Computer Science – Performance
Scientific paper
Jan 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011aas...21715605a&link_type=abstract
American Astronomical Society, AAS Meeting #217, #156.05; Bulletin of the American Astronomical Society, Vol. 43, 2011
Computer Science
Performance
Scientific paper
When simulating the distribution of sources across the night sky, querying for stationary objects, such as galaxies, is relatively simple. For moving objects, such as near earth objects (NEOs) and main belt asteroids (MBAs), this becomes increasing more complex. Each family of solar system objects has a range of abundances and speeds through ra/dec space. For example, MBAs are plentiful ( 107) but move slowly (< 1 deg/day), and NEOs are rare ( 105) but can move up to 70 deg/day. How do we optimally store and query all families of moving objects? We describe performance results and experiences using different methods, such as storing bounding boxes for the trajectories, and spatial abstraction tools, such as MSSQL geospatial support and SkyServer's HTM index and library of spatial constructs. We apply these results to simulations of the data flow from the Large Synoptic Survey Telescope with the goal of querying simulated catalogs quickly for a list of objects that would appear in the LSST's circular aperture at a given pointing and epoch.
AlSayyad Yusra
Budavari Tamas
Connolly Andrew J.
Howe Bill
Jones Lynne
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