Galaxy and mass assembly (GAMA): Detection of low-surface-brightness galaxies from SDSS data

Richard P. Williams, Ivan K Baldry, Lee S Kelvin, P. A. James, S. P. Driver, M. Prescott, Sarah Brough, M J I Brown, L. J.M. Davies, Benne W Holwerda, Jochen Liske, Peder Norberg, Amanda J Moffett, A. H. Wright

Research output: Contribution to journalArticleResearchpeer-review

11 Citations (Scopus)

Abstract

We report on a search for new low-surface-brightness galaxies (LSBGs) using Sloan Digital Sky Survey (SDSS) data within the Galaxy And Mass Assembly (GAMA) equatorial fields. The search method consisted of masking objects detected with SDSS photo, combining gri images weighted to maximize the expected signal-to-noise ratio, and smoothing the images. The processed images were then run through a detection algorithm that finds all pixels above a set threshold and groups them based on their proximity to one another. The list of detections was cleaned of contaminants such as diffraction spikes and the faint wings of masked objects. From these, selecting potentially the brightest in terms of total flux, a list of 343 LSBGs was produced having been confirmed using VISTA Kilo-degree Infrared Galaxy Survey (VIKING) imaging. The photometry of this sample was refined using the deeper VIKING Z band as the aperture-defining band. Measuring their g - i and J - K colours shows that most are consistent with being at redshifts less than 0.2. The photometry is carried out using an auto aperture for each detection giving surface brightnesses of μr ≳ 25 mag arcsec-2 and magnitudes of r > 19.8 mag. None of these galaxies are bright enough to be within the GAMA main survey limit but could be part of future deeper surveys to measure the low-mass end of the galaxy stellar mass function.

Original languageEnglish
Pages (from-to)2746-2755
Number of pages10
JournalMonthly Notices of the Royal Astronomical Society
Volume463
Issue number3
DOIs
Publication statusPublished - 2016

Keywords

  • Galaxies: dwarf
  • Galaxies: photometry
  • Techniques: image processing

Cite this