Computer Science – Performance
Scientific paper
Jan 2003
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003jad.....9....8d&link_type=abstract
THE JOURNAL OF ASTRONOMICAL DATA Vol. 9 2003
Computer Science
Performance
Scientific paper
The DIVA satellite will, in addition to the astrometry, obtain photometric data for about 40 million survey stars and spectral data for about a third of these. Relevant sections of the CCD-data stream will be transmitted to Earth to allow a photometric and a spectrophotometric analysis.
The DIVA photometric (SM) data can be used to derive stellar colours. Colours are in particular required for the chromaticity correction of the astrometry. The UV telescope (UV) is designed to obtain information about the Balmer jump region of the spectral energy distribution. The spectrophotometric (SC) data consists of overlapping spectral orders in the cross-scan direction. From these SC images the dispi (dispersed position-coded intensity) will be derived. The information on all stellar parameters is, of course, contained in the dispi and can be extracted without deconvolution. CCDs of the type foreseen for DIVA are in the process of being tested for their performance under the special conditions of this space mission.
Methods are being tested, like artificial neural networks (ANNs) and others, to derive the astrophysical parameters Teff, log g, [M/H], and E(B-V) from the dispi. We find that even with the relatively modest spectral resolution of the dispi the ANN can discriminate well in temperature, moderately well in gravity and extinction, and crudely in metallicity, all clearly dependent on the brightness of the star. Degeneracy in the temperature and extinction determination can be lifted especially using Balmer jump information from the DIVA UV telescope.
Bailer-Jones Coryn A. L.
de Boer Klaas. S.
Evans Dafydd W.
Hilker Michael
Kaempf T. A.
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