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In the current paradigm of cosmology, the formation of large-scale structures is mainly driven by non-radiating dark matter, making up the dominant part of the matter budget of the Universe. Cosmological observations however, rely on the detection of luminous galaxies, which are biased tracers of the underlying dark matter. In this thesis I present cosmological reconstructions of both, the dark matter density field that forms the cosmic web, and cosmic velocities, for which both aspects of my work are delved into, the theoretical formalism and the results of its applications to cosmological simulations and also to a galaxy redshift survey.The foundation of our method is relying on a statistical approach, in which a given galaxy catalogue is interpreted as a biased realization of the underlying dark matter density field. The inference is computationally performed on a mesh grid by sampling from a probability density function, which describes the joint posterior distribution of matter density and the three dimensional velocity field. The statistical background of our method is described in Chapter ”Implementation of argo”, where the introduction in sampling methods is given, paying special attention to Markov Chain Monte-Carlo techniques. In Chapter ”Phase-Space Reconstructions with N-body Simulations”, I introduce and implement a novel biasing scheme to relate the galaxy number density to the underlying dark matter, which I decompose into a deterministic part, described by a non-linear and scale-dependent analytic expression, and a stochastic part, by presenting a negative binomial (NB) likelihood function that models deviations from Poissonity. Both bias components had already been studied theoretically, but were so far never tested in a reconstruction algorithm. I test these new contributions againstN-body simulations to quantify improvements and show that, compared to state-of-the-art methods, the stochastic bias is inevitable at wave numbers of k≥0.15h Mpc^−1 in the power spectrum in order to obtain unbiased results from the reconstructions. In the second part of Chapter ”Phase-Space Reconstructions with N-body Simulations” I describe and validate our approach to infer the three dimensional cosmic velocity field jointly with the dark matter density. I use linear perturbation theory for the large-scale bulk flows and a dispersion term to model virialized galaxy motions, showing that our method is accurately recovering the real-space positions of the redshift-space distorted galaxies. I analyze the results with the isotropic and also the two-dimensional power spectrum.Finally, in Chapter ”Phase-space Reconstructions with Galaxy Redshift Surveys”, I show how I combine all findings and results and apply the method to the CMASS (for Constant (stellar) Mass) galaxy catalogue of the Baryon Oscillation Spectroscopic Survey (BOSS). I describe how our method is accounting for the observational selection effects inside our reconstruction algorithm. Also, I demonstrate that the renormalization of the prior distribution function is mandatory to account for higher order contributions in the structure formation model, and finally a redshift-dependent bias factor is theoretically motivated and implemented into our method. The various refinements yield unbiased results of the dark matter until scales of k≤0.2 h Mpc^−1in the power spectrum and isotropize the galaxy catalogue down to distances of r∼20h^−1 Mpc in the correlation function. We further test the results of our cosmic velocity field reconstruction by comparing them to a synthetic mock galaxy catalogue, finding a strong correlation between the mock and the reconstructed velocities. The applications of both, the density field without redshift-space distortions, and the velocity reconstructions, are very broad and can be used for improved analyses of the baryonic acoustic oscillations, environmental studies of the cosmic web, the kinematic Sunyaev-Zel’dovic or integrated Sachs-Wolfe effect.
