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The interaction between surfaces displaying end-grafted hydrophilic polymer brushes plays important roles in biology and in many wet-technological applications. The outer surfaces of Gram-negative bacteria, for example, are composed of lipopolysaccharide (LPS) molecules exposing oligo- and polysaccharides to the aqueous environment. This unique, structurally complex biological interface is of great scientific interest as it mediates the interaction of bacteria with neighboring bacteria in colonies and biofilms. The interaction between polymer-decorated surfaces is generally coupled to the distance-dependent conformation of the polymer chains. Therefore, structural insight into the interacting surfaces is a prerequisite to understand the interaction characteristics as well as the underlying physical mechanisms. This problem has been addressed by theory, but accurate experimental data on polymer conformations under confinement are rare, because obtaining perturbation-free structural insight into buried soft interfaces is inherently difficult.
In this thesis, lipid membrane surfaces decorated with hydrophilic polymers of technological and biological relevance are investigated under controlled interaction conditions, i.e., at defined surface separations. For this purpose, dedicated sample architectures and experimental tools are developed. Via ellipsometry and neutron reflectometry pressure-distance curves and distance-dependent polymer conformations in terms of brush compression and reciprocative interpenetration are determined. Additional element-specific structural insight into the end-point distribution of interacting brushes is obtained by standing-wave x-ray fluorescence (SWXF).
The methodology is first established for poly[ethylene glycol] (PEG) brushes of defined length and grafting density. For this system, neutron reflectometry revealed pronounced brush interpenetration, which is not captured in common brush theories and therefore motivates rigorous simulation-based treatments. In the second step the same approach is applied to realistic mimics of the outer surfaces of Gram-negative bacteria: monolayers of wild type LPSs extracted from E. Coli O55:B5 displaying strain-specific O-side chains. The neutron reflectometry experiments yield unprecedented structural insight into bacterial interactions, which are of great relevance for the properties of biofilms.
Structural dynamics of photoexcited nanolayered perovskites studied by ultrafast x-ray diffraction
(2012)
This publication-based thesis represents a contribution to the active research field of ultrafast structural dynamics in laser-excited nanostructures. The investigation of such dynamics is mandatory for the understanding of the various physical processes on microscopic scales in complex materials which have great potentials for advances in many technological applications. I theoretically and experimentally examine the coherent, incoherent and anharmonic lattice dynamics of epitaxial metal-insulator heterostructures on timescales ranging from femtoseconds up to nanoseconds. To infer information on the transient dynamics in the photoexcited crystal lattices experimental techniques using ultrashort optical and x-ray pulses are employed. The experimental setups include table-top sources as well as large-scale facilities such as synchrotron sources. At the core of my work lies the development of a linear-chain model to simulate and analyze the photoexcited atomic-scale dynamics. The calculated strain fields are then used to simulate the optical and x-ray response of the considered thin films and multilayers in order to relate the experimental signatures to particular structural processes. This way one obtains insight into the rich lattice dynamics exhibiting coherent transport of vibrational energy from local excitations via delocalized phonon modes of the samples. The complex deformations in tailored multilayers are identified to give rise to highly nonlinear x-ray diffraction responses due to transient interference effects. The understanding of such effects and the ability to precisely calculate those are exploited for the design of novel ultrafast x-ray optics. In particular, I present several Phonon Bragg Switch concepts to efficiently generate ultrashort x-ray pulses for time-resolved structural investigations. By extension of the numerical models to include incoherent phonon propagation and anharmonic lattice potentials I present a new view on the fundamental research topics of nanoscale thermal transport and anharmonic phonon-phonon interactions such as nonlinear sound propagation and phonon damping. The former issue is exemplified by the time-resolved heat conduction from thin SrRuO3 films into a SrTiO3 substrate which exhibits an unexpectedly slow heat conductivity. Furthermore, I discuss various experiments which can be well reproduced by the versatile numerical models and thus evidence strong lattice anharmonicities in the perovskite oxide SrTiO3. The thesis also presents several advances of experimental techniques such as time-resolved phonon spectroscopy with optical and x-ray photons as well as concepts for the implementation of x-ray diffraction setups at standard synchrotron beamlines with largely improved time-resolution for investigations of ultrafast structural processes. This work forms the basis for ongoing research topics in complex oxide materials including electronic correlations and phase transitions related to the elastic, magnetic and polarization degrees of freedom.
Nowadays, colloidal rods can be synthesized in large amounts. The rods are typically cylindrically and their length ranges from several nanometers to a few micrometers. In solution, systems of colloidal rodlike molecules or aggregates can form liquid-crystalline phases with long-range orientational and spatial order. In the present work, we investigate structure formation and fractionation in systems of rodlike colloids with the help of Monte Carlo simulations in the NPT ensemble. Repulsive interactions can successfully be mimicked by the hard rod model, which has been studied extensively in the past. In many cases, attractive interactions like van der Waals or depletion forces cannot be neglected, however. In the first part of this work, the phase behavior of monodisperse attractive rods is characterized for different interaction strengths. Phase diagrams as a function of rod length and pressure are presented. Most systems of synthesized mesoscopic rods have a polydisperse length distribution as a consequence of the longitudinal growth process of the rods. For many technical and research applications, a rather small polydispersity is desired in order to have well defined material properties. The polydispersity can be reduced by a spatial demixing (fractionation) of long and short rods. Fractionation and structure formation is studied in a tridisperse and a polydisperse bulk suspension of rods. We observe that the resulting structures depend distinctly on the interaction strength. The fractionation in the system is strongly enhanced with increasing interaction strength. Suspensions are typically confined in a container. We also examine the influence of adjacent substrates in systems of tridisperse and polydisperse rod suspensions. Three different substrate types are studied in detail: a planar wall, a corrugated substrate, and a substrate with rectangular cavities. We analyze the fluid structure close to the substrate and substrate controlled fractionation. The spatial arrangement of long and short rods in front of the substrate depends sensitively on the substrate structure and the pressure. Rods with a predefined length are segregated at substrates with rectangular cavities.
The mammalian brain is, with its numerous neural elements and structured complex connectivity, one of the most complex systems in nature. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex networks. Here, we try to shed some light on the relationship between structural and functional connectivities by studying synchronization dynamics in a realistic anatomical network of cat cortical connectivity. We model the cortical areas by a subnetwork of interacting excitable neurons (multilevel model) and by a neural mass model (population model). With weak couplings, the multilevel model displays biologically plausible dynamics and the synchronization patterns reveal a hierarchical cluster organization in the network structure. We can identify a group of brain areas involved in multifunctional tasks by comparing the dynamical clusters to the topological communities of the network. With strong couplings of multilevel model and by using neural mass model, the dynamics are characterized by well-defined oscillations. The synchronization patterns are mainly determined by the node intensity (total input strengths of a node); the detailed network topology is of secondary importance. The biologically improved multilevel model exhibits similar dynamical patterns in the two regimes. Thus, the study of synchronization in a multilevel complex network model of cortex can provide insights into the relationship between network topology and functional organization of complex brain networks.
In the present work, we use symbolic regression for automated modeling of dynamical systems. Symbolic regression is a powerful and general method suitable for data-driven identification of mathematical expressions. In particular, the structure and parameters of those expressions are identified simultaneously.
We consider two main variants of symbolic regression: sparse regression-based and genetic programming-based symbolic regression. Both are applied to identification, prediction and control of dynamical systems.
We introduce a new methodology for the data-driven identification of nonlinear dynamics for systems undergoing abrupt changes. Building on a sparse regression algorithm derived earlier, the model after the change is defined as a minimum update with respect to a reference model of the system identified prior to the change. The technique is successfully exemplified on the chaotic Lorenz system and the van der Pol oscillator. Issues such as computational complexity, robustness against noise and requirements with respect to data volume are investigated.
