Precision cosmology from large-scale galaxy clustering with the Sloan Digital Sky Survey

Details Precision cosmology from large-scale galaxy clustering with the Sloan Digital Sky Survey Precision cosmology from large-scale galaxy clustering with the Sloan Digital Sky Survey

Jun 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006phdt.........1p&link_type=abstract

PhD dissertation, Proquest Dissertations And Theses 2006. Section 0098, Part 0606 124 pages; [Ph.D. dissertation]. United State

Mathematics

Logic

Cosmology, Galaxy Clustering, Sloan Digital Sky Survey, Large-Scale Structure

Scientific paper

We present estimates of cosmological parameters from the application of the linear Karhunen-Loève (KL) transform technique to the analysis of the three- dimensional power spectrum of density fluctuations using Sloan Digital Sky Survey (SDSS) galaxy redshifts. We use O m h and f b = O b /O m to describe the shape of the power spectrum, [Special characters omitted.] for the (linearly extrapolated) normalization, and b to parametrize linear theory redshift-space distortions. On scales k <= 0.16 h/Mpc, our maximum likelihood values are O m h = [Special characters omitted.] , f b = [Special characters omitted.] , [Special characters omitted.] = [Special characters omitted.] , and b [Special characters omitted.] . When we take a prior on O b from the Wilkinson Microwave Anisotropy Probe (WMAP) results, we find O m h = [Special characters omitted.] , which is in excellent agreement with other measurements. Thus we have reasonably measured the gross shape of the power spectrum, but some degeneracy remains between O m h and f b because the baryon oscillations were not resolved given the survey window function at the time.
This work also describes methods for processing data within science archive databases, specifically the SDSS Catalog Archive Server (CAS), in order to prepare well-characterized samples of data that are free of survey artifacts for sensitive studies of galaxy clustering. Advanced spatial indexing systems are used to improve performance and describe the complex interactions of spherical geometric objects that describe the geometry of the survey. We also generate and use Monte Carlo random points on a cluster of database servers. These methods are combined to compress the galaxy redshift data for the first step in the linear KL algorithm.

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