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In the living cell, the organization of the complex internal structure relies to a large extent on molecular motors. Molecular motors are proteins that are able to convert chemical energy from the hydrolysis of adenosine triphosphate (ATP) into mechanical work. Being about 10 to 100 nanometers in size, the molecules act on a length scale, for which thermal collisions have a considerable impact onto their motion. In this way, they constitute paradigmatic examples of thermodynamic machines out of equilibrium. This study develops a theoretical description for the energy conversion by the molecular motor myosin V, using many different aspects of theoretical physics. Myosin V has been studied extensively in both bulk and single molecule experiments. Its stepping velocity has been characterized as a function of external control parameters such as nucleotide concentration and applied forces. In addition, numerous kinetic rates involved in the enzymatic reaction of the molecule have been determined. For forces that exceed the stall force of the motor, myosin V exhibits a 'ratcheting' behaviour: For loads in the direction of forward stepping, the velocity depends on the concentration of ATP, while for backward loads there is no such influence. Based on the chemical states of the motor, we construct a general network theory that incorporates experimental observations about the stepping behaviour of myosin V. The motor's motion is captured through the network description supplemented by a Markov process to describe the motor dynamics. This approach has the advantage of directly addressing the chemical kinetics of the molecule, and treating the mechanical and chemical processes on equal grounds. We utilize constraints arising from nonequilibrium thermodynamics to determine motor parameters and demonstrate that the motor behaviour is governed by several chemomechanical motor cycles. In addition, we investigate the functional dependence of stepping rates on force by deducing the motor's response to external loads via an appropriate Fokker-Planck equation. For substall forces, the dominant pathway of the motor network is profoundly different from the one for superstall forces, which leads to a stepping behaviour that is in agreement with the experimental observations. The extension of our analysis to Markov processes with absorbing boundaries allows for the calculation of the motor's dwell time distributions. These reveal aspects of the coordination of the motor's heads and contain direct information about the backsteps of the motor. Our theory provides a unified description for the myosin V motor as studied in single motor experiments.
The Arctic is a particularly sensitive area with respect to climate change due to the high surface albedo of snow and ice and the extreme radiative conditions. Clouds and aerosols as parts of the Arctic atmosphere play an important role in the radiation budget, which is, as yet, poorly quantified and understood. The LIDAR (Light Detection And Ranging) measurements presented in this PhD thesis contribute with continuous altitude resolved aerosol profiles to the understanding of occurrence and characteristics of aerosol layers above Ny-Ålesund, Spitsbergen. The attention was turned to the analysis of periods with high aerosol load. As the Arctic spring troposphere exhibits maximum aerosol optical depths (AODs) each year, March and April of both the years 2007 and 2009 were analyzed. Furthermore, stratospheric aerosol layers of volcanic origin were analyzed for several months, subsequently to the eruptions of the Kasatochi and Sarychev volcanoes in summer 2008 and 2009, respectively. The Koldewey Aerosol Raman LIDAR (KARL) is an instrument for the active remote sensing of atmospheric parameters using pulsed laser radiation. It is operated at the AWIPEV research base and was fundamentally upgraded within the framework of this PhD project. It is now equipped with a new telescope mirror and new detection optics, which facilitate atmospheric profiling from 450m above sea level up to the mid-stratosphere. KARL provides highly resolved profiles of the scattering characteristics of aerosol and cloud particles (backscattering, extinction and depolarization) as well as water vapor profiles within the lower troposphere. Combination of KARL data with data from other instruments on site, namely radiosondes, sun photometer, Micro Pulse LIDAR, and tethersonde system, resulted in a comprehensive data set of scattering phenomena in the Arctic atmosphere. The two spring periods March and April 2007 and 2009 were at first analyzed based on meteorological parameters, like local temperature and relative humidity profiles as well as large scale pressure patterns and air mass origin regions. Here, it was not possible to find a clear correlation between enhanced AOD and air mass origin. However, in a comparison of two cloud free periods in March 2007 and April 2009, large AOD values in 2009 coincided with air mass transport through the central Arctic. This suggests the