We show how symbolic regression can be used for time series prediction. Again, issues such as robustness against noise and convergence rate are investigated us- ing the harmonic oscillator as a toy problem. In combination with embedding, we demonstrate the prediction of a propagating front in coupled FitzHugh-Nagumo oscillators. Additionally, we show how we can enhance numerical weather predictions to commercially forecast power production of green energy power plants.
We employ symbolic regression for synchronization control in coupled van der Pol oscillators. Different coupling topologies are investigated. We address issues such as plausibility and stability of the control laws found. The toolkit has been made open source and is used in turbulence control applications.
Genetic programming based symbolic regression is very versatile and can be adapted to many optimization problems. The heuristic-based algorithm allows for cost efficient optimization of complex tasks.
We emphasize the ability of symbolic regression to yield white-box models. In contrast to black-box models, such models are accessible and interpretable which allows the usage of established tool chains.
This work deals with the connection between two basic phenomena in Nonlinear Dynamics: synchronization of chaotic systems and recurrences in phase space. Synchronization takes place when two or more systems adapt (synchronize) some characteristic of their respective motions, due to an interaction between the systems or to a common external forcing. The appearence of synchronized dynamics in chaotic systems is rather universal but not trivial. In some sense, the possibility that two chaotic systems synchronize is counterintuitive: chaotic systems are characterized by the sensitivity ti different initial conditions. Hence, two identical chaotic systems starting at two slightly different initial conditions evolve in a different manner, and after a certain time, they become uncorrelated. Therefore, at a first glance, it does not seem to be plausible that two chaotic systems are able to synchronize. But as we will see later, synchronization of chaotic systems has been demonstrated. On one hand it is important to investigate the conditions under which synchronization of chaotic systems occurs, and on the other hand, to develop tests for the detection of synchronization. In this work, I have concentrated on the second task for the cases of phase synchronization (PS) and generalized synchronization (GS). Several measures have been proposed so far for the detection of PS and GS. However, difficulties arise with the detection of synchronization in systems subjected to rather large amounts of noise and/or instationarities, which are common when analyzing experimental data. The new measures proposed in the course of this thesis are rather robust with respect to these effects. They hence allow to be applied to data, which have evaded synchronization analysis so far. The proposed tests for synchronization in this work are based on the fundamental property of recurrences in phase space.
In the present work synchronization phenomena in complex dynamical systems exhibiting multiple time scales have been analyzed. Multiple time scales can be active in different manners. Three different systems have been analyzed with different methods from data analysis. The first system studied is a large heterogenous network of bursting neurons, that is a system with two predominant time scales, the fast firing of action potentials (spikes) and the burst of repetitive spikes followed by a quiescent phase. This system has been integrated numerically and analyzed with methods based on recurrence in phase space. An interesting result are the different transitions to synchrony found in the two distinct time scales. Moreover, an anomalous synchronization effect can be observed in the fast time scale, i.e. there is range of the coupling strength where desynchronization occurs. The second system analyzed, numerically as well as experimentally, is a pair of coupled CO₂ lasers in a chaotic bursting regime. This system is interesting due to its similarity with epidemic models. We explain the bursts by different time scales generated from unstable periodic orbits embedded in the chaotic attractor and perform a synchronization analysis of these different orbits utilizing the continuous wavelet transform. We find a diverse route to synchrony of these different observed time scales. The last system studied is a small network motif of limit cycle oscillators. Precisely, we have studied a hub motif, which serves as elementary building block for scale-free networks, a type of network found in many real world applications. These hubs are of special importance for communication and information transfer in complex networks. Here, a detailed study on the mechanism of synchronization in oscillatory networks with a broad frequency distribution has been carried out. In particular, we find a remote synchronization of nodes in the network which are not directly coupled. We also explain the responsible mechanism and its limitations and constraints. Further we derive an analytic expression for it and show that information transmission in pure phase oscillators, such as the Kuramoto type, is limited. In addition to the numerical and analytic analysis an experiment consisting of electrical circuits has been designed. The obtained results confirm the former findings.
This thesis analyses synchronization phenomena occurring in large ensembles of interacting oscillatory units. In particular, the effects of nonisochronicity (frequency dependence on the oscillator's amplitude) on the macroscopic transition to synchronization are studied in detail. The new phenomena found (Anomalous Synchronization) are investigated in populations of oscillators as well as between oscillator's ensembles.
Synchronization of large ensembles of oscillators is an omnipresent phenomenon observed in different fields of science like physics, engineering, life sciences, etc. The most simple setup is that of globally coupled phase oscillators, where all the oscillators contribute to a global field which acts on all oscillators. This formulation of the problem was pioneered by Winfree and Kuramoto. Such a setup gives a possibility for the analysis of these systems in terms of global variables. In this work we describe nontrivial collective dynamics in oscillator populations coupled via mean fields in terms of global variables. We consider problems which cannot be directly reduced to standard Kuramoto and Winfree models.
In the first part of the thesis we adopt a method introduced by Watanabe and Strogatz. The main idea is that the system of identical oscillators of particular type can be described by a low-dimensional system of global equations. This approach enables us to perform a complete analytical analysis for a special but vast set of initial conditions. Furthermore, we show how the approach can be expanded for some nonidentical systems. We apply the Watanabe-Strogatz approach to arrays of Josephson junctions and systems of identical phase oscillators with leader-type coupling.
In the next parts of the thesis we consider the self-consistent mean-field theory method that can be applied to general nonidentical globally coupled systems of oscillators both with or without noise. For considered systems a regime, where the global field rotates uniformly, is the most important one. With the help of this approach such solutions of the self-consistency equation for an arbitrary distribution of frequencies and coupling parameters can be found analytically in the parametric form, both for noise-free and noisy cases.
We apply this method to deterministic Kuramoto-type model with generic coupling and an ensemble of spatially distributed oscillators with leader-type coupling. Furthermore, with the proposed self-consistent approach we fully characterize rotating wave solutions of noisy Kuramoto-type model with generic coupling and an ensemble of noisy oscillators with bi-harmonic coupling.
Whenever possible, a complete analysis of global dynamics is performed and compared with direct numerical simulations of large populations.
Subject of this work is the investigation of generic synchronization phenomena in interacting complex systems. These phenomena are observed, among all, in coupled deterministic chaotic systems. At very weak interactions between individual systems a transition to a weakly coherent behavior of the systems can take place. In coupled continuous time chaotic systems this transition manifests itself with the effect of phase synchronization, in coupled chaotic discrete time systems with the effect of non-vanishing macroscopic mean field. Transition to coherence in a chain of locally coupled oscillators described with phase equations is investigated with respect to the symmetries in the system. It is shown that the reversibility of the system caused by these symmetries results to non-trivial topological properties of trajectories so that the system constructed to be dissipative reveals in a whole parameter range quasi-Hamiltonian features, i.e. the phase volume is conserved on average and Lyapunov exponents come in symmetric pairs. Transition to coherence in an ensemble of globally coupled chaotic maps is described with the loss of stability of the disordered state. The method is to break the self-consistensy of the macroscopic field and to characterize the ensemble in analogy to an amplifier circuit with feedback with a complex linear transfer function. This theory is then generalized for several cases of theoretic interest.
