Computer Science – Databases
Scientific paper
Dec 2008
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008aipc.1082..137h&link_type=abstract
CLASSIFICATION AND DISCOVERY IN LARGE ASTRONOMICAL SURVEYS: Proceedings of the International Conference: ``Classification and Di
Computer Science
Databases
1
Image Processing, Quasars, Active Or Peculiar Galaxies, Objects, And Systems, Astronomical Catalogs, Atlases, Sky Surveys, Databases, Retrieval Systems, Archives, Etc.
Scientific paper
In the context of big HST surveys, we present extensive and well tested image simulations to derive the survey detection completeness. We elaborate on the reliability of 2D galaxy fitting codes (GALFIT and GIM2D), which are widely used for morphological galaxy classification (especially for galaxies at high redshift), but are rarely tested thoroughly. While both codes perform similarly well on bright, big galaxies in these surveys, we find that GALFIT is more robust on faint and small galaxies, especially when used in the context of GALAPAGOS, a script that automates the fitting process successfully. Furthermore, we show that both codes underestimate the true parameter error bars severely. Whereas a Sérsic index cut is not an ideal tool to distinguish between early- and late-type galaxies it is widely used as such. We will point out potential complications in using such a simple automated cut. [1]
Barden Marco
Häußler Boris
McIntosh Daniel H.
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