Object classification and astrophysical parameter determination with the GAIA Galactic Survey Mission and virtual observatories

Details Object classification and astrophysical parameter determination with the GAIA Galactic Survey Mission and virtual observatories Object classification and astrophysical parameter determination with the GAIA Galactic Survey Mission and virtual observatories

May 2003

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003aas...202.5505b&link_type=abstract

American Astronomical Society Meeting 202, #55.05; Bulletin of the American Astronomical Society, Vol. 35, p.774

Astronomy and Astrophysics

Astrophysics

1

Scientific paper

The GAIA Galactic Survey Mission will be launched in 2010 by the European Space Agency to obtain microarcsecond precision astrometry and radial velocities of stars across the entire Galaxy. The resulting six dimensional phase space database (3 spatial, 3 velocity co-ordinates) will be supplemented by 15 band optical photometry at many tens of epochs. This large, complex database -- comprising all one billion objects in the sky brighter than 20th magnitude -- will be the basis for numerous scientific projects, such as investigating the merger history and chemical evolution of our Galaxy, mapping its star formation history and searching for exosolar planets, and will significantly improve our understanding of stellar and galactic astrophysics. But to achieve this, an accurate classification of everything in the database (including QSOs, galaxies and solar system objects) will be required, as will a detailed determination of stellar parameters (effective temperatures, radii, metallicities etc.). I shall describe the approach being taken to tackle this complex task and mention the multidimensional data analysis techniques which are being studied for this purpose. A number of the challenges we face are common to those faced by virtual observatory projects, including combination of inhomogeneous data, object matching, efficient mining for specific object types and variable criteria for object selection.

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