<img src="http://vg00.met.vgwort.de/na/806c85cec18906a64e06" width="1" height="1" alt=""> Subject of this work is the possibility to synchronize nonlinear systems via correlated noise and automatic control. The thesis is divided into two parts. The first part is motivated by field studies on feral sheep populations on two islands of the St. Kilda archipelago, which revealed strong correlations due to environmental noise. For a linear system the population correlation equals the noise correlation (Moran effect). But there exists no systematic examination of the properties of nonlinear maps under the influence of correlated noise. Therefore, in the first part of this thesis the noise-induced correlation of logistic maps is systematically examined. For small noise intensities it can be shown analytically that the correlation of quadratic maps in the fixed-point regime is always smaller than or equal to the noise correlation. In the period-2 regime a Markov model explains qualitatively the main dynamical characteristics. Furthermore, two different mechanisms are introduced which lead to a higher correlation of the systems than the environmental correlation. The new effect of "correlation resonance" is described, i. e. the correlation yields a maximum depending on the noise intensity. In the second part of the thesis an automatic control method is presented which synchronizes different systems in a robust way. This method is inspired by phase-locked loops and is based on a feedback loop with a differential control scheme, which allows to change the phases of the controlled systems. The effectiveness of the approach is demonstrated for controlled phase synchronization of regular oscillators and foodweb models.
Synchrotron-based angle-resolved time-of-flight electron spectroscopy for dynamics in dichalogenides
(2018)
Poly(vinylidene fluoride) (PVDF)-based homo-, co- and ter-polymers are well-known for their ferroelectric and relaxor-ferroelectric properties. Their semi-crystalline morphology consists of crystalline and amorphous phases, plus interface regions in between, and governs the relevant electro-active properties. In this work, the influence of chemical, thermal and mechanical treatments on the structure and morphology of PVDF-based polymers and on the related ferroelectric/relaxor-ferroelectric properties is investigated. Polymer films were prepared in different ways and subjected to various treatments such as annealing, quenching and stretching. The resulting changes in the transitions and relaxations of the polymer samples were studied by means of dielectric, thermal, mechanical and optical techniques. In particular, the origin(s) behind the mysterious mid-temperature transition (T_{mid}) that is observed in all PVDF-based polymers was assessed. A new hypothesis is proposed to describe the T_{mid} transition as a result of multiple processes taking place within the temperature range of the transition. The contribution of the individual processes to the observed overall transition depends on both the chemical structure of the monomer units and the processing conditions which also affect the melting transition. Quenching results in a decrease of the overall crystallinity and in smaller crystallites. On samples quenched after annealing, notable differences in the fractions of different crystalline phases have been observed when compared to samples that had been slowly cooled. Stretching of poly(vinylidene fluoride-tetrafluoroethylene) (P(VDF-TFE)) films causes an increase in the fraction of the ferroelectric β-phase with simultaneous increments in the melting point (T_m) and the crystallinity (\chi_c) of the copolymer. While an increase in the stretching temperature does not have a profound effect on the amount of the ferroelectric phase, its stability appears to improve.
Measurements of the non-linear dielectric permittivity \varepsilon_2^\prime in a poly(vinylidenefluoride-trifluoroethylene-chlorofluoroethylene) (P(VDF-TrFE- CFE)) relaxor-ferroelectric (R-F) terpolymer reveal peaks at 30 and 80 °C that cannot be identified in conventional dielectric spectroscopy. The former peak is associated with T_{mid}\ and may help to understand the non-zero \varepsilon_2^\prime values that are found for the paraelectric terpolymer phase. The latter peak can also be observed during cooling of P(VDF-TrFE) copolymer samples at 100 °C and is due to conduction processes and space-charge polarization as a result of the accumulation of real charges at the electrode-sample interface. Annealing lowers the Curie-transition temperature of the terpolymer as a consequence of its smaller ferroelectric-phase fraction, which by default exists even in terpolymers with relatively high CFE content. Changes in the transition temperatures are in turn related to the behavior of the hysteresis curves observed on differently heat-treated samples. Upon heating, the hysteresis curves evolve from those known for a ferroelectric to those of a typical relaxor-ferroelectric material. Comparing dielectric-hysteresis loops obtained at various temperatures, we find that annealed terpolymer films show higher electric-displacement values and lower coercive fields than the non-annealed samples − irrespective of the measurement temperature − and also exhibit ideal relaxor-ferroelectric behavior at ambient temperatures, which makes them excellent candidates for related applications at or near room temperature. However, non-annealed films − by virtue of their higher ferroelectric activity − show a larger and more stable remanent polarization at room temperature, while annealed samples need to be poled below 0 °C to induce a well-defined polarization. Overall, by modifying the three phases in PVDF-based polymers, it has been demonstrated how the preparation steps and processing conditions can be tailored to achieve the desired properties that are optimal for specific applications.
A huge number of applications require coherent radiation in the visible spectral range. Since diode lasers are very compact and efficient light sources, there exists a great interest to cover these applications with diode laser emission. Despite modern band gap engineering not all wavelengths can be accessed with diode laser radiation. Especially in the visible spectral range between 480 nm and 630 nm no emission from diode lasers is available, yet. Nonlinear frequency conversion of near-infrared radiation is a common way to generate coherent emission in the visible spectral range. However, radiation with extraordinary spatial temporal and spectral quality is required to pump frequency conversion. Broad area (BA) diode lasers are reliable high power light sources in the near-infrared spectral range. They belong to the most efficient coherent light sources with electro-optical efficiencies of more than 70%. Standard BA lasers are not suitable as pump lasers for frequency conversion because of their poor beam quality and spectral properties. For this purpose, tapered lasers and diode lasers with Bragg gratings are utilized. However, these new diode laser structures demand for additional manufacturing and assembling steps that makes their processing challenging and expensive. An alternative to BA diode lasers is the stripe-array architecture. The emitting area of a stripe-array diode laser is comparable to a BA device and the manufacturing of these arrays requires only one additional process step. Such a stripe-array consists of several narrow striped emitters realized with close proximity. Due to the overlap of the fields of neighboring emitters or the presence of leaky waves, a strong coupling between the emitters exists. As a consequence, the emission of such an array is characterized by a so called supermode. However, for the free running stripe-array mode competition between several supermodes occurs because of the lack of wavelength stabilization. This leads to power fluctuations, spectral instabilities and poor beam quality. Thus, it was necessary to study the emission properties of those stripe-arrays to find new concepts to realize an external synchronization of the emitters. The aim was to achieve stable longitudinal and transversal single mode operation with high output powers giving a brightness sufficient for efficient nonlinear frequency conversion. For this purpose a comprehensive analysis of the stripe-array devices was done here. The physical effects that are the origin of the emission characteristics were investigated theoretically and experimentally. In this context numerical models could be verified and extended. A good agreement between simulation and experiment was observed. One way to stabilize a specific supermode of an array is to operate it in an external cavity. Based on mathematical simulations and experimental work, it was possible to design novel external cavities to select a specific supermode and stabilize all emitters of the array at the same wavelength. This resulted in stable emission with 1 W output power, a narrow bandwidth in the range of 2 MHz and a very good beam quality with M²<1.5. This is a new level of brightness and brilliance compared to other BA and stripe-array diode laser systems. The emission from this external cavity diode laser (ECDL) satisfied the requirements for nonlinear frequency conversion. Furthermore, a huge improvement to existing concepts was made. In the next step newly available periodically poled crystals were used for second harmonic generation (SHG) in single pass setups. With the stripe-array ECDL as pump source, more than 140 mW of coherent radiation at 488 nm could be generated with a very high opto-optical conversion efficiency. The generated blue light had very good transversal and longitudinal properties and could be used to generate biphotons by parametric down-conversion. This was feasible because of the improvement made with the infrared stripe-array diode lasers due to the development of new physical concepts.
