530 Physik
Refine
Year of publication
- 2016 (19) (remove)
Document Type
- Doctoral Thesis (19) (remove)
Is part of the Bibliography
- yes (19)
Keywords
- hypersound (2)
- ultrafast (2)
- (sub-) tropical Africa (1)
- (sub-) tropisches Afrika (1)
- Anharmonizität (1)
- Arctic atmosphere (1)
- Azobenzene (1)
- Bildanalyse (1)
- Bodenfeuchte (1)
- Brillouin scattering (1)
Changes in extratropical storm track activity and their implications for extreme weather events
(2016)
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.
The cell interior is a highly packed environment in which biological macromolecules evolve and function. This crowded media has effects in many biological processes such as protein-protein binding, gene regulation, and protein folding. Thus, biochemical reactions that take place in such crowded conditions differ from diluted test tube conditions, and a considerable effort has been invested in order to understand such differences.
In this work, we combine different computationally tools to disentangle the effects of molecular crowding on biochemical processes. First, we propose a lattice model to study the implications of molecular crowding on enzymatic reactions. We provide a detailed picture of how crowding affects binding and unbinding events and how the separate effects of crowding on binding equilibrium act together. Then, we implement a lattice model to study the effects of molecular crowding on facilitated diffusion. We find that obstacles on the DNA impair facilitated diffusion. However, the extent of this effect depends on how dynamic obstacles are on the DNA. For the scenario in which crowders are only present in the bulk solution, we find that at some conditions presence of crowding agents can enhance specific-DNA binding. Finally, we make use of structure-based techniques to look at the impact of the presence of crowders on the folding a protein. We find that polymeric crowders have stronger effects on protein stability than spherical crowders. The strength of this effect increases as the polymeric crowders become longer. The methods we propose here are general and can also be applied to more complicated systems.
Thermophony in real gases
(2016)
A thermophone is an electrical device for sound generation. The advantages of thermophones over conventional sound transducers such as electromagnetic, electrostatic or piezoelectric transducers are their operational principle which does not require any moving parts, their resonance-free behavior, their simple construction and their low production costs.
In this PhD thesis, a novel theoretical model of thermophonic sound generation in real gases has been developed. The model is experimentally validated in a frequency range from 2 kHz to 1 MHz by testing more then fifty thermophones of different materials, including Carbon nano-wires, Titanium, Indium-Tin-Oxide, different sizes and shapes for sound generation in gases such as air, argon, helium, oxygen, nitrogen and sulfur hexafluoride.
Unlike previous approaches, the presented model can be applied to different kinds of thermophones and various gases, taking into account the thermodynamic properties of thermophone materials and of adjacent gases, degrees of freedom and the volume occupied by the gas atoms and molecules, as well as sound attenuation effects, the shape and size of the thermophone surface and the reduction of the generated acoustic power due to photonic emission. As a result, the model features better prediction accuracy than the existing models by a factor up to 100. Moreover, the new model explains previous experimental findings on thermophones which can not be explained with the existing models.
The acoustic properties of the thermophones have been tested in several gases using unique, highly precise experimental setups comprising a Laser-Doppler-Vibrometer combined with a thin polyethylene film which acts as a broadband and resonance-free sound-pressure detector. Several outstanding properties of the thermophones have been demonstrated for the first time, including the ability to generate arbitrarily shaped acoustic signals, a greater acoustic efficiency compared to conventional piezoelectric and electrostatic airborne ultrasound transducers, and applicability as powerful and tunable sound sources with a bandwidth up to the megahertz range and beyond.
Additionally, new applications of thermophones such as the study of physical properties of gases, the thermo-acoustic gas spectroscopy, broad-band characterization of transfer functions of sound and ultrasound detection systems, and applications in non-destructive materials testing are discussed and experimentally demonstrated.
The cytoskeleton is an essential component of living cells. It is composed of different types of protein filaments that form complex, dynamically rearranging, and interconnected networks. The cytoskeleton serves a multitude of cellular functions which further depend on the cell context. In animal cells, the cytoskeleton prominently shapes the cell's mechanical properties and movement. In plant cells, in contrast, the presence of a rigid cell wall as well as their larger sizes highlight the role of the cytoskeleton in long-distance intracellular transport. As it provides the basis for cell growth and biomass production, cytoskeletal transport in plant cells is of direct environmental and economical relevance. However, while knowledge about the molecular details of the cytoskeletal transport is growing rapidly, the organizational principles that shape these processes on a whole-cell level remain elusive.
