Statistics – Computation
Scientific paper
Jan 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011aas...21712206j&link_type=abstract
American Astronomical Society, AAS Meeting #217, #122.06; Bulletin of the American Astronomical Society, Vol. 43, 2011
Statistics
Computation
Scientific paper
LSST will generate 100 petabytes of images and 20 petabytes of catalogs, covering 18,000-20,000 square degrees of area sampled every few days, throughout a total of ten years of time -- all publicly available and exquisitely calibrated.
The primary access to this data will be through Data Access Centers (DACs). DACs will provide access to catalogs of sources (single detections from individual images) and objects (associations of sources from multiple images). Simple user interfaces or direct SQL queries at the DAC can return user-specified portions of data from catalogs or images. More complex manipulations of the data, such as calculating multi-point correlation functions or creating alternative photo-z measurements on terabyte-scale data, can be completed with the DAC's own resources. Even more data-intensive computations requiring access to large numbers of image pixels on petabyte-scale could also be conducted at the DAC, using compute resources allocated in a similar manner to a TAC. DAC resources will be available to all individuals in member countries or institutes and LSST science collaborations. DACs will also assist investigators with requests for allocations at national facilities such as the Petascale Computing Facility, TeraGrid, and Open Science Grid.
Using data on this scale requires new approaches to accessibility and analysis which are being developed through interactions with the LSST Science Collaborations. We are producing simulated images (as might be acquired by LSST) based on models of the universe and generating catalogs from these images (as well as from the base model) using the LSST data management framework in a series of data challenges. The resulting images and catalogs are being made available to the science collaborations to verify the algorithms and develop user interfaces.
All LSST software is open source and available online, including preliminary catalog formats. We encourage feedback from the community.
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