In der vorliegenden Arbeit wird die planetare Grenzschicht in Ny-Ålesund, Spitzbergen, sowohl bezüglich kleinskaliger („mikrometeorologischer“) Effekte als auch in ihrer Kopplung mit der Synoptik untersucht. Dazu werden verschiedene Beobachtungsdaten aus der Säule und in Bodennähe zusammengezogen und bewertet. Die so gewonnenen Datensätze werden dann zur Validierung eines nicht-hydrostatischen, regionalen Klimamodells genutzt. Weiterhin werden orographisch bedingte Einflüsse, die Untergrundbeschaffenheit und die lokale Heterogenität der Unterlage untersucht. Hierzu werden meteorologische Größen, wie die Variabilität der Temperatur und insbesondere die jährliche Windverteilung in Bodennähe untersucht und es erfolgt ein Vergleich von in-situ gemessenen turbulenten Flüssen von den Eddy-Kovarianz-Messkomplexen bei Ny-Ålesund und im Bayelva-Tal unter demselben Aspekt. Es zeigt sich, dass der Eddy-Kovarianz-Messkomplex im Bayelva-Tal sehr stark durch eine orographisch bedingte Kanalisierung der Strömung beeinflusst ist und sich nicht für Vergleiche mit regionalen Klimamodellen mit horizontalen Auflösungen von <1km eignet. Die hohe Bodenfeuchte im Bayelva-Tal führt zudem zu einem deutlich kleineren Bowen-Verhältnis, als es für diese Region zu erwarten ist. Der Eddy-Kovarianz-Messkomplex bei Ny-Ålesund erweist sich hingegen als geeigneter für solche Modellvergleiche, aufgrund der typischen, küstennahen Windverteilung und des repräsentativen Footprints. Letzteres wird durch die Bestimmung der Footprint-Klimatologie des Jahres 2013 mit einem aktuellen Footprint-Modell erarbeitet.
Weiterhin wird die Auswirkung von (Anti-) Zyklonen über den Archipel auf die zeitliche Variabilität der lokalen Grenzschichteigenschaften untersucht und bewertet. Dazu wird ein Zyklonen-Detektions-Algorithmus auf ERA-Interim-Reanalysedatensätze angewendet, wodurch die Häufigkeit von nahezu ideal konzentrischen Hoch- und die Tiefdruckgebieten für drei Jahre bestimmt wird. Aus dieser Verteilung werden insgesamt drei interessante Zeiträume zu verschiedenen Jahreszeiten ausgewählt und im Rahmen von Prozessstudien die lokalen bodennahen meteorologischen Messungen, der turbulente Austausch an der Oberfläche und die Grenzschichtdynamik in der Säule untersucht. Die zeitliche Variabilität der dynamischen Grenzschichtstabilität in der Säule wird anhand von zeitlich hoch aufgelösten vertikalen Profilen der Bulk-Richardson-Zahl aus Kompositprofilen aus Fernerkundungsinstrumenten (Radiometer, Wind-LIDAR) sowie Mastdaten (BSRN-Mast) untersucht und die Grenzschichthöhe ermittelt. Aus diesen Analysen ergibt sich eine deutliche Abhängigkeit der thermischen Stabilität beim Durchzug von Fronten, eine damit einhergehende erhebliche Abhängigkeit der Grenzschichtdynamik und der Grenzschichthöhe sowie des turbulenten Austauschs von der zeitlichen Variabilität der Windgeschwindigkeit in der Säule.
Auf Grundlage der Standortanalysen und Prozessstudien erfolgt ein Vergleich der bodennahen Messungen und den Beobachtungen aus der Säule, sowohl von den genannten Fernerkundungsinstrumenten als auch von In-situ-Messungen (Radiosonden) für den Zeitraum einer Radiosondierungskampagne mit dem nicht-hydrostatischen, regionalen Klimamodel WRF (ARW). Auf Grundlage der Fragestellung, inwieweit aktuelle Schemata die Grenzschichtcharakteristika in orographisch stark gegliedertem Gelände in der Arktis reproduzieren können, werden zwei Grenzschichtparametrisierungsschemata mit verschiedenen Ordnungen der Schließung validiert. Hierzu wird die zeitliche Variabilität der Temperatur, der Feuchte und des Windfeldes in der Säule bis 2000m in den Simulationen mit den Beobachtungsdaten vergleichen. Es wird gezeigt, dass durch Modifikation der Initialwertfelder eine sehr gute Übereinstimmung zwischen den Simulationen und den Beobachtungen bereits bei einer horizontalen Auflösung von 1km erreicht werden kann und die Wahl des Grenzschichtschemas nur untergeordneten Einfluss hat. Hieraus werden Ansätze der Weiterentwicklung der Parametrisierungen, aber auch Empfehlungen bezüglich der Initialwertfelder, wie der Landmaske und der Orographie, vorgeschlagen.
