Statistics – Computation
Scientific paper
Aug 2007
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007phdt........16b&link_type=abstract
Proquest Dissertations And Theses 2007. Section 0070, Part 0606 117 pages; [Ph.D. dissertation].United States -- Florida: Unive
Statistics
Computation
Cell Count Moments, Halo, Cosmology, Large-Scale Structure, Structure Formation, Nonlinear Gravitational Clustering
Scientific paper
One of the main goals of the study of Large Scale Structures is to understand the clustering properties of the galaxy distribution from fundamental principles. Purely baryonic theories of Structure Formation failed to produce the desired results, suggesting strongly that the Universe is filled with some kind of dark matter which is non baryonic in nature and interacts weakly with ordinary baryonic matter. At this point of time it is not possible to determine the distribution of dark matter observationally. However we can observe the distribution of galaxies. Observations show that galaxy clustering on small scales is non-linear and an analytical understanding of Non Linear Gravitational Clustering (NLGC) is difficult to achieve. The higher order correlation functions cannot be determined analytically and the information available in full correlation functions derived from galaxy catalogs, if not beyond the reach of our computational abilities, is beyond our ability to handle. Count in cells offer a manageable alternative statistical measure and the Halo model a useful phenomenological model for studying NLGC. We study the moments of Count in cells in the Halo model. Halo model is used to predict, calibrate and interpret redshift distortions and finite volume effects in the measurements of galaxy correlation functions, weak gravitational lensing, the Lyman-alpha forest and CMB Sunyaev-Zel'dovich foregrounds. In order to be confident of these results it is important to test the model in as many ways as is possible.
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