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Advanced Galaxy Cluster Detection Software
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| The Sloan Digital Sky Survey (SDSS) is one of the first of many NASA sponsored missions to produce a trillion pixel image of the sky. A main objective of the SDSS is to determine the spatial clustering of galaxies in the universe. With the advent of large, high-precision surveys like the SDSS, it is now time to apply advanced algorithms taken from statistics, signal processing and computer science to these data to quantify the degree of clustering seen and thus robustly find clusters of galaxies within these large datasets. Over the past five years, the authors of this proposal have collaborated with statisticians, engineers and computer scientists to test a variety of new algorithms on astronomical data. We now come together to produce -- for the benefit of the community -- a suite of high performance cluster detection software that synthesizes the best of all our experiences.
In addition, we will use this suite of software to produce the definitive galaxy clustering database for the SDSS. This will be achieved as follows: First, we will develop the test bed for our detection code. This will consist of publicly available software for generating simulated data sets with known clustering properties. These simulations are critical for defining the selection function of any cluster survey. Second, we will compare the different detection algorithms that have been developed by the team members. Based on these comparisons, we will select the best combination of detection
algorithms, and implementation techniques, and use these to produce an open source software suite. Finally, we will apply the software we have developed to the SDSS galaxy database and produce a
robust, well-understood and well-parameterized catalog of many thousands of clusters. The broad applicability of this software is critical to its success and should be useful for the Large Synoptic
Survey Telescope, the "Virtual Observatory" and many other NASA missions like 2MASS, GALEX, Chandra. |
Bibliography
| | THE CUT-AND-ENHANCE METHOD: SELECTING CLUSTERS OF GALAXIES FROM THE SLOAN DIGITAL SKY SURVEY COMMISSIONING DATA
Goto et al.; AJ, (2001) 123 pp. 1807
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| DETECTING CLUSTERS OF GALAXIES IN THE SLOAN DIGITAL SKY SURVEY. I. MONTE CARLO COMPARISON OF CLUSTER DETECTION ALGORITHMS
Kim et al.; AJ, (2001) 123 pp. 20
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