occurrence of aerosol transformation processes during the aerosol transport to Ny-Ålesund. Measurements on 4 April 2009 revealed maximum AOD values of up to 0.12 and aerosol size distributions changing with altitude. This and other performed case studies suggest the differentiation between three aerosol event types and their origin: Vertically limited aerosol layers in dry air, highly variable hygroscopic boundary layer aerosols and enhanced aerosol load across wide portions of the troposphere. For the spring period 2007, the available KARL data were statistically analyzed using a characterization scheme, which is based on optical characteristics of the scattering particles. The scheme was validated using several case studies. Volcanic eruptions in the northern hemisphere in August 2008 and June 2009 arose the opportunity to analyze volcanic aerosol layers within the stratosphere. The rate of stratospheric AOD change was similar within both years with maximum values above 0.1 about three to five weeks after the respective eruption. In both years, the stratospheric AOD persisted at higher rates than usual until the measurements were stopped in late September due to technical reasons. In 2008, up to three aerosol layers were detected, the layer structure in 2009 was characterized by up to six distinct and thin layers which smeared out to one broad layer after about two months. The lowermost aerosol layer was continuously detected at the tropopause altitude. Three case studies were performed, all revealed rather large indices of refraction of m = (1.53–1.55) - 0.02i, suggesting the presence of an absorbing carbonaceous component. The particle radius, derived with inversion calculations, was also similar in both years with values ranging from 0.16 to 0.19 μm. However, in 2009, a second mode in the size distribution was detected at about 0.5 μm. The long term measurements with the Koldewey Aerosol Raman LIDAR in Ny-Ålesund provide the opportunity to study Arctic aerosols in the troposphere and the stratosphere not only in case studies but on longer time scales. In this PhD thesis, both, tropospheric aerosols in the Arctic spring and stratospheric aerosols following volcanic eruptions have been described qualitatively and quantitatively. Case studies and comparative studies with data of other instruments on site allowed for the analysis of microphysical aerosol characteristics and their temporal evolution.
The Greenland Ice Sheet (GIS) contains enough water volume to raise global sea level by over 7 meters. It is a relic of past glacial climates that could be strongly affected by a warming world. Several studies have been performed to investigate the sensitivity of the ice sheet to changes in climate, but large uncertainties in its long-term response still exist. In this thesis, a new approach has been developed and applied to modeling the GIS response to climate change. The advantages compared to previous approaches are (i) that it can be applied over a wide range of climatic scenarios (both in the deep past and the future), (ii) that it includes the relevant feedback processes between the climate and the ice sheet and (iii) that it is highly computationally efficient, allowing simulations over very long timescales. The new regional energy-moisture balance model (REMBO) has been developed to model the climate and surface mass balance over Greenland and it represents an improvement compared to conventional approaches in modeling present-day conditions. Furthermore, the evolution of the GIS has been simulated over the last glacial cycle using an ensemble of model versions. The model performance has been validated against field observations of the present-day climate and surface mass balance, as well as paleo information from ice cores. The GIS contribution to sea level rise during the last interglacial is estimated to be between 0.5-4.1 m, consistent with previous estimates. The ensemble of model versions has been constrained to those that are consistent with the data, and a range of valid parameter values has been defined, allowing quantification of the uncertainty and sensitivity of the modeling approach. Using the constrained model ensemble, the sensitivity of the GIS to long-term climate change was investigated. It was found that the GIS exhibits hysteresis behavior (i.e., it is multi-stable under certain conditions), and that a temperature threshold exists above which the ice sheet transitions to an essentially ice-free state. The threshold in the global temperature is estimated to be in the range of 1.3-2.3°C above preindustrial conditions, significantly lower than previously believed. The timescale of total melt scales non-linearly with the overshoot above the temperature threshold, such that a 2°C anomaly causes the ice sheet to melt in ca. 50,000 years, but an anomaly of 6°C will melt the ice sheet in less than 4,000 years. The meltback of the ice sheet was found to become irreversible after a fraction of the ice sheet is already lost – but this level of irreversibility also depends on the temperature anomaly.
