This thesis explores possible solutions to the dwarf galaxy problem. This is a discrepancy between the number of dwarf galaxies we observe, and the number predicted from cosmological computer simulations. Simulations predict around ten times more dwarf galaxy satellites than are currently observed. I have investigated two possible solutions: dark galaxies and the low surface brightness universe. Dark galaxies are dark matter halos which contain gas, but few or no stars, hence are optically dark. As part of the Arecibo Galaxy Environment Survey I surveyed the neutral hydrogen gas around the nearby galaxy M33. I found 32 gas clouds, 11 of which are new detections. Amongst these there was one particularly interesting cloud. AGESM33-32 is ring shaped and larger than M33 itself, if at the same distance. It has a velocity width which is similar to the velocity dispersion of gas in a disk galaxy, as well as having a clear velocity gradient across it which may be due to rotation. The fact that it also currently has no observed associated stars means it is a dark galaxy candidate. Optically, dwarf galaxies may be out there, but too faint for us to detect. This means that with newer, deeper, images we may be able to unveil a large, low surface brightness, population of dwarf galaxies. However, the question remains as to how these can be distinguished from background galaxies. I have used Next Generation Virgo Survey (NGVS) data to carry out photometry on 852 Virgo galaxies in four bands. I also measured the photometric properties of galaxies on a background (non-cluster) NGVS frame. I discovered that a combination of colour magnitude and surface brightness information could be used to identify cluster dwarf galaxies from background field galaxies. The most effective method is to use the surface brightness-magnitude relation.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:723572 |
Date | January 2017 |
Creators | Keenan, Olivia Charlotte |
Publisher | Cardiff University |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://orca.cf.ac.uk/104065/ |
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