Water scarcity, adaption on climate change, and risk assessment of droughts and floods are critical topics for science and society these days. Monitoring and modeling of the hydrological cycle are a prerequisite to understand and predict the consequences for weather and agriculture. As soil water storage plays a key role for partitioning of water fluxes between the atmosphere, biosphere, and lithosphere, measurement techniques are required to estimate soil moisture states from small to large scales.
The method of cosmic-ray neutron sensing (CRNS) promises to close the gap between point-scale and remote-sensing observations, as its footprint was reported to be 30 ha. However, the methodology is rather young and requires highly interdisciplinary research to understand and interpret the response of neutrons to soil moisture. In this work, the signal of nine detectors has been systematically compared, and correction approaches have been revised to account for meteorological and geomagnetic variations. Neutron transport simulations have been consulted to precisely characterize the sensitive footprint area, which turned out to be 6--18 ha, highly local, and temporally dynamic. These results have been experimentally confirmed by the significant influence of water bodies and dry roads. Furthermore, mobile measurements on agricultural fields and across different land use types were able to accurately capture the various soil moisture states. It has been further demonstrated that the corresponding spatial and temporal neutron data can be beneficial for mesoscale hydrological modeling. Finally, first tests with a gyrocopter have proven the concept of airborne neutron sensing, where increased footprints are able to overcome local effects.
This dissertation not only bridges the gap between scales of soil moisture measurements. It also establishes a close connection between the two worlds of observers and modelers, and further aims to combine the disciplines of particle physics, geophysics, and soil hydrology to thoroughly explore the potential and limits of the CRNS method.
In the first part of my work I have investigated the ageing properties of the first passage time distributions in a one-dimensional subdiffusive continuous time random walk with power law distributed waiting times of the form $\psi(\tau) \sim \tau^{-1-\alpha}$ with $0<\alpha<1$ and $1<\alpha<2$. The age or ageing time $t_a$ is the time span from the start of the stochastic process to the start of the observation of this process (at $t=0$). I have calculated the results for a single target and two targets, also including the biased case, where the walker is driven towards the boundary by a constant force. I have furthermore refined the previously derived results for the non-ageing case and investigated the changes that occur when the walk is performed in a discrete quenched energy landscape, where the waiting times are fixed for every site. The results include the exact Laplace space densities and infinite (converging) series as exact results in the time space. The main results are the dominating long time power law behavior regimes, which depend on the ageing time. For the case of unbiased subdiffusion ($\alpha < 1$) in the presence of one target, I find three different dominant terms for ranges of $t$ separated by $t_a$ and another crossover time $t^{\star}$, which depends on $t_a$ as well as on the anomalous exponent $\alpha$ and the anomalous diffusion coefficient $K_{\alpha}$. In all three regimes ($t \ll t_a$, $t_a \ll t \ll t^{\star}$, $t \gg t^{\star}$) one finds power law decay with exponents depending on $\alpha$. The middle regime only exists for $t_a \ll t^{\star}$. The dominant terms in the first two regimes (ageing regimes) come from the probability distribution of the forward waiting time, the time one has to wait for the stochastic process to make the first step during the observation. When the observation time is larger than the second crossover time $t^{\star}$, the first passage time density does not show ageing and the non-ageing first passage time dominates. The power law exponents in the respective regimes are $-\alpha$ for strong ageing, $-1-\alpha$ in the intermediate regime, and $-1-\alpha/2$ in the final non-ageing regime. A similar split into three regimes can be found for $1<\alpha<2$, only with a different second crossover time $t^*$. In this regime the diffusion is normal but also age-dependent. For the diffusion in quenched energy landscapes one cannot detect ageing. The first passage time density shows a quenched power law $^\sim t^{-(1+2\alpha)/(1+\alpha)}$. For diffusion between two target sites and the biased diffusion towards a target only two scaling regimes emerge, separated by the ageing time. In the ageing case $t \ll t_a$ the forward waiting time is again dominant with power law exponent $-\alpha$, while the non-ageing power law $-1-\alpha$ is found for all times $t \gg t_a$. An intermediate regime does not exist. The bias and the confinement have similar effects on the first passage time density. For quenched diffusion, the biased case is interesting, as the bias reduces correlations due to revisiting of the same waiting time. As a result, CTRW like behavior is observed, including ageing. Extensive computer simulations support my findings.
