-i; and one brightness dimension, i.
The algorithm includes six steps:
Get galaxy list extracts the five-dimensions of interest from the catalog.
Filter calculates the unweighted BCG likelihood for each galaxy
(unweighted by galaxy count) and discards unlikely galaxies.
Check neighbors weights the BCG likelihood with the number of neighbors.
Pick most likely for each galaxy, determines whether it is the most
likely galaxy in the neighborhood to be the center of the cluster.
Discard compromised results removes suspicious results and stores the
final cluster catalog.
Retrieve the members of the clusters retrieves the galaxies that the
MaxBCG algorithm determined are part of the cluster.
We have coded a SQL version (text or Word) of this algorithm that you can try using
CasJobs or MySkyServer. This code requires a K-Correction table.
For more information you can read the paper "When Database Systems Meet the Grid"
in proceedings of The 2nd Biennial Conference on Innovative Data Systems Research,
January 4-7, Asilonmar, CA, US, 2005.
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