Sabiu, Cristiano Giovanni (2006) Probing the large-scale homogeneity of the universe with galaxy redshift surveys. MSc(R) thesis, University of Glasgow.
Full text available as:| 
              
PDF
 Download (5MB)  | 
          
Abstract
Modern cosmological observations clearly reveal that the universe contains a hierarchy of clustering. However, recent surveys show a transition to homogeneity on large scales. The exact scale at which this transition occurs is still a topic of much debate. There has been much work done in trying to characterise the galaxy distribution using multifractals. However, for a number of years the size, depth and accuracy of galaxy surveys was regarded as insufficient to give a definitive answer. One of the main problems which arises in a multifractal analysis is how to deal with observational selection effects: i.e. 'masks' in the survey region and a geometric boundary to the survey itself. In this thesis I will introduce a volume boundary correction which is rather similar to the approach developed by Pan and Coles in 2001, but which improves on their angular boundary correction in two important respects: firstly, our volume correction 'throws away' fewer galaxies close the boundary of a given data set and secondly it is computationally more efficient. After application of our volume correction, I will then show how the underlying generalised dimensions of a given point set can be computed. I will apply this procedure to calculate the generalised fractal dimensions of both simulated fractal point sets and mock galaxy surveys which mimic the properties of the recent IRAS PSCz catalogue.
| Item Type: | Thesis (MSc(R)) | 
|---|---|
| Qualification Level: | Masters | 
| Additional Information: | Adviser: Martin Hendry | 
| Keywords: | Astronomy | 
| Date of Award: | 2006 | 
| Depositing User: | Enlighten Team | 
| Unique ID: | glathesis:2006-74221 | 
| Copyright: | Copyright of this thesis is held by the author. | 
| Date Deposited: | 23 Sep 2019 15:33 | 
| Last Modified: | 23 Sep 2019 15:33 | 
| URI: | https://theses.gla.ac.uk/id/eprint/74221 | 
Actions (login required)
![]()  | 
        View Item | 
Downloads
Downloads per month over past year
        
            
 Tools
 Tools