Complex network theory provides an elegant and powerful framework to statistically investigate the topology of local and long range dynamical interrelationships, i.e., teleconnections, in the climate system. Employing a refined methodology relying on linear and nonlinear measures of time series analysis, the intricate correlation structure within a multivariate climatological data set is cast into network form. Within this graph theoretical framework, vertices are identified with grid points taken from the data set representing a region on the the Earth's surface, and edges correspond to strong statistical interrelationships between the dynamics on pairs of grid points. The resulting climate networks are neither perfectly regular nor completely random, but display the intriguing and nontrivial characteristics of complexity commonly found in real world networks such as the internet, citation and acquaintance networks, food webs and cortical networks in the mammalian brain. Among other interesting properties, climate networks exhibit the "small-world" effect and possess a broad degree distribution with dominating super-nodes as well as a pronounced community structure. We have performed an extensive and detailed graph theoretical analysis of climate networks on the global topological scale focussing on the flow and centrality measure betweenness which is locally defined at each vertex, but includes global topological information by relying on the distribution of shortest paths between all pairs of vertices in the network. The betweenness centrality field reveals a rich internal structure in complex climate networks constructed from reanalysis and atmosphere-ocean coupled general circulation model (AOGCM) surface air temperature data. Our novel approach uncovers an elaborately woven meta-network of highly localized channels of strong dynamical information flow, that we relate to global surface ocean currents and dub the backbone of the climate network in analogy to the homonymous data highways of the internet. This finding points to a major role of the oceanic surface circulation in coupling and stabilizing the global temperature field in the long term mean (140 years for the model run and 60 years for reanalysis data). Carefully comparing the backbone structures detected in climate networks constructed using linear Pearson correlation and nonlinear mutual information, we argue that the high sensitivity of betweenness with respect to small changes in network structure may allow to detect the footprints of strongly nonlinear physical interactions in the climate system. The results presented in this thesis are thoroughly founded and substantiated using a hierarchy of statistical significance tests on the level of time series and networks, i.e., by tests based on time series surrogates as well as network surrogates. This is particularly relevant when working with real world data. Specifically, we developed new types of network surrogates to include the additional constraints imposed by the spatial embedding of vertices in a climate network. Our methodology is of potential interest for a broad audience within the physics community and various applied fields, because it is universal in the sense of being valid for any spatially extended dynamical system. It can help to understand the localized flow of dynamical information in any such system by combining multivariate time series analysis, a complex network approach and the information flow measure betweenness centrality. Possible fields of application include fluid dynamics (turbulence), plasma physics and biological physics (population models, neural networks, cell models). Furthermore, the climate network approach is equally relevant for experimental data as well as model simulations and hence introduces a novel perspective on model evaluation and data driven model building. Our work is timely in the context of the current debate on climate change within the scientific community, since it allows to assess from a new perspective the regional vulnerability and stability of the climate system while relying on global and not only on regional knowledge. The methodology developed in this thesis hence has the potential to substantially contribute to the understanding of the local effect of extreme events and tipping points in the earth system within a holistic global framework.
Supernovae are known to be the dominant energy source for driving turbulence in the interstellar medium. Yet, their effect on magnetic field amplification in spiral galaxies is still poorly understood. Analytical models based on the uncorrelated-ensemble approach predicted that any created field will be expelled from the disk before a significant amplification can occur. By means of direct simulations of supernova-driven turbulence, we demonstrate that this is not the case. Accounting for vertical stratification and galactic differential rotation, we find an exponential amplification of the mean field on timescales of 100Myr. The self-consistent numerical verification of such a “fast dynamo” is highly beneficial in explaining the observed strong magnetic fields in young galaxies. We, furthermore, highlight the importance of rotation in the generation of helicity by showing that a similar mechanism based on Cartesian shear does not lead to a sustained amplification of the mean magnetic field. This finding impressively confirms the classical picture of a dynamo based on cyclonic turbulence.
