Mathematics – Logic
Scientific paper
Nov 2005
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005phdt.........5n&link_type=abstract
Ph.D dissertation, 2005. Section 0051, Part 0606 138 pages; United States -- Colorado: University of Colorado at Boulder; 2005.
Mathematics
Logic
Dark Matter
Scientific paper
The theme of this thesis is the relationship between the visible and the dark matter in the Universe on large length scales. This relationship is important to understand, since it seems that the relatively simple dynamics of the dark matter dominates the large-scale structure of the Universe, but this structure must be tested with observations of visible matter.
More specifically, in the first two papers which comprise this thesis, I investigate how to tell where galaxies might reside, given a collection of dark matter. In Chapter 2, I compare the spatial distribution of dark-matter haloes (virialized lumps where galaxies are thought to reside) detected in cosmological N -body simulations to the spatial distribution of galaxies as measured from observations. I use a standard statistic to quantify the spatial distributions, the power spectrum. In this study, the method I use to detect haloes in the simulations is adequate, but not entirely satisfactory. In Chapter 3, I describe an improved halo-finding algorithm which I developed.
The third paper, in Chapter 4, is more analytical than the previous two. I derive and test relationships between the power spectra of galaxies and dark matter, and also the galaxy-matter power spectrum (which quantifies the distribution of matter around galaxies). This project grew out of a desire to understand better recent measurements of the clustering of dark matter around galaxies. These are exciting measurements since for the first time, they allow an aspect of the large-scale distribution of dark matter in the Universe to
be quantified observationally with useful precision. The relationships I derive aid intuitive understanding, and also should prove useful in interpreting future precision measurements of galaxy-matter clustering.
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