Probing the large-scale structure of the universe with future galaxy redshift surveys

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

Characterization of Segmented Large Volume, High Purity Germanium Detectors

Gamma ray tracking in future HPGe arrays like AGATA will rely on pulse shape analysis (PSA) of multiple Gamma interactions. For this purpose, a simple and fast procedure was developed which enabled the first full characterization of a segmented large volume HPGe detector. An analytical model for the hole mobility in a Ge crystal lattice was developed to describe the hole drift anisotropy with experimental velocity values along the crystal axis as parameters. The new model is based on the drifted Maxwellian hole distribution in Ge. It is verified by reproducing successfully experimental longitudinal hole anisotropy data. A comparison between electron and hole mobility shows large differences for the longitudinal and tangential velocity anisotropy as a function of the electrical field orientation. Measurements on a 12 fold segmented, n-type, large volume, irregular shaped HPGe detector were performed in order to determine the parameters of anisotropic mobility for electrons and holes as charge carriers created by gamma ray interactions. To characterize the electron mobility the complete outer detector surface was scanned in small steps employing photopeak interactions at 60keV. A precise measurement of the hole drift anisotropy was performed with 356keV rays. The drift velocity anisotropy and crystal geometry cause considerable rise time differences in pulse shapes depending on the position of the spatial charge carrier creation. Pulse shapes of direct and transient signals are reproduced by weighting potential calculations with high precision. The measured angular dependence of rise times is caused by the anisotropic mobility, crystal geometry, changing field strength and space charge effects. Preamplified signals were processed employing digital spectroscopy electronics. Response functions, crosstalk contributions and averaging procedures were taken into account implying novel methods due to the segmentation of the Ge-crystal and the digital electronics. The results are relevant for the future gamma ray tracking detectors where high precision of position information of single gamma ray interactions is required. The high accuracy in simulation enabled very high position resolution using PSA. The first application of this technique in a real experiment aimed at the correction for crystal bending imperfections in a Bragg-spectrometer. A position resolution of 1.4mm (sigma) was achieved with 184keV gamma rays employing the fully characterized detector. By careful characterization of the electronic noise, this result is expected to improve further upon use of optimized filters

Non-linear dependences in finance

The thesis is composed of three parts. Part I introduces the mathematical and statistical tools that are relevant for the study of dependences, as well as statistical tests of Goodness-of-fit for empirical probability distributions. I propose two extensions of usual tests when dependence is present in the sample data and when observations have a fat-tailed distribution. The financial content of the thesis starts in Part II. I present there my studies regarding the "cross-sectional" dependences among the time series of daily stock returns, i.e. the instantaneous forces that link several stocks together and make them behave somewhat collectively rather than purely independently. A calibration of a new factor model is presented here, together with a comparison to measurements on real data. Finally, Part III investigates the temporal dependences of single time series, using the same tools and measures of correlation. I propose two contributions to the study of the origin and description of "volatility clustering": one is a generalization of the ARCH-like feedback construction where the returns are self-exciting, and the other one is a more original description of self-dependences in terms of copulas. The latter can be formulated model-free and is not specific to financial time series. In fact, I also show here how concepts like recurrences, records, aftershocks and waiting times, that characterize the dynamics in a time series can be written in the unifying framework of the copula.Comment: PhD Thesi

COBE's search for structure in the Big Bang

The launch of Cosmic Background Explorer (COBE) and the definition of Earth Observing System (EOS) are two of the major events at NASA-Goddard. The three experiments contained in COBE (Differential Microwave Radiometer (DMR), Far Infrared Absolute Spectrophotometer (FIRAS), and Diffuse Infrared Background Experiment (DIRBE)) are very important in measuring the big bang. DMR measures the isotropy of the cosmic background (direction of the radiation). FIRAS looks at the spectrum over the whole sky, searching for deviations, and DIRBE operates in the infrared part of the spectrum gathering evidence of the earliest galaxy formation. By special techniques, the radiation coming from the solar system will be distinguished from that of extragalactic origin. Unique graphics will be used to represent the temperature of the emitting material. A cosmic event will be modeled of such importance that it will affect cosmological theory for generations to come. EOS will monitor changes in the Earth's geophysics during a whole solar color cycle

Kinetic Analysis of dynamic MP4A PET Scans of Human Brain using Voxel based Nonlinear Least Squares Fitting

Dynamic PET (Positron Emission Tomography) involving a number of radiotracers is an established technique for in vivo estimation of biochemical parameters in human brain, such as the overall metabolic rate and certain receptor concentrations or enzyme activities. 11C labeled methyl-4-piperidyl acetate (MP4A) and -propionate (MP4P) are established radiotracers for measuring activity of acetylcholine esterase (AChE), which relates to functionality of the cholinergic system. MP4A kinetic analysis without arterial blood sampling employs a reference tissue based "irreversible tracer model". Implementations can be region or voxel based, in the second case providing parametric images of k3 which is an indicator of AChE activity. This work introduces an implementation of voxel based kinetic analysis using weighted Nonlinear Least Squares fitting (NLS), which is fast enough for standard PCs. The entire workflow leading from reconstructed PET scans to parametric images of k3, including normalization and correction for patient movement, has been automatized. Image preprocessing has been redefined and fixed masks are no longer required. A focus of this work is error estimation of k3 at the voxel and regional level. A formula is derived for voxel based estimation of random error, it is based on residual weighted squared differences and has been successfully validated against simulated data. The reference curves turned out to be the main source of errors in regional mean values of k3. Major improvements were reached in this area by switching from fixed to adaptive Putamen masks and raising their volume from 5.4 to 12.5 or 16 ml. Also, a method for correcting reference curves obtained from nonideal reference tissues is presented. For the improved implementation, random error of the mean k3 of a number of cerebral regions has been assessed based on PET studies of 12 human subjects, by splitting them in two independent data sets at the sinogram level. According to this sample, absolute standard errors of 0.0012 in most cortex regions and 0.0053 in Hippocampus are induced by noise of voxel based activity curves, while errors of approximately 0.0025 and 0.0050 are induced by noise of the reference curves. Different types of systematic as well as noise-induced bias have been investigated by simulations; their combined effect on the computed k3 was found below 3 percent. The implementation is available as a modul of the VINCI software package and has been used in clinical studies on Parkinson's Disease and Alzheimer Dementia