Hatton, Stephen John (1999) Probing the large-scale structure of the universe with future galaxy redshift surveys. Doctoral thesis, Durham University.
Several projects are currently underway to obtain large galaxy redshift surveys over the course of the next decade. The aim of this thesis is to study how well the resultant three-dimensional maps of the galaxy distribution will be able to constrain the various parameters of the standard Big Bang cosmology. The work is driven by the need to deal with data of far better quality than has previously been available. Systematic biases in the treatment of existing datasets have been dwarfed by random errors due to the small size of the sample, but this will not be the case with the wealth of data that will shortly become available. We employ a set of high-resolution /V-body simulations spanning a range of cosmologies and galaxy biasing schemes. We use the power spectrum of the galaxy density field, measured using the fast Fourier transform process, to develop models and statistics for extracting cosmological information. In particular, we examine the distortion of the power spectrum by galaxy peculiar velocities when measurements are made in redshift space. Mock galaxy catalogues are drawn from these simulations, mimicking the geometries and selection functions of the large surveys we wish to model. Applying the same models to the mock catalogues is not a trivial task, as geometrical effects distort the power spectrum, and measurement errors are determined by the survey volume. We develop methods for assessing these effects and present an in-depth analysis of the likely confidence intervals we will obtain from the surveys on the parameters that determine the power spectrum. Real galaxy catalogues are prone to additional biases that must be assessed and removed. One of these is the effect of extinction by dust in the Milky Way, which imprints its own angular clustering signal on the measured power spectrum. We investigate the strength of this effect for the SDSS survey.
|Item Type:||Thesis (Doctoral)|
|Award:||Doctor of Philosophy|
|Copyright:||Copyright of this thesis is held by the author|
|Deposited On:||13 Sep 2012 15:45|