Mechanosensation is a fundamental biological process that provides the basis for sensing touch and pain as well as for hearing and proprioception. A special class of ion-channel proteins known as mechanosensitive proteins convert the mechanical stimuli into electrochemical signals to mediate this process. Mechanosensitive proteins undergo conformational changes in response to mechanical force, which eventually leads to the opening of the proteins' ion channel. Mammalian mechanosensitive proteins remained a long sought-after mystery until 2010 when a family of two proteins - Piezo1 and Piezo2 - was identifed as mechanosensors [1]. The cryo-EM structures of Piezo1 and Piezo2 protein were resolved in the last years and reveal a propeller-shaped homotrimer with 114 transmembrane helices [2, 3, 4, 5]. The protein structures are curved and have been suggested to deform the surrounding membrane into a nano-dome, which mechanically responds to membrane tension resulting from external forces [2]. In this thesis, the conformations of membrane-embedded Piezo1 and Piezo2 proteins and their tension-induced conformational changes are investigated using molecular dynamics simulations. Our coarse-grained molecular dynamics simulations show that the Piezo proteins induce curvature in the surrounding membrane and form a stable protein-membrane nano-dome in the tensionless membrane. These membrane-embedded Piezo proteins, however, adopt substantially less curved conformations in our simulations compared to the cryo-EM structures solved in detergent micelles, which agrees with recent experimental investigations of the overall Piezo nano-dome shape in membrane vesicles [6, 7, 8]. At high membrane tension, the Piezo proteins attain nearly planar conformations in our simulations. Our systematic investigation of Piezo proteins under different membrane tensions indicates a half-maximal conformational response at membrane tension values rather close to the experimentally suggested values of Piezo activation [9, 10]. In addition, our simulations indicate a widening of the Piezo1 ion channel at high membrane tension, which agrees with the channel widening observed in recent nearly flattened cryo-EM structures of Piezo1 in small membrane vesicles [11]. In contrast, the Piezo2 ion channel does not respond to membrane tension in our simulations. These different responses of the Piezo1 and Piezo2 ion channels in our simulations are in line with patch-clamp experiments, in which Piezo1, but not Piezo2, was shown to be activated by membrane tension alone [12].
Famously, Einstein read off the geometry of spacetime from Maxwell's equations. Today, we take this geometry that serious that our fundamental theory of matter, the standard model of particle physics, is based on it. However, it seems that there is a gap in our understanding if it comes to the physics outside of the solar system. Independent surveys show that we need concepts like dark matter and dark energy to make our models fit with the observations. But these concepts do not fit in the standard model of particle physics. To overcome this problem, at least, we have to be open to matter fields with kinematics and dynamics beyond the standard model. But these matter fields might then very well correspond to different spacetime geometries. This is the basis of this thesis: it studies the underlying spacetime geometries and ventures into the quantization of those matter fields independently of any background geometry. In the first part of this thesis, conditions are identified that a general tensorial geometry must fulfill to serve as a viable spacetime structure. Kinematics of massless and massive point particles on such geometries are introduced and the physical implications are investigated. Additionally, field equations for massive matter fields are constructed like for example a modified Dirac equation. In the second part, a background independent formulation of quantum field theory, the general boundary formulation, is reviewed. The general boundary formulation is then applied to the Unruh effect as a testing ground and first attempts are made to quantize massive matter fields on tensorial spacetimes.
Tensorial spacetime geometries carrying predictive, interpretable and quantizable matter dynamics
(2012)
Which tensor fields G on a smooth manifold M can serve as a spacetime structure? In the first part of this thesis, it is found that only a severely restricted class of tensor fields can provide classical spacetime geometries, namely those that can carry predictive, interpretable and quantizable matter dynamics. The obvious dependence of this characterization of admissible tensorial spacetime geometries on specific matter is not a weakness, but rather presents an insight: it was Maxwell theory that justified Einstein to promote Lorentzian manifolds to the status of a spacetime geometry. Any matter that does not mimick the structure of Maxwell theory, will force us to choose another geometry on which the matter dynamics of interest are predictive, interpretable and quantizable. These three physical conditions on matter impose three corresponding algebraic conditions on the totally symmetric contravariant coefficient tensor field P that determines the principal symbol of the matter field equations in terms of the geometric tensor G: the tensor field P must be hyperbolic, time-orientable and energy-distinguishing. Remarkably, these physically necessary conditions on the geometry are mathematically already sufficient to realize all kinematical constructions familiar from Lorentzian geometry, for precisely the same structural reasons. This we were able to show employing a subtle interplay of convex analysis, the theory of partial differential equations and real algebraic geometry. In the second part of this thesis, we then explore general properties of any hyperbolic, time-orientable and energy-distinguishing tensorial geometry. Physically most important are the construction of freely falling non-rotating laboratories, the appearance of admissible modified dispersion relations to particular observers, and the identification of a mechanism that explains why massive particles that are faster than some massless particles can radiate off energy until they are slower than all massless particles in any hyperbolic, time-orientable and energy-distinguishing geometry. In the third part of the thesis, we explore how tensorial spacetime geometries fare when one wants to quantize particles and fields on them. This study is motivated, in part, in order to provide the tools to calculate the rate at which superluminal particles radiate off energy to become infraluminal, as explained above. Remarkably, it is again the three geometric conditions of hyperbolicity, time-orientability and energy-distinguishability that allow the quantization of general linear electrodynamics on an area metric spacetime and the quantization of massive point particles obeying any admissible dispersion relation. We explore the issue of field equations of all possible derivative order in rather systematic fashion, and prove a practically most useful theorem that determines Dirac algebras allowing the reduction of derivative orders. The final part of the thesis presents the sketch of a truly remarkable result that was obtained building on the work of the present thesis. Particularly based on the subtle duality maps between momenta and velocities in general tensorial spacetimes, it could be shown that gravitational dynamics for hyperbolic, time-orientable and energy distinguishable geometries need not be postulated, but the formidable physical problem of their construction can be reduced to a mere mathematical task: the solution of a system of homogeneous linear partial differential equations. This far-reaching physical result on modified gravity theories is a direct, but difficult to derive, outcome of the findings in the present thesis. Throughout the thesis, the abstract theory is illustrated through instructive examples.
This cumulative thesis is concerned with the evolution of geomagnetic activity since the beginning of the 20th century, that is, the time-dependent response of the geomagnetic field to solar forcing. The focus lies on the description of the magnetospheric response field at ground level, which is particularly sensitive to the ring current system, and an interpretation of its variability in terms of the solar wind driving. Thereby, this work contributes to a comprehensive understanding of long-term solar-terrestrial interactions.
The common basis of the presented publications is formed by a reanalysis of vector magnetic field measurements from geomagnetic observatories located at low and middle geomagnetic latitudes. In the first two studies, new ring current targeting geomagnetic activity indices are derived, the Annual and Hourly Magnetospheric Currents indices (A/HMC). Compared to existing indices (e.g., the Dst index), they do not only extend the covered period by at least three solar cycles but also constitute a qualitative improvement concerning the absolute index level and the ~11-year solar cycle variability. The analysis of A/HMC shows that (a) the annual geomagnetic activity experiences an interval-dependent trend with an overall linear decline during 1900–2010 of ~5 % (b) the average trend-free activity level amounts to ~28 nT (c) the solar cycle related variability shows amplitudes of ~15–45 nT (d) the activity level for geomagnetically quiet conditions (Kp<2) lies slightly below 20 nT. The plausibility of the last three points is ensured by comparison to independent estimations either based on magnetic field measurements from LEO satellite missions (since the 1990s) or the modeling of geomagnetic activity from solar wind input (since the 1960s). An independent validation of the longterm trend is problematic mainly because the sensitivity of the locally measured geomagnetic activity depends on geomagnetic latitude. Consequently, A/HMC is neither directly comparable to global geomagnetic activity indices (e.g., the aa index) nor to the partly reconstructed open solar magnetic flux, which requires a homogeneous response of the ground-based measurements to the interplanetary magnetic field and the solar wind speed.