Die Arbeit beschreibt die Analyse von Beobachtungen zweier Sonnenflecken in zweidimensionaler Spektro-Polarimetrie. Die Daten wurden mit dem Fabry-Pérot-Interferometer der Universität Göttingen am Vakuum-Turm-Teleskop auf Teneriffa erfasst. Von der aktiven Region NOAA 9516 wurde der volle Stokes-Vektor des polarisierten Lichts in der Absorptionslinie bei 630,249 nm in Einzelaufnahmen beobachtet, und von der aktiven Region NOAA 9036 wurde bei 617,3 nm Wellenlänge eine 90-minütige Zeitserie des zirkular polarisierten Lichts aufgezeichnet. Aus den reduzierten Daten werden Ergebniswerte für Intensität, Geschwindigkeit in Beobachtungsrichtung, magnetische Feldstärke sowie verschiedene weitere Plasmaparameter abgeleitet. Mehrere Ansätze zur Inversion solarer Modellatmosphären werden angewendet und verglichen. Die teilweise erheblichen Fehlereinflüsse werden ausführlich diskutiert. Das Frequenzverhalten der Ergebnisse und Abhängigkeiten nach Ort und Zeit werden mit Hilfe der Fourier- und Wavelet-Transformation weiter analysiert. Als Resultat lässt sich die Existenz eines hochfrequenten Bandes für Geschwindigkeitsoszillationen mit einer zentralen Frequenz von 75 Sekunden (13 mHz) bestätigen. In größeren photosphärischen Höhen von etwa 500 km entstammt die Mehrheit der damit zusammenhängenden Schockwellen den dunklen Anteilen der Granulen, im Unterschied zu anderen Frequenzbereichen. Die 75-Sekunden-Oszillationen werden ebenfalls in der aktiven Region beobachtet, vor allem in der Lichtbrücke. In den identifizierten Bändern oszillatorischer Power der Geschwindigkeit sind in einer dunklen, penumbralen Struktur sowie in der Lichtbrücke ausgeprägte Strukturen erkennbar, die sich mit einer Horizontalgeschwindigkeit von 5-8 km/s in die ruhige Sonne bewegen. Diese zeigen einen deutlichen Anstieg der Power, vor allem im 5-Minuten-Band, und stehen möglicherweise in Zusammenhang mit dem Phänomen der „Evershed-clouds“. Eingeschränkt durch ein sehr geringes Signal-Rausch-Verhältnis und hohe Fehlereinflüsse werden auch Magnetfeldvariationen mit einer Periode von sechs Minuten am Übergang von Umbra zu Penumbra in der Nähe einer Lichtbrücke beobachtet. Um die beschriebenen Resultate zu erzielen, wurden bestehende Visualisierungsverfahren der Frequenzanalyse verbessert oder neu entwickelt, insbesondere für Ergebnisse der Wavelet-Transformation.
In order to investigate the temporal characteristics of cognitive processing, we apply multivariate phase synchronization analysis to event-related potentials. The experimental design combines a semantic incongruity in a sentence context with a physical mismatch (color change). In the ERP average, these result in an N400 component and a P300-like positivity, respectively. The synchronization analysis shows an effect of global desynchronization in the theta band around 288ms after stimulus presentation for the semantic incongruity, while the physical mismatch elicits an increase of global synchronization in the alpha band around 204ms. Both of these effects clearly precede those in the ERP average. Moreover, the delay between synchronization effect and ERP component correlates with the complexity of the cognitive processes.
In biological cells, the long-range intracellular traffic is powered by molecular motors which transport various cargos along microtubule filaments. The microtubules possess an intrinsic direction, having a 'plus' and a 'minus' end. Some molecular motors such as cytoplasmic dynein walk to the minus end, while others such as conventional kinesin walk to the plus end. Cells typically have an isopolar microtubule network. This is most pronounced in neuronal axons or fungal hyphae. In these long and thin tubular protrusions, the microtubules are arranged parallel to the tube axis with the minus ends pointing to the cell body and the plus ends pointing to the tip. In such a tubular compartment, transport by only one motor type leads to 'motor traffic jams'. Kinesin-driven cargos accumulate at the tip, while dynein-driven cargos accumulate near the cell body. We identify the relevant length scales and characterize the jamming behaviour in these tube geometries by using both Monte Carlo simulations and analytical calculations. A possible solution to this jamming problem is to transport cargos with a team of plus and a team of minus motors simultaneously, so that they can travel bidirectionally, as observed in cells. The presumably simplest mechanism for such bidirectional transport is provided by a 'tug-of-war' between the two motor teams which is governed by mechanical motor interactions only. We develop a stochastic tug-of-war model and study it with numerical and analytical calculations. We find a surprisingly complex cooperative motility behaviour. We compare our results to the available experimental data, which we reproduce qualitatively and quantitatively.
Mass accretion onto compact objects through accretion disks is a common phenomenon in the universe. It is seen in all energy domains from active galactic nuclei through cataclysmic variables (CVs) to young stellar objects. Because CVs are fairly easy to observe, they provide an ideal opportunity to study accretion disks in great detail and thus help us to understand accretion also in other energy ranges. Mass accretion in these objects is often accompanied by mass outflow from the disks. This accretion disk wind, at least in CVs, is thought to be radiatively driven, similar to O star winds. WOMPAT, a 3-D Monte Carlo radiative transfer code for accretion disk winds of CVs is presented.