The second part of my research was done on the subject of ageing Scher-Montroll transport, which is in parts closely related to the first passage densities. It explains the electrical current in an amorphous material. I have investigated the effect of the width of a given initial distribution of charge carriers on the transport coefficients as well as the ageing effect on the emerging power law regimes and a constant initial regime. While a spread out initial distribution has only little impact on the Scher-Montroll current, ageing alters the behavior drastically. Instead of the two classical power laws one finds four current regimes, up to three of which can appear in a single experiment. The dominant power laws differ for $t \ll t_a, t_c$, $t_a \ll t \ll t_c$, $t_c \ll t \ll t_a$, and $t \gg t_a,t_c$. Here, $t_c$ is the crossover time of the non-aged Scher-Montroll current. For strongly aged systems one can observe a constant current in the first regime while the others are dominated by decaying power laws with exponents $\alpha -1$, $-\alpha$, and $-1-\alpha$. The ageing regimes are the 1st and 3rd one, while the classical regimes are the 2nd and the 4th. I have verified the theory using numerical integration of the exact integrals and applied the new results to experimental data.
In the third part I considered a single file of subdiffusing particles in an energy landscape. Every occupied site of the landscape acts as a boundary, from which a particle is immediately reflected to its previous site, if it tries to jump there. I have analysed the effects single-file diffusion a quenched landscape compared to an annealed landscape and I have related these results to the number of steps and related quantities. The diffusion changes from ultraslow logarithmic diffusion in the annealed or CTRW case to subdiffusion with an anomalous exponent $\alpha/(1+\alpha)$ in the quenched landscape. The behavior is caused by the forward waiting time, which changes drastically from the quenched to the annealed case. Single-file effects in the quenched landscape are even more complicated to consider in the ensemble average, since the diffusion in individual landscapes shows extremely diverse behavior. Extensive simulations support my theoretical arguments, which consider mainly the long time evolution of the mean square displacement of a bulk particle.
In this Thesis, the properties of aqueous hemicellulose polysaccharides are investigated using computer simulations. The high swelling capacity of materials composed of these molecules allows the generation of directed motion in plant materials entirely controlled by water uptake.
To explore the molecular origin of this swelling capacity, a computational model with atomistic resolution for hemicellulose polysaccharides is build and validated in comparison with experiments. Using this model, simulations of small polysaccharides are employed to gain an understanding of the interactions of these molecules with water, the influence of water on their conformational freedom, and the swelling capacity quantified in terms of osmotic pressure. It is revealed that the branched hemicellulose polysaccharides show different hydration characteristics compared to linear polysaccharides.
To study swelling properties on length and time scales that exceed the limitations imposed by atomistic simulations, a procedure to obtain transferable coarse-grain models is developed. The transferability of the coarse-grain models over both different degrees of polymerization as well as different solute concentrations is demonstrated. Therefore, the procedure allows the construction of large coarse-grained systems based on small atomistic reference systems. Finally, the coarse-grain model is applied to demonstrate that linear and branched polysaccharides show a different swelling behavior when coupled to a water bath.
The goal of the presented work is to explore the interaction between gold nanorods (GNRs) and hyper-sound waves. For the generation of the hyper-sound I have used Azobenzene-containing polymer transducers. Multilayer polymer structures with well-defined thicknesses and smooth interfaces were built via layer-by-layer deposition. Anionic polyelectrolytes with Azobenzene side groups (PAzo) were alternated with cationic polymer PAH, for the creation of transducer films. PSS/PAH multilayer were built for spacer layers, which do not absorb in the visible light range. The properties of the PAzo/PAH film as a transducer are carefully characterized by static and transient optical spectroscopy. The optical and mechanical properties of the transducer are studied on the picosecond time scale. In particular the relative change of the refractive index of the photo-excited and expanded PAH/PAzo is Δn/n = - 2.6*10‐4. Calibration of the generated strain is performed by ultrafast X-ray diffraction calibrated the strain in a Mica substrate, into which the hyper-sound is transduced. By simulating the X-ray data with a linear-chain-model the strain in the transducer under the excitation is derived to be Δd/d ~ 5*10‐4.
