The Spectrum of LSST Data Analysis Challenges: Kiloscale to Petascale

Details The Spectrum of LSST Data Analysis Challenges: Kiloscale to Petascale The Spectrum of LSST Data Analysis Challenges: Kiloscale to Petascale

Jan 2010

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010aas...21540124l&link_type=abstract

American Astronomical Society, AAS Meeting #215, #401.24; Bulletin of the American Astronomical Society, Vol. 42, p.221

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The unprecedented science opportunities enabled by LSST's wide-fast-deep mode of operation are accompanied by equally unprecedented data analysis challenges, due to the huge size and synoptic scope of LSST data products. While the most obvious challenges are those due to the petabyte scale of fundamental LSST databases, new and difficult data analysis problems that span a broad range of sizes, types, and complexity, and require a matching breadth of methodological research, must also be addressed. Some smaller-scale LSST data products, such as multicolor light curves for individual objects, will present challenging statistics problems; e.g., requiring multivariate time series methods capable of handling nonuniform, non-simultaneous sampling with measurement errors. Very large-scale LSST data products, such as comprehensive catalogs of stars or galaxies, will require significant informatics/data mining innovation; e.g., to enable accurate classification or photo-z estimation for huge samples. These scales mark the boundaries of a broad spectrum of LSST data analysis problems; research-level informatics and statistics challenges arise in various combinations across this whole spectrum. We survey the diversity of forthcoming LSST data analysis problems and opportunities, highlighting representative problems that address compelling astronomical science and present significant methodological challenges involving both astrostatistics and astroinformatics.

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