Stellar winds play an important role for the evolution of massive stars and their cosmic environment. Multiple lines of evidence, coming from spectroscopy, polarimetry, variability, stellar ejecta, and hydrodynamic modeling, suggest that stellar winds are non-stationary and inhomogeneous. This is referred to as 'wind clumping'. The urgent need to understand this phenomenon is boosted by its far-reaching implications. Most importantly, all techniques to derive empirical mass-loss rates are more or less corrupted by wind clumping. Consequently, mass-loss rates are extremely uncertain. Within their range of uncertainty, completely different scenarios for the evolution of massive stars are obtained. Settling these questions for Galactic OB, LBV and Wolf-Rayet stars is prerequisite to understanding stellar clusters and galaxies, or predicting the properties of first-generation stars. In order to develop a consistent picture and understanding of clumped stellar winds, an international workshop on 'Clumping in Hot Star Winds' was held in Potsdam, Germany, from 18. - 22. June 2007. About 60 participants, comprising almost all leading experts in the field, gathered for one week of extensive exchange and discussion. The Scientific Organizing Committee (SOC) included John Brown (Glasgow), Joseph Cassinelli (Madison), Paul Crowther (Sheffield), Alex Fullerton (Baltimore), Wolf-Rainer Hamann (Potsdam, chair), Anthony Moffat (Montreal), Stan Owocki (Newark), and Joachim Puls (Munich). These proceedings contain the invited and contributed talks presented at the workshop, and document the extensive discussions.
During the last few years there was a tremendous growth of scientific activities in the fields related to both Physics and Control theory: nonlinear dynamics, micro- and nanotechnologies, self-organization and complexity, etc. New horizons were opened and new exciting applications emerged. Experts with different backgrounds starting to work together need more opportunities for information exchange to improve mutual understanding and cooperation. The Conference "Physics and Control 2007" is the third international conference focusing on the borderland between Physics and Control with emphasis on both theory and applications. With its 2007 address at Potsdam, Germany, the conference is located for the first time outside of Russia. The major goal of the Conference is to bring together researchers from different scientific communities and to gain some general and unified perspectives in the studies of controlled systems in physics, engineering, chemistry, biology and other natural sciences. We hope that the Conference helps experts in control theory to get acquainted with new interesting problems, and helps experts in physics and related fields to know more about ideas and tools from the modern control theory.
A numerical bifurcation analysis of the electrically driven plane sheet pinch is presented. The electrical conductivity varies across the sheet such as to allow instability of the quiescent basic state at some critical Hartmann number. The most unstable perturbation is the two-dimensional tearing mode. Restricting the whole problem to two spatial dimensions, this mode is followed up to a time-asymptotic steady state, which proves to be sensitive to three-dimensional perturbations even close to the point where the primary instability sets in. A comprehensive three-dimensional stability analysis of the two-dimensional steady tearing-mode state is performed by varying parameters of the sheet pinch. The instability with respect to three-dimensional perturbations is suppressed by a sufficiently strong magnetic field in the invariant direction of the equilibrium. For a special choice of the system parameters, the unstably perturbed state is followed up in its nonlinear evolution and is found to approach a three-dimensional steady state.
We investigate numerically the appearance of heteroclinic behavior in a three-dimensional, buoyancy-driven fluid layer with stress-free top and bottom boundaries, a square horizontal periodicity with a small aspect ratio, and rotation at low to moderate rates about a vertical axis. The Prandtl number is 6.8. If the rotation is not too slow, the skewed-varicose instability leads from stationary rolls to a stationary mixed-mode solution, which in turn loses stability to a heteroclinic cycle formed by unstable roll states and connections between them. The unstable eigenvectors of these roll states are also of the skewed-varicose or mixed-mode type and in some parameter regions skewed-varicose like shearing oscillations as well as square patterns are involved in the cycle. Always present weak noise leads to irregular horizontal translations of the convection pattern and makes the dynamics chaotic, which is verified by calculating Lyapunov exponents. In the nonrotating case, the primary rolls lose, depending on the aspect ratio, stability to traveling waves or a stationary square pattern. We also study the symmetries of the solutions at the intermittent fixed points in the heteroclinic cycle.
