University of Hertfordshire

From the same journal

From the same journal

  • Andreas Hiemer
  • Marco Barden
  • Lee S. Kelvin
  • Boris Häußler
  • Sabine Schindler
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Original languageEnglish
Number of pages29
Pages (from-to)3089-3117
JournalMonthly Notices of the Royal Astronomical Society
Journal publication date11 Nov 2014
Volume444
Issue4
Early online date15 Sep 2014
DOIs
Publication statusPublished - 11 Nov 2014

Abstract

We present GALAPAGOS-C, a code designed to process a complete set of survey images through automation of source detection (via SEXTRACTOR), postage stamp cutting, object mask preparation, sky background estimation and complex two-dimensional light profile Sérsic modelling (via GALFIT). GALAPAGOS-C is designed around the concept of MPI-parallelization, allowing the processing of large data sets in a quick and efficient manner. Further, GALAPAGOS-C is capable of fitting multiple-Sérsic profiles to each galaxy, each representing distinct galaxy components (e.g. bulge, disc, bar), in addition to the option to fit asymmetric Fourier mode distortions. The modelling reliability of our core single-Sérsic fitting capability is tested thoroughly using image simulations.We apply GALAPAGOS-C to the Space Telescope A901/902 Galaxy Evolution Survey to investigate the evolution of galaxy structure with cosmic time and the dependence on environment. We measure the distribution of Sérsic indices as a function of local object density in the A901/902 cluster sample to provide one of the first measures of the Sérsic index- density relation. We find that the fraction of galaxies with a high Sérsic index (2.5 < n < 7.0) is higher in denser environments (35 per cent), halving towards sparsely populated regions (15 per cent). The population of low Sérsic index galaxies (0.4 < n< 1.6) is lower in denser environments (35 per cent), increasing towards sparsely populated regions (60 per cent). The population of intermediate Sérsic index galaxies (1.6 < n < 2.5) approximately follows the trend of the high Sérsic index types.

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ID: 9201446