The last study combines a consistent, HMC-based identification of geomagnetic storms from 1930–2015 with an analysis of the corresponding spatial (magnetic local time-dependent) disturbance patterns. Amongst others, the disturbances at dawn and dusk, particularly their evolution during the storm recovery phases, are shown to be indicative of the solar wind driving structure (Interplanetary Coronal Mass Ejections vs. Stream or Co-rotating Interaction Regions), which enables a backward-prediction of the storm driver classes. The results indicate that ICME-driven geomagnetic storms have decreased since 1930 which is consistent with the concurrent decrease of HMC. Out of the collection of compiled follow-up studies the inclusion of measurements from high-latitude geomagnetic observatories into the third study’s framework seems most promising at this point.
In normal everyday viewing, we perform large eye movements (saccades) and miniature or fixational eye movements. Most of our visual perception occurs while we are fixating. However, our eyes are perpetually in motion. Properties of these fixational eye movements, which are partly controlled by the brainstem, change depending on the task and the visual conditions. Currently, fixational eye movements are poorly understood because they serve the two contradictory functions of gaze stabilization and counteraction of retinal fatigue. In this dissertation, we investigate the spatial and temporal properties of time series of eye position acquired from participants staring at a tiny fixation dot or at a completely dark screen (with the instruction to fixate a remembered stimulus); these time series were acquired with high spatial and temporal resolution. First, we suggest an advanced algorithm to separate the slow phases (named drift) and fast phases (named microsaccades) of these movements, which are considered to play different roles in perception. On the basis of this identification, we investigate and compare the temporal scaling properties of the complete time series and those time series where the microsaccades are removed. For the time series obtained during fixations on a stimulus, we were able to show that they deviate from Brownian motion. On short time scales, eye movements are governed by persistent behavior and on a longer time scales, by anti-persistent behavior. The crossover point between these two regimes remains unchanged by the removal of microsaccades but is different in the horizontal and the vertical components of the eyes. Other analyses target the properties of the microsaccades, e.g., the rate and amplitude distributions, and we investigate, whether microsaccades are triggered dynamically, as a result of earlier events in the drift, or completely randomly. The results obtained from using a simple box-count measure contradict the hypothesis of a purely random generation of microsaccades (Poisson process). Second, we set up a model for the slow part of the fixational eye movements. The model is based on a delayed random walk approach within the velocity related equation, which allows us to use the data to determine control loop durations; these durations appear to be different for the vertical and horizontal components of the eye movements. The model is also motivated by the known physiological representation of saccade generation; the difference between horizontal and vertical components concurs with the spatially separated representation of saccade generating regions. Furthermore, the control loop durations in the model suggest an external feedback loop for the horizontal but not for the vertical component, which is consistent with the fact that an internal feedback loop in the neurophysiology has only been identified for the vertical component. Finally, we confirmed the scaling properties of the model by semi-analytical calculations. In conclusion, we were able to identify several properties of the different parts of fixational eye movements and propose a model approach that is in accordance with the described neurophysiology and described limitations of fixational eye movement control.
Arctic climate change is marked by intensified warming compared to global trends and a significant reduction in Arctic sea ice which can intricately influence mid-latitude atmospheric circulation through tropo- and stratospheric pathways. Achieving accurate simulations of current and future climate demands a realistic representation of Arctic climate processes in numerical climate models, which remains challenging.
Model deficiencies in replicating observed Arctic climate processes often arise due to inadequacies in representing turbulent boundary layer interactions that determine the interactions between the atmosphere, sea ice, and ocean. Many current climate models rely on parameterizations developed for mid-latitude conditions to handle Arctic turbulent boundary layer processes.
This thesis focuses on modified representation of the Arctic atmospheric processes and understanding their resulting impact on large-scale mid-latitude atmospheric circulation within climate models. The improved turbulence parameterizations, recently developed based on Arctic measurements, were implemented in the global atmospheric circulation model ECHAM6. This involved modifying the stability functions over sea ice and ocean for stable stratification and changing the roughness length over sea ice for all stratification conditions. Comprehensive analyses are conducted to assess the impacts of these modifications on ECHAM6's simulations of the Arctic boundary layer, overall atmospheric circulation, and the dynamical pathways between the Arctic and mid-latitudes.
Through a step-wise implementation of the mentioned parameterizations into ECHAM6, a series of sensitivity experiments revealed that the combined impacts of the reduced roughness length and the modified stability functions are non-linear. Nevertheless, it is evident that both modifications consistently lead to a general decrease in the heat transfer coefficient, being in close agreement with the observations.
Additionally, compared to the reference observations, the ECHAM6 model falls short in accurately representing unstable and strongly stable conditions.
The less frequent occurrence of strong stability restricts the influence of the modified stability functions by reducing the affected sample size. However, when focusing solely on the specific instances of a strongly stable atmosphere, the sensible heat flux approaches near-zero values, which is in line with the observations. Models employing commonly used surface turbulence parameterizations were shown to have difficulties replicating the near-zero sensible heat flux in strongly stable stratification.
I also found that these limited changes in surface layer turbulence parameterizations have a statistically significant impact on the temperature and wind patterns across multiple pressure levels, including the stratosphere, in both the Arctic and mid-latitudes. These significant signals vary in strength, extent, and direction depending on the specific month or year, indicating a strong reliance on the background state.
Furthermore, this research investigates how the modified surface turbulence parameterizations may influence the response of both stratospheric and tropospheric circulation to Arctic sea ice loss.
The most suitable parameterizations for accurately representing Arctic boundary layer turbulence were identified from the sensitivity experiments. Subsequently, the model's response to sea ice loss is evaluated through extended ECHAM6 simulations with different prescribed sea ice conditions.
The simulation with adjusted surface turbulence parameterizations better reproduced the observed Arctic tropospheric warming in vertical extent, demonstrating improved alignment with the reanalysis data. Additionally, unlike the control experiments, this simulation successfully reproduced specific circulation patterns linked to the stratospheric pathway for Arctic-mid-latitude linkages. Specifically, an increased occurrence of the Scandinavian-Ural blocking regime (negative phase of the North Atlantic Oscillation) in early (late) winter is observed. Overall, it can be inferred that improving turbulence parameterizations at the surface layer can improve the ECHAM6's response to sea ice loss.
The present work investigates the structure formation and wetting in two dimensional (2D) Langmuir monolayer phases in local thermodynamic equilibrium. A Langmuir monolayer is an isolated 2D system of surfactants at the air/water interface. It exhibits crystalline, liquid crystalline, liquid and gaseous phases differing in positional and/or orientational order. Permanent electric dipole moments of the surfactants lead to a long range repulsive interaction and to the formation of mesoscopic patterns. An interaction model is used describing the structure formation as a competition between short range attraction (bare line tension) and long range repulsion (surface potentials) on a scale Delta. Delta has the meaning of a dividing length between the short and long range interaction. In the present work the thermodynamic equilibrium conditions for the shape of two phase boundary lines (Young-Laplace equation) and three phase intersection points (Young′s condition) are derived and applied to describe experimental data: The line tension is measured by pendant droplet tensiometry. The bubble shape and size of 2D foams is calculated numerically and compared to experimental foams. Contact angles are measured by fitting numerical solutions of the Young-Laplace equation on micron scale. The scaling behaviour of the contact angle allows to measure a lower limit for Delta. Further it is discussed, whether in biological membranes wetting transitions are a way in order to control reaction kinetics. Studies performed in our group are discussed with respect to this question in the framework of the above mentioned theory. Finally the apparent violation of Gibbs′ phase rule in Langmuir monolayers (non-horizontal plateau of the surface pressure/area-isotherm, extended three phase coexistence region in one component systems) is investigated quantitatively. It has been found that the most probable explanation are impurities within the system whereas finite size effects or the influence of the long range electrostatics can not explain the order of magnitude of the effect.