This thesis is devoted to the following question: How does the complex architecture of the plant cytoskeleton relate to its transport functionality? The answer requires a systems level perspective of plant cytoskeletal structure and transport. To this end, I combined state-of-the-art confocal microscopy, quantitative digital image analysis, and mathematically powerful, intuitively accessible graph-theoretical approaches.
This thesis summarizes five of my publications that shed light on the plant cytoskeleton as a transportation network: (1) I developed network-based frameworks for accurate, automated quantification of cytoskeletal structures, applicable in, e.g., genetic or chemical screens; (2) I showed that the actin cytoskeleton displays properties of efficient transport networks, hinting at its biological design principles; (3) Using multi-objective optimization, I demonstrated that different plant cell types sustain cytoskeletal networks with cell-type specific and near-optimal organization; (4) By investigating actual transport of organelles through the cell, I showed that properties of the actin cytoskeleton are predictive of organelle flow and provided quantitative evidence for a coordination of transport at a cellular level; (5) I devised a robust, optimization-based method to identify individual cytoskeletal filaments from a given network representation, allowing the investigation of single filament properties in the network context. The developed methods were made publicly available as open-source software tools.
Altogether, my findings and proposed frameworks provide quantitative, system-level insights into intracellular transport in living cells. Despite my focus on the plant cytoskeleton, the established combination of experimental and theoretical approaches is readily applicable to different organisms. Despite the necessity of detailed molecular studies, only a complementary, systemic perspective, as presented here, enables both understanding of cytoskeletal function in its evolutionary context as well as its future technological control and utilization.
This publications-based thesis summarizes my contribution to the scientific field of ultrafast structural dynamics. It consists of 16 publications, about the generation, detection and coupling of coherent gigahertz longitudinal acoustic phonons, also called hypersonic waves. To generate such high frequency phonons, femtosecond near infrared laser pulses were used to heat nanostructures composed of perovskite oxides on an ultrashort timescale. As a consequence the heated regions of such a nanostructure expand and a high frequency acoustic phonon pulse is generated. To detect such coherent acoustic sound pulses I use ultrafast variants of optical Brillouin and x-ray scattering. Here an incident optical or x-ray photon is scattered by the excited sound wave in the sample. The scattered light intensity measures the occupation of the phonon modes.
The central part of this work is the investigation of coherent high amplitude phonon wave packets which can behave nonlinearly, quite similar to shallow water waves which show a steepening of wave fronts or solitons well known as tsunamis. Due to the high amplitude of the acoustic wave packets in the solid, the acoustic properties can change significantly in the vicinity of the sound pulse. This may lead to a shape change of the pulse. I have observed by time-resolved Brillouin scattering, that a single cycle hypersound pulse shows a wavefront steepening. I excited hypersound pulses with strain amplitudes until 1% which I have calibrated by ultrafast x-ray diffraction (UXRD).
On the basis of this first experiment we developed the idea of the nonlinear mixing of narrowband phonon wave packets which we call "nonlinear phononics" in analogy with the nonlinear optics, which summarizes a kaleidoscope of surprising optical phenomena showing up at very high electric fields. Such phenomena are for instance Second Harmonic Generation, four-wave-mixing or solitons. But in case of excited coherent phonons the wave packets have usually very broad spectra which make it nearly impossible to look at elementary scattering processes between phonons with certain momentum and energy.
For that purpose I tested different techniques to excite narrowband phonon wave packets which mainly consist of phonons with a certain momentum and frequency. To this end epitaxially grown metal films on a dielectric substrate were excited with a train of laser pulses. These excitation pulses drive the metal film to oscillate with the frequency given by their inverse temporal displacement and send a hypersonic wave of this frequency into the substrate. The monochromaticity of these wave packets was proven by ultrafast optical Brillouin and x-ray scattering.
Using the excitation of such narrowband phonon wave packets I was able to observe the Second Harmonic Generation (SHG) of coherent phonons as a first example of nonlinear wave mixing of nanometric phonon wave packets.
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.
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.