Our dynamic Sun manifests its activity by different phenomena: from the 11-year cyclic sunspot pattern to the unpredictable and violent explosions in the case of solar flares. During flares, a huge amount of the stored magnetic energy is suddenly released and a substantial part of this energy is carried by the energetic electrons, considered to be the source of the nonthermal radio and X-ray radiation. One of the most important and still open question in solar physics is how the electrons are accelerated up to high energies within (the observed in the radio emission) short time scales. Because the acceleration site is extremely small in spatial extent as well (compared to the solar radius), the electron acceleration is regarded as a local process. The search for localized wave structures in the solar corona that are able to accelerate electrons together with the theoretical and numerical description of the conditions and requirements for this process, is the aim of the dissertation. Two models of electron acceleration in the solar corona are proposed in the dissertation: I. Electron acceleration due to the solar jet interaction with the background coronal plasma (the jet--plasma interaction) A jet is formed when the newly reconnected and highly curved magnetic field lines are relaxed by shooting plasma away from the reconnection site. Such jets, as observed in soft X-rays with the Yohkoh satellite, are spatially and temporally associated with beams of nonthermal electrons (in terms of the so-called type III metric radio bursts) propagating through the corona. A model that attempts to give an explanation for such observational facts is developed here. Initially, the interaction of such jets with the background plasma leads to an (ion-acoustic) instability associated with growing of electrostatic fluctuations in time for certain range of the jet initial velocity. During this process, any test electron that happen to feel this electrostatic wave field is drawn to co-move with the wave, gaining energy from it. When the jet speed has a value greater or lower than the one, required by the instability range, such wave excitation cannot be sustained and the process of electron energization (acceleration and/or heating) ceases. Hence, the electrons can propagate further in the corona and be detected as type III radio burst, for example. II. Electron acceleration due to attached whistler waves in the upstream region of coronal shocks (the electron--whistler--shock interaction) Coronal shocks are also able to accelerate electrons, as observed by the so-called type II metric radio bursts (the radio signature of a shock wave in the corona). From in-situ observations in space, e.g., at shocks related to co-rotating interaction regions, it is known that nonthermal electrons are produced preferably at shocks with attached whistler wave packets in their upstream regions. Motivated by these observations and assuming that the physical processes at shocks are the same in the corona as in the interplanetary medium, a new model of electron acceleration at coronal shocks is presented in the dissertation, where the electrons are accelerated by their interaction with such whistlers. The protons inflowing toward the shock are reflected there by nearly conserving their magnetic moment, so that they get a substantial velocity gain in the case of a quasi-perpendicular shock geometry, i.e, the angle between the shock normal and the upstream magnetic field is in the range 50--80 degrees. The so-accelerated protons are able to excite whistler waves in a certain frequency range in the upstream region. When these whistlers (comprising the localized wave structure in this case) are formed, only the incoming electrons are now able to interact resonantly with them. But only a part of these electrons fulfill the the electron--whistler wave resonance condition. Due to such resonant interaction (i.e., of these electrons with the whistlers), the electrons are accelerated in the electric and magnetic wave field within just several whistler periods. While gaining energy from the whistler wave field, the electrons reach the shock front and, subsequently, a major part of them are reflected back into the upstream region, since the shock accompanied with a jump of the magnetic field acts as a magnetic mirror. Co-moving with the whistlers now, the reflected electrons are out of resonance and hence can propagate undisturbed into the far upstream region, where they are detected in terms of type II metric radio bursts. In summary, the kinetic energy of protons is transfered into electrons by the action of localized wave structures in both cases, i.e., at jets outflowing from the magnetic reconnection site and at shock waves in the corona.
The Voyager 2 Photopolarimeter experiment has yielded the highest resolved data of Saturn's rings, exhibiting a wide variety of features. The B-ring region between 105000 km and 110000 km distance from Saturn has been investigated. It has a high matter density and contains no significance features visible by eye. Analysis with statistical methods has let us to the detection of two significant events. These features are correlated with the inner 3:2 resonances of the F-ring shepherd satellites Pandora and Prometheus, and may be evidence of large ring paricles caught in the corotation resonances.