The aim of this thesis is to achieve a deep understanding of the working mechanism of polymer based solar cells and to improve the device performance. Two types of the polymer based solar cells are studied here: all-polymer solar cells comprising macromolecular donors and acceptors based on poly(p-phenylene vinylene) and hybrid cells comprising a PPV copolymer in combination with a novel small molecule electron acceptor. To understand the interplay between morphology and photovoltaic properties in all-polymer devices, I compared the photocurrent characteristics and excited state properties of bilayer and blend devices with different nano-morphology, which was fine tuned by using solvents with different boiling points. The main conclusion from these complementary measurements was that the performance-limiting step is the field-dependent generation of free charge carriers, while bimolecular recombination and charge extraction do not compromise device performance. These findings imply that the proper design of the donor-acceptor heterojunction is of major importance towards the goal of high photovoltaic efficiencies. Regarding polymer-small molecular hybrid solar cells I combined the hole-transporting polymer M3EH-PPV with a novel Vinazene-based electron acceptor. This molecule can be either deposited from solution or by thermal evaporation, allowing for a large variety of layer architectures to be realized. I then demonstrated that the layer architecture has a large influence on the photovoltaic properties. Solar cells with very high fill factors of up to 57 % and an open circuit voltage of 1V could be achieved by realizing a sharp and well-defined donor-acceptor heterojunction. In the past, fill factors exceeding 50 % have only been observed for polymers in combination with soluble fullerene-derivatives or nanocrystalline inorganic semiconductors as the electron-accepting component. The finding that proper processing of polymer-vinazene devices leads to similar high values is a major step towards the design of efficient polymer-based solar cells.
The Antarctic ice sheet is the largest freshwater reservoir worldwide. If it were to melt completely, global sea levels would rise by about 58 m. Calculation of projections of the Antarctic contribution to sea level rise under global warming conditions is an ongoing effort which
yields large ranges in predictions. Among the reasons for this are uncertainties related to the physics of ice sheet modeling. These
uncertainties include two processes that could lead to runaway ice retreat: the Marine Ice Sheet Instability (MISI), which causes rapid grounding line retreat on retrograde bedrock, and the Marine Ice Cliff Instability (MICI), in which tall ice cliffs become unstable and calve off, exposing even taller ice cliffs.
In my thesis, I investigated both marine instabilities (MISI and MICI) using the Parallel Ice Sheet Model (PISM), with a focus on MICI.
In recent decades, astronomy has seen a boom in large-scale stellar surveys of the Galaxy. The detailed information obtained about millions of individual stars in the Milky Way is bringing us a step closer to answering one of the most outstanding questions in astrophysics: how do galaxies form and evolve? The Milky Way is the only galaxy where we can dissect many stars into their high-dimensional chemical composition and complete phase space, which analogously as fossil records can unveil the past history of the genesis of the Galaxy. The processes that lead to large structure formation, such as the Milky Way, are critical for constraining cosmological models; we call this line of study Galactic archaeology or near-field cosmology.
At the core of this work, we present a collection of efforts to chemically and dynamically characterise the disks and bulge of our Galaxy. The results we present in this thesis have only been possible thanks to the advent of the Gaia astrometric satellite, which has revolutionised the field of Galactic archaeology by precisely measuring the positions, parallax distances and motions of more than a billion stars. Another, though not less important, breakthrough is the APOGEE survey, which has observed spectra in the near-infrared peering into the dusty regions of the Galaxy, allowing us to determine detailed chemical abundance patterns in hundreds of thousands of stars. To accurately depict the Milky Way structure, we use and develop the Bayesian isochrone fitting tool/code called StarHorse; this software can predict stellar distances, extinctions and ages by combining astrometry, photometry and spectroscopy based on stellar evolutionary models. The StarHorse code is pivotal to calculating distances where Gaia parallaxes alone cannot allow accurate estimates.
We show that by combining Gaia, APOGEE, photometric surveys and using StarHorse, we can produce a chemical cartography of the Milky way disks from their outermost to innermost parts. Such a map is unprecedented in the inner Galaxy. It reveals a continuity of the bimodal chemical pattern previously detected in the solar neighbourhood, indicating two populations with distinct formation histories. Furthermore, the data reveals a chemical gradient within the thin disk where the content of 𝛼-process elements and metals is higher towards the centre. Focusing on a sample in the inner MW we confirm the extension of the chemical duality to the innermost regions of the Galaxy. We find stars with bar shape orbits to show both high- and low-𝛼 abundances, suggesting the bar formed by secular evolution trapping stars that already existed. By analysing the chemical orbital space of the inner Galactic regions, we disentangle the multiple populations that inhabit this complex region. We reveal the presence of the thin disk, thick disk, bar, and a counter-rotating population, which resembles the outcome of a perturbed proto-Galactic disk. Our study also finds that the inner Galaxy holds a high quantity of super metal-rich stars up to three times solar suggesting it is a possible repository of old super-metal-rich stars found in the solar neighbourhood.
We also enter into the complicated task of deriving individual stellar ages. With StarHorse, we calculate the ages of main-sequence turn-off and sub-giant stars for several public spectroscopic surveys. We validate our results by investigating linear relations between chemical abundances and time since the 𝛼 and neutron capture elements are sensitive to age as a reflection of the different enrichment timescales of these elements. For further study of the disks in the solar neighbourhood, we use an unsupervised machine learning algorithm to delineate a multidimensional separation of chrono-chemical stellar groups revealing the chemical thick disk, the thin disk, and young 𝛼-rich stars. The thick disk is shown to have a small age dispersion indicating its fast formation contrary to the thin disk that spans a wide range of ages.
With groundbreaking data, this thesis encloses a detailed chemo-dynamical view of the disk and bulge of our Galaxy. Our findings on the Milky Way can be linked to the evolution of high redshift disk galaxies, helping to solve the conundrum of galaxy formation.
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 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.
The two hallmark features of Brownian motion are the linear growth < x2(t)> = 2Ddt of the mean squared displacement (MSD) with diffusion coefficient D in d spatial dimensions, and the Gaussian distribution of displacements. With the increasing complexity of the studied systems deviations from these two central properties have been unveiled over the years. Recently, a large variety of systems have been reported in which the MSD exhibits the linear growth in time of Brownian (Fickian) transport, however, the distribution of displacements is pronouncedly non-Gaussian (Brownian yet non-Gaussian, BNG). A similar behaviour is also observed for viscoelastic-type motion where an anomalous trend of the MSD, i.e., <x2(t)> ~ ta, is combined with a priori unexpected non-Gaussian distributions (anomalous yet non-Gaussian, ANG). This kind of behaviour observed in BNG and ANG diffusions has been related to the presence of heterogeneities in the systems and a common approach has been established to address it, that is, the random diffusivity approach.
This dissertation explores extensively the field of random diffusivity models. Starting from a chronological description of all the main approaches used as an attempt of describing BNG and ANG diffusion, different mathematical methodologies are defined for the resolution and study of these models. The processes that are reported in this work can be classified in three subcategories, i) randomly-scaled Gaussian processes, ii) superstatistical models and iii) diffusing diffusivity models, all belonging to the more general class of random diffusivity models. Eventually, the study focuses more on BNG diffusion, which is by now well-established and relatively well-understood. Nevertheless, many examples are discussed for the description of ANG diffusion, in order to highlight the possible scenarios which are known so far for the study of this class of processes.
