Computer Science – Performance
Scientific paper
Jun 2006
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006aas...208.6202b&link_type=abstract
American Astronomical Society Meeting 208, #62.02; Bulletin of the American Astronomical Society, Vol. 38, p.142
Computer Science
Performance
Scientific paper
The Dark Energy Survey (DES) is a 5-year (2009-2014), multi-institutional endeavor to image 5000 deg2 in g, r, i, and z filters using a new 3 deg2 imager for the CTIO Blanco 4-m telescope. The primary goal of the DES is to precisely constrain the dark energy equation of state parameter and its variation with redshift using four complementary techniques: 1) galaxy cluster survey (4000 deg2 overlap with the South Pole Telescope Sunyaev-Zel’dovich Effect survey), 2) galaxy angular power spectrum, 3) weak lensing cosmic shear, and 4) supernovae Ia distances. The DES will produce 1 Petabyte of data: raw and reduced images, co-added tiles, and a 100 Terabyte catalog database. Nightly observations will flow over the network from Chile to the main DES archive center at NCSA. The data volume requires a highly automated processing pipeline with robust quality assurance. We have designed and are developing a data management system that is grid-computing enabled. The system includes a flexible and scaleable pipeline processing and data access framework built from middleware developed at NCSA for the broader grid computing community. Another central component is a DES catalog database that is fully integrated with the automated pipelines. In addition, we plan to employ an image data archive tool being developed by the NOAO Data Products Program. Data processing and archiving will be carried out on the high performance computing infrastructure at NCSA and elsewhere within the DES collaboration. We will provide the pipelines to the public, and we will release the reduced data one year after they are acquired.
Alam Tanweer
Annis James
Barkhouse Wayne
Beldica Cristina
Cai David
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