Statistics – Computation
Scientific paper
Dec 2002
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2002spie.4844..225c&link_type=abstract
Observatory Operations to Optimize Scientific Return III. Edited by Quinn, Peter J. Proceedings of the SPIE, Volume 4844, pp
Statistics
Computation
Scientific paper
In the coming decade we will build on the foundations of current large scale imaging surveys such as the SDSS, 2MASS and MACHO to develop deep, wide-field imaging surveys covering over 15,000 square degrees that are designed to probe to the time domain. One such project is the Large Synoptic Survey Telescope (LSST). We describe here some of the data management challenges we face in moving from the current generation of surveys to an imaging program of the size of the LSST. Scaling from todays deep CCD imaging surveys and wide-field photometric surveys we show that the computational challenge of analyzing the data from a three Gigapixel camera with 10s integrations should be manageable on the time frame that the LSST is expected to be delivered. While encouraging, these hardware considerations are only a very small aspect of the software engineering and data management procedures that must be developed in order for the LSST to succeed.
Boroson Todd A.
Connolly Andrew
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