Galaxy Analysis over Large Areas:
Parameter Assessment by
GALFITting Objects from SExtractor

Context: GALAPAGOS is an application to help automate the analysis of large astronomical imaging survey data sets. It simplifies the process of source detection, two-dimensional light-profile modelling and catalogue compilation.

Aims: The idea is to combine object detection with SExtractor and light profile modelling with GALFIT. Additionally, GALAPAGOS incorporates routines to cuts postage stamp images for all sources, prepare object masks and estimate a robust local sky background. Control of all these features is managed through a single setup script, thus enabling simple access to manage large survey data sets.

Methods: GALAPAGOS uses SExtractor to initially detect sources in the images and applies GALFIT to model galaxy light profiles. To robustly estimate the background sky it uses a flux growth curve method. The sizes of postage stamps for detected sources are based on SExtractor shape parameters. In order to efficiently process large amounts of data in reasonable time, GALAPAGOS incorporates a complex sorting mechanism and makes use of modern CPU's multiplexing capabilities. When combining data from different survey images, it takes care to remove multiple entries from identical sources. GALAPAGOS is programmed in the Interactive Data Language, IDL.

Results: Recently, various teams have used GALAPAGOS to analyse imaging surveys. Additionally, we tested its stability and ability to properly recover structural parameters extensively with artificial image simulations. GALAPAGOS is fast: a single 2.2 GHz CPU processes about 1000 primary sources per 24 hours (one-orbit HST data).