The work in this thesis charts the revival and development of research that tests some of the core fundamental assumptions that characterise the study of magnitude-redshift surveys for the estimation of galaxy luminosity functions (LF). Estimating LFs, either parametrically or non-parametrically, generally requires the assumption of separability between the LF, and the density function. The work carried out initially by Rauzy (2001) amounts to a test statistic, Tc, constructed from the cumulative luminosity function (CLF). It is a direct probe of separability and therefore is rendered a magnitude completeness test to identify the presence of potential systematics and/or evolution within a particular survey sample. We originally applied Rauzy's test of completeness to the Millennium Galaxy Catalogue (MGC), the Two Degree Field Galaxy Redshift Survey (2dFGRS) and the Sloan Digital Sky Survey (SDSS). We then extended the Tc statistic for data-sets characterised by two distinct faint and bright apparent magnitude limits. Following on from this we have developed a variant on Tc that we have named, Tv, which was constructed instead from the cumulative density function (CDF) and can be considered a differential form of the much celebrated, Schmidt (1968) V/Vmax statistic. The completeness analysis of data-sets such as the 2dFGRS and the Clowes Campusano Large Quasar Group Survey (CCLQG) have also lead to developing a procedure that will optimise our estimators based on the signal-to-noise of our sampling technique. Finally, we have developed a new, robust statistical probe to constrain evolutionary models applied to current and future redshift surveys. This probe exploits the fundamental assumption of separability coupled with a maximum entropy technique to constrain the evolutionary parameter that characterises, in particular, pure luminosity evolution.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:513051 |
| Date | January 2009 |
| Creators | Johnston, Russell W. I. |
| Publisher | University of Glasgow |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://theses.gla.ac.uk/1175/ |
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