The second part of the dissertation deals with the statistical analysis of random diffusivity processes. A general description based on the concept of moment-generating function is initially provided to obtain standard statistical properties of the models. Then, the discussion moves to the study of the power spectral analysis and the first passage statistics for some particular random diffusivity models. A comparison between the results coming from the random diffusivity approach and the ones for standard Brownian motion is discussed. In this way, a deeper physical understanding of the systems described by random diffusivity models is also outlined.
To conclude, a discussion based on the possible origins of the heterogeneity is sketched, with the main goal of inferring which kind of systems can actually be described by the random diffusivity approach.
When Galactic microlensing events of stars are observed, one usually measures a symmetric light curve corresponding to a single lens, or an asymmetric light curve, often with caustic crossings, in the case of a binary lens system. In principle, the fraction of binary stars at a certain separation range can be estimated based on the number of measured microlensing events. However, a binary system may produce a light curve which can be fitted well as a single lens light curve, in particullary if the data sampling is poor and the errorbars are large. We investigate what fraction of microlensing events produced by binary stars for different separations may be well fitted by and hence misinterpreted as single lens events for various observational conditions. We find that this fraction strongly depends on the separation of the binary components, reaching its minimum at between 0.6 and 1.0 Einstein radius, where it is still of the order of 5% The Einstein radius is corresponding to few A.U. for typical Galactic microlensing scenarios. The rate for misinterpretation is higher for short microlensing events lasting up to few months and events with smaller maximum amplification. For fixed separation it increases for binaries with more extreme mass ratios. Problem of degeneracy in photometric light curve solution between binary lens and binary source microlensing events was studied on simulated data, and data observed by the PLANET collaboration. The fitting code BISCO using the PIKAIA genetic algorithm optimizing routine was written for optimizing binary-source microlensing light curves observed at different sites, in I, R and V photometric bands. Tests on simulated microlensing light curves show that BISCO is successful in finding the solution to a binary-source event in a very wide parameter space. Flux ratio method is suggested in this work for breaking degeneracy between binary-lens and binary-source photometric light curves. Models show that only a few additional data points in photometric V band, together with a full light curve in I band, will enable breaking the degeneracy. Very good data quality and dense data sampling, combined with accurate binary lens and binary source modeling, yielded the discovery of the lowest-mass planet discovered outside of the Solar System so far, OGLE-2005-BLG-390Lb, having only 5.5 Earth masses. This was the first observed microlensing event in which the degeneracy between a planetary binary-lens and an extreme flux ratio binary-source model has been successfully broken. For events OGLE-2003-BLG-222 and OGLE-2004-BLG-347, the degeneracy was encountered despite of very dense data sampling. From light curve modeling and stellar evolution theory, there was a slight preference to explain OGLE-2003-BLG-222 as a binary source event, and OGLE-2004-BLG-347 as a binary lens event. However, without spectra, this degeneracy cannot be fully broken. No planet was found so far around a white dwarf, though it is believed that Jovian planets should survive the late stages of stellar evolution, and that white dwarfs will retain planetary systems in wide orbits. We want to perform high precision astrometric observations of nearby white dwarfs in wide binary systems with red dwarfs in order to find planets around white dwarfs. We selected a sample of observing targets (WD-RD binary systems, not published yet), which can possibly have planets around the WD component, and modeled synthetic astrometric orbits which can be observed for these targets using existing and future astrometric facilities. Modeling was performed for the astrometric accuracy of 0.01, 0.1, and 1.0 mas, separation between WD and planet of 3 and 5 A.U., binary system separation of 30 A.U., planet masses of 10 Earth masses, 1 and 10 Jupiter masses, WD mass of 0.5M and 1.0 Solar masses, and distances to the system of 10, 20 and 30 pc. It was found that the PRIMA facility at the VLTI will be able to detect planets around white dwarfs once it is operating, by measuring the astrometric wobble of the WD due to a planet companion, down to 1 Jupiter mass. We show for the simulated observations that it is possible to model the orbits and find the parameters describing the potential planetary systems.
Theory of mRNA degradation
(2012)
One of the central themes of biology is to understand how individual cells achieve a high fidelity in gene expression. Each cell needs to ensure accurate protein levels for its proper functioning and its capability to proliferate. Therefore, complex regulatory mechanisms have evolved in order to render the expression of each gene dependent on the expression level of (all) other genes. Regulation can occur at different stages within the framework of the central dogma of molecular biology. One very effective and relatively direct mechanism concerns the regulation of the stability of mRNAs. All organisms have evolved diverse and powerful mechanisms to achieve this. In order to better comprehend the regulation in living cells, biochemists have studied specific degradation mechanisms in detail. In addition to that, modern high-throughput techniques allow to obtain quantitative data on a global scale by parallel analysis of the decay patterns of many different mRNAs from different genes. In previous studies, the interpretation of these mRNA decay experiments relied on a simple theoretical description based on an exponential decay. However, this does not account for the complexity of the responsible mechanisms and, as a consequence, the exponential decay is often not in agreement with the experimental decay patterns. We have developed an improved and more general theory of mRNA degradation which provides a general framework of mRNA expression and allows describing specific degradation mechanisms. We have made an attempt to provide detailed models for the regulation in different organisms. In the yeast S. cerevisiae, different degradation pathways are known to compete and furthermore most of them rely on the biochemical modification of mRNA molecules. In bacteria such as E. coli, degradation proceeds primarily endonucleolytically, i.e. it is governed by the initial cleavage within the coding region. In addition, it is often coupled to the level of maturity and the size of the polysome of an mRNA. Both for S. cerevisiae and E. coli, our descriptions lead to a considerable improvement of the interpretation of experimental data. The general outcome is that the degradation of mRNA must be described by an age-dependent degradation rate, which can be interpreted as a consequence of molecular aging of mRNAs. Within our theory, we find adequate ways to address this much debated topic from a theoretical perspective. The improvements of the understanding of mRNA degradation can be readily applied to further comprehend the mRNA expression under different internal or environmental conditions such as after the induction of transcription or stress application. Also, the role of mRNA decay can be assessed in the context of translation and protein synthesis. The ultimate goal in understanding gene regulation mediated by mRNA stability will be to identify the relevance and biological function of different mechanisms. Once more quantitative data will become available, our description allows to elaborate the role of each mechanism by devising a suitable model.
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.
A key non-destructive technique for analysis, optimization and developing of new functional materials such as sensors, transducers, electro-optical and memory devices is presented. The Thermal-Pulse Tomography (TPT) provides high-resolution three-dimensional images of electric field and polarization distribution in a material. This thermal technique use a pulsed heating by means of focused laser light which is absorbed by opaque electrodes. The diffusion of the heat causes changes in the sample geometry, generating a short-circuit current or change in surface potential, which contains information about the spatial distribution of electric dipoles or space charges. Afterwards, a reconstruction of the internal electric field and polarization distribution in the material is possible via Scale Transformation or Regularization methods. In this way, the TPT was used for the first time to image the inhomogeneous ferroelectric switching in polymer ferroelectric films (candidates to memory devices). The results shows the typical pinning of electric dipoles in the ferroelectric polymer under study and support the previous hypotheses of a ferroelectric reversal at a grain level via nucleation and growth. In order to obtain more information about the impact of the lateral and depth resolution of the thermal techniques, the TPT and its counterpart called Focused Laser Intensity Modulation Method (FLIMM) were implemented in ferroelectric films with grid-shaped electrodes. The results from both techniques, after the data analysis with different regularization and scale methods, are in total agreement. It was also revealed a possible overestimated lateral resolution of the FLIMM and highlights the TPT method as the most efficient and reliable thermal technique. After an improvement in the optics, the Thermal-Pulse Tomography method was implemented in polymer-dispersed liquid crystals (PDLCs) films, which are used in electro-optical applications. The results indicated a possible electrostatic interaction between the COH group in the liquid crystals and the fluorinate atoms of the used ferroelectric matrix. The geometrical parameters of the LC droplets were partially reproduced as they were compared with Scanning Electron Microscopy (SEM) images. For further applications, it is suggested the use of a non-strong-ferroelectric polymer matrix. In an effort to develop new polymerferroelectrets and for optimizing their properties, new multilayer systems were inspected. The results of the TPT method showed the non-uniformity of the internal electric-field distribution in the shaped-macrodipoles and thus suggested the instability of the sample. Further investigation on multilayers ferroelectrets was suggested and the implementation of less conductive polymers layers too.