It is desirable to reduce the potential threats that result from the variability of nature, such as droughts or heat waves that lead to food shortage, or the other extreme, floods that lead to severe damage. To prevent such catastrophic events, it is necessary to understand, and to be capable of characterising, nature's variability. Typically one aims to describe the underlying dynamics of geophysical records with differential equations. There are, however, situations where this does not support the objectives, or is not feasible, e.g., when little is known about the system, or it is too complex for the model parameters to be identified. In such situations it is beneficial to regard certain influences as random, and describe them with stochastic processes. In this thesis I focus on such a description with linear stochastic processes of the FARIMA type and concentrate on the detection of long-range dependence. Long-range dependent processes show an algebraic (i.e. slow) decay of the autocorrelation function. Detection of the latter is important with respect to, e.g. trend tests and uncertainty analysis. Aiming to provide a reliable and powerful strategy for the detection of long-range dependence, I suggest a way of addressing the problem which is somewhat different from standard approaches. Commonly used methods are based either on investigating the asymptotic behaviour (e.g., log-periodogram regression), or on finding a suitable potentially long-range dependent model (e.g., FARIMA[p,d,q]) and test the fractional difference parameter d for compatibility with zero. Here, I suggest to rephrase the problem as a model selection task, i.e.comparing the most suitable long-range dependent and the most suitable short-range dependent model. Approaching the task this way requires a) a suitable class of long-range and short-range dependent models along with suitable means for parameter estimation and b) a reliable model selection strategy, capable of discriminating also non-nested models. With the flexible FARIMA model class together with the Whittle estimator the first requirement is fulfilled. Standard model selection strategies, e.g., the likelihood-ratio test, is for a comparison of non-nested models frequently not powerful enough. Thus, I suggest to extend this strategy with a simulation based model selection approach suitable for such a direct comparison. The approach follows the procedure of a statistical test, with the likelihood-ratio as the test statistic. Its distribution is obtained via simulations using the two models under consideration. For two simple models and different parameter values, I investigate the reliability of p-value and power estimates obtained from the simulated distributions. The result turned out to be dependent on the model parameters. However, in many cases the estimates allow an adequate model selection to be established. An important feature of this approach is that it immediately reveals the ability or inability to discriminate between the two models under consideration. Two applications, a trend detection problem in temperature records and an uncertainty analysis for flood return level estimation, accentuate the importance of having reliable methods at hand for the detection of long-range dependence. In the case of trend detection, falsely concluding long-range dependence implies an underestimation of a trend and possibly leads to a delay of measures needed to take in order to counteract the trend. Ignoring long-range dependence, although present, leads to an underestimation of confidence intervals and thus to an unjustified belief in safety, as it is the case for the return level uncertainty analysis. A reliable detection of long-range dependence is thus highly relevant in practical applications. Examples related to extreme value analysis are not limited to hydrological applications. The increased uncertainty of return level estimates is a potentially problem for all records from autocorrelated processes, an interesting examples in this respect is the assessment of the maximum strength of wind gusts, which is important for designing wind turbines. The detection of long-range dependence is also a relevant problem in the exploration of financial market volatility. With rephrasing the detection problem as a model selection task and suggesting refined methods for model comparison, this thesis contributes to the discussion on and development of methods for the detection of long-range dependence.
In the modern industrialized countries every year several hundred thousands of people die due to the sudden cardiac death. The individual risk for this sudden cardiac death cannot be defined precisely by common available, non-invasive diagnostic tools like Holter-monitoring, highly amplified ECG and traditional linear analysis of heart rate variability (HRV). Therefore, we apply some rather unconventional methods of nonlinear dynamics to analyse the HRV. Especially, some complexity measures that are basing on symbolic dynamics as well as a new measure, the renormalized entropy, detect some abnormalities in the HRV of several patients who have been classified in the low risk group by traditional methods. A combination of these complexity measures with the parameters in the frequency domain seems to be a promising way to get a more precise definition of the individual risk. These findings have to be validated by a representative number of patients.
We have used techniques of nonlinear dynamics to compare a special model for the reversals of the Earth's magnetic field with the observational data. Although this model is rather simple, there is no essential difference to the data by means of well-known characteristics, such as correlation function and probability distribution. Applying methods of symbolic dynamics we have found that the considered model is not able to describe the dynamical properties of the observed process. These significant differences are expressed by algorithmic complexity and Renyi information.
I perform and analyse the first ever calculations of rotating stellar iron core collapse in {3+1} general relativity that start out with presupernova models from stellar evolutionary calculations and include a microphysical finite-temperature nuclear equation of state, an approximate scheme for electron capture during collapse and neutrino pressure effects. Based on the results of these calculations, I obtain the to-date most realistic estimates for the gravitational wave signal from collapse, bounce and the early postbounce phase of core collapse supernovae. I supplement my {3+1} GR hydrodynamic simulations with 2D Newtonian neutrino radiation-hydrodynamic supernova calculations focussing on (1) the late postbounce gravitational wave emission owing to convective overturn, anisotropic neutrino emission and protoneutron star pulsations, and (2) on the gravitational wave signature of accretion-induced collapse of white dwarfs to neutron stars.