Galaxy And Mass Assembly (GAMA): detection of low-surface-brightness galaxies from SDSS data

Abstract

We report on a search for new low-surface-brightness galaxies (LSBGs) using Sloan Digital Sky Survey (SDSS) data within the GAMA equatorial fields. The search method consisted of masking objects detected with SDSS photo, combining gri images weighted to maximise the expected signal-to-noise ratio (SNR), 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 ${\mu }_r\ge 25\mathrm{mag}{\mathrm{arcsec}}^{-2}$ 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.

11 pages, 8 figures, accepted by MNRAS

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• Observational Properties of Ultra-Diffuse Galaxies in the Field: Field-UDGs are Predominantly Blue and Starforming
• Sky Subtraction in an Era of Low Surface Brightness Astronomy
• Low-Surface-Brightness Galaxies are missing in the observed Stellar Mass Function
• A Sample of Edge-on HI-rich low-surface-brightness Galaxy Candidates in the 40% ALFALFA Catalog
• Understanding the chemical evolution of blue Edge-on Low Surface Brightness Galaxies
• Variation of optical and infrared properties of galaxies with their surface brightness
• Cosmological prior for the $J$-factor estimation of dwarf spheroidal galaxies
• Estimating the mass of galactic components using machine learning algorithms