Managing the Data Flow from the LSST

Details Managing the Data Flow from the LSST Managing the Data Flow from the LSST

Dec 2002

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2002aas...20113405c&link_type=abstract

American Astronomical Society, 201st AAS Meeting, #134.05; Bulletin of the American Astronomical Society, Vol. 34, p.1318

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The Large-aperture Synoptic Survey Telescope (LSST) represents the next generation of wide-field survey telescopes. With repeated scans of the sky on timescales ranging from a few minutes to several years it will be one of the first of the wide-area survey facilities to open up the study of the time domain in astrophysics. The scientific returns from such an approach are numerous, ranging from the dynamics of near-Earth asteroids and Kuiper-belt objects through to the detection of intermediate and high redshift supernovae. We will discuss here the impact that such a diverse range of scientific questions will have on the analysis and management of the data flow from such a telescope. We will focus on a number of areas that must be addressed in order for the successful operation of the LSST. These will include: a) the computational challenge presented by a data rate in excess of 8TB per night b) approaches for efficiently measuring the differences between repeated observations or for co-adding multiple images to construct a deep image of the sky c) the impact on the design of the software due to the requirement that we be able to detect variability over a very broad range of temporal scales (from almost real-time though to several years) d) our ability to successfully archive the data products from this survey such that they maximize the LSST's scientific returns. Throughout we will discuss the current state-of-the-art in analysis software and algorithms and how they might be expected to scale with the increase in computational resources over the coming decade. We will use existing surveys to estimate the likely load on such a processing system and identify the areas within the data management that we must address in the near future.

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