Additional to the investigation of the properties of the transducer itself, I have performed a series of experiments to study the penetration of the generated strain into various adjacent materials. By depositing the PAzo/PAH film onto a PAH/PSS structure with gold nanorods incorporated in it, I have shown that nanoscale impurities can be detected via the scattering of hyper-sound.
Prior to the investigation of complex structures containing GNRs and the transducer, I have performed several sets of experiments on GNRs deposited on a small buffer of PSS/PAH. The static and transient response of GNRs is investigated for different fluence of the pump beam and for different dielectric environments (GNRs covered by PSS/PAH).
A systematic analysis of sample architectures is performed in order to construct a sample with the desired effect of GNRs responding to the hyper-sound strain wave. The observed shift of a feature related to the longitudinal plasmon resonance in the transient reflection spectra is interpreted as the event of GNRs sensing the strain wave. We argue that the shift of the longitudinal plasmon resonance is caused by the viscoelastic deformation of the polymer around the nanoparticle. The deformation is induced by the out of plane difference in strain in the area directly under a particle and next to it. Simulations based on the linear chain model support this assumption. Experimentally this assumption is proven by investigating the same structure, with GNRs embedded in a PSS/PAH polymer layer.
The response of GNRs to the hyper-sound wave is also observed for the sample structure with GNRs embedded in PAzo/PAH films. The response of GNRs in this case is explained to be driven by the change of the refractive index of PAzo during the strain propagation.
Change points in time series are perceived as heterogeneities in the statistical or dynamical characteristics of the observations. Unraveling such transitions yields essential information for the understanding of the observed system’s intrinsic evolution and potential external influences. A precise detection of multiple changes is therefore of great importance for various research disciplines, such as environmental sciences, bioinformatics and economics. The primary purpose of the detection approach introduced in this thesis is the investigation of transitions underlying direct or indirect climate observations. In order to develop a diagnostic approach capable to capture such a variety of natural processes, the generic statistical features in terms of central tendency and dispersion are employed in the light of Bayesian inversion. In contrast to established Bayesian approaches to multiple changes, the generic approach proposed in this thesis is not formulated in the framework of specialized partition models of high dimensionality requiring prior specification, but as a robust kernel-based approach of low dimensionality employing least informative prior distributions.
First of all, a local Bayesian inversion approach is developed to robustly infer on the location and the generic patterns of a single transition. The analysis of synthetic time series comprising changes of different observational evidence, data loss and outliers validates the performance, consistency and sensitivity of the inference algorithm. To systematically investigate time series for multiple changes, the Bayesian inversion is extended to a kernel-based inference approach. By introducing basic kernel measures, the weighted kernel inference results are composed into a proxy probability to a posterior distribution of multiple transitions. The detection approach is applied to environmental time series from the Nile river in Aswan and the weather station Tuscaloosa, Alabama comprising documented changes. The method’s performance confirms the approach as a powerful diagnostic tool to decipher multiple changes underlying direct climate observations.
Finally, the kernel-based Bayesian inference approach is used to investigate a set of complex terrigenous dust records interpreted as climate indicators of the African region of the Plio-Pleistocene period. A detailed inference unravels multiple transitions underlying the indirect climate observations, that are interpreted as conjoint changes. The identified conjoint changes coincide with established global climate events. In particular, the two-step transition associated to the establishment of the modern Walker-Circulation contributes to the current discussion about the influence of paleoclimate changes on the environmental conditions in tropical and subtropical Africa at around two million years ago.