Computer Science – Performance
Scientific paper
Sep 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009aspc..411...55l&link_type=abstract
Astronomical Data Analysis Software and Systems XVIII ASP Conference Series, Vol. 411, proceedings of the conference held 2-5 No
Computer Science
Performance
9
Scientific paper
Gaia is ESA's ambitious space astrometry mission with a foreseen launch date in late 2011. Its main objective is to perform a stellar census of the 1,000 million brightest objects in our galaxy (completeness to V=20 mag) from which an astrometric catalog of micro-arcsec (μas) level accuracy will be constructed. A key element in this endeavor is the Astrometric Global Iterative Solution (AGIS) - the mathematical and numerical framework for combining the ≈80 available observations per star obtained during Gaia's 5 yr lifetime into a single global astrometic solution. AGIS consists of four main algorithmic cores which improve the source astrometic parameters, satellite attitude, calibration, and global parameters in a block-iterative manner. We present and discuss this basic scheme, the algorithms themselves and the overarching system architecture. The latter is a data-driven distributed processing framework designed to achieve an overall system performance that is not I/O limited. AGIS is being developed as a pure Java system by a small number of geographically distributed European groups. We present some of the software engineering aspects of the project and show used methodologies and tools. Finally we will briefly discuss how AGIS is embedded into the overall Gaia data processing architecture.
Hobbs David
Lammers Uwe
Lindegren Lennart
O'Mullane William
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