In this thesis, I present my contributions to the field of ultrafast molecular spectroscopy. Using the molecule 2-thiouracil as an example, I use ultrashort x-ray pulses from free- electron lasers to study the relaxation dynamics of gas-phase molecular samples. Taking advantage of the x-ray typical element- and site-selectivity, I investigate the charge flow and geometrical changes in the excited states of 2-thiouracil.
In order to understand the photoinduced dynamics of molecules, knowledge about the ground-state structure and the relaxation after photoexcitation is crucial. Therefore, a part of this thesis covers the electronic ground-state spectroscopy of mainly 2-thiouracil to provide the basis for the time-resolved experiments. Many of the previously published studies that focused on the gas-phase time-resolved dynamics of thionated uracils after UV excitation relied on information from solution phase spectroscopy to determine the excitation energies. This is not an optimal strategy as solvents alter the absorption spec- trum and, hence, there is no guarantee that liquid-phase spectra resemble the gas-phase spectra. Therefore, I measured the UV-absorption spectra of all three thionated uracils to provide a gas-phase reference and, in combination with calculations, we determined the excited states involved in the transitions.
In contrast to the UV absorption, the literature on the x-ray spectroscopy of thionated uracil is sparse. Thus, we measured static photoelectron, Auger-Meitner and x-ray absorption spectra on the sulfur L edge before or parallel to the time-resolved experiments we performed at FLASH (DESY, Hamburg). In addition, (so far unpublished) measurements were performed at the synchrotron SOLEIL (France) which have been included in this thesis and show the spin-orbit splitting of the S 2p photoline and its satellite which was not observed at the free-electron laser.
The relaxation of 2-thiouracil has been studied extensively in recent years with ultrafast visible and ultraviolet methods showing the ultrafast nature of the molecular process after photoexcitation. Ultrafast spectroscopy probing the core-level electrons provides a complementary approach to common optical ultrafast techniques. The method inherits its local sensitivity from the strongly localised core electrons. The core energies and core-valence transitions are strongly affected by local valence charge and geometry changes, and past studies have utilised this sensitivity to investigate the molecular process reflected by the ultrafast dynamics. We have built an apparatus that provides the requirements to perform time-resolved x-ray spectroscopy on molecules in the gas phase. With the apparatus, we performed UV-pump x-ray-probe electron spectroscopy on the S 2p edge of 2-thiouracil using the free-electron laser FLASH2. While the UV triggers the relaxation dynamics, the x-ray probes the single sulfur atom inside the molecule. I implemented photoline self-referencing for the photoelectron spectral analysis. This minimises the spectral jitter of the FEL, which is due to the underlying self-amplified spontaneous emission (SASE) process. With this approach, we were not only able to study dynamical changes in the binding energy of the electrons but also to detect an oscillatory behaviour in the shift of the observed photoline, which we associate with non-adiabatic dynamics involving several electronic states. Moreover, we were able to link the UV-induced shift in binding energy to the local charge flow at the sulfur which is directly connected to the electronic state. Furthermore, the analysis of the Auger-Meitner electrons shows that energy shifts observed at early stages of the photoinduced relaxation are related to the geometry change in the molecule. More specifically, the observed increase in kinetic energy of the Auger-Meitner electrons correlates with a previously predicted C=S bond stretch.
In our daily life, recurrence plays an important role on many spatial and temporal scales and in different contexts. It is the foundation of learning, be it in an evolutionary or in a neural context. It therefore seems natural that recurrence is also a fundamental concept in theoretical dynamical systems science. The way in which states of a system recur or develop in a similar way from similar initial states makes it possible to infer information about the underlying dynamics of the system. The mathematical space in which we define the state of a system (state space) is often high dimensional, especially in complex systems that can also exhibit chaotic dynamics. The recurrence plot (RP) enables us to visualize the recurrences of any high-dimensional systems in a two-dimensional, binary representation. Certain patterns in RPs can be related to physical properties of the underlying system, making the qualitative and quantitative analysis of RPs an integral part of nonlinear systems science. The presented work has a methodological focus and further develops recurrence analysis (RA) by addressing current research questions related to an increasing amount of available data and advances in machine learning techniques. By automatizing a central step in RA, namely the reconstruction of the state space from measured experimental time series, and by investigating the impact of important free parameters this thesis aims to make RA more accessible to researchers outside of physics.
The first part of this dissertation is concerned with the reconstruction of the state space from time series. To this end, a novel idea is proposed which automates the reconstruction problem in the sense that there is no need to preprocesse the data or estimate parameters a priori. The key idea is that the goodness of a reconstruction can be evaluated by a suitable objective function and that this function is minimized in the embedding process. In addition, the new method can process multivariate time series input data. This is particularly important because multi-channel sensor-based observations are ubiquitous in many research areas and continue to increase. Building on this, the described minimization problem of the objective function is then processed using a machine learning approach.
In the second part technical and methodological aspects of RA are discussed. First, we mathematically justify the idea of setting the most influential free parameter in RA, the recurrence threshold ε, in relation to the distribution of all pairwise distances in the data. This is especially important when comparing different RPs and their quantification statistics and is fundamental to any comparative study. Second, some aspects of recurrence quantification analysis (RQA) are examined. As correction schemes for biased RQA statistics, which are based on diagonal lines, we propose a simple method for dealing with border effects of an RP in RQA and a skeletonization algorithm for RPs. This results in less biased (diagonal line based) RQA statistics for flow-like data. Third, a novel type of RQA characteristic is developed, which can be viewed as a generalized non-linear powerspectrum of high dimensional systems. The spike powerspectrum transforms a spike-train like signal into its frequency domain. When transforming the diagonal line-dependent recurrence rate (τ-RR) of a RP in this way, characteristic periods, which can be seen in the state space representation of the system can be unraveled. This is not the case, when Fourier transforming τ-RR.
Finally, RA and RQA are applied to climate science in the third part and neuroscience in the fourth part. To the best of our knowledge, this is the first time RPs and RQA have been used to analyze lake sediment data in a paleoclimate context. Therefore, we first elaborate on the basic formalism and the interpretation of visually visible patterns in RPs in relation to the underlying proxy data. We show that these patterns can be used to classify certain types of variability and transitions in the Potassium record from six short (< 17m) sediment cores collected during the Chew Bahir Drilling Project. Building on this, the long core (∼ m composite) from the same site is analyzed and two types of variability and transitions are
identified and compared with ODP Site wetness index from the eastern Mediterranean. Type variability likely reflects the influence of precessional forcing in the lower latitudes at times of maximum values of the long eccentricity cycle ( kyr) of the earth’s orbit around the sun, with a tendency towards extreme events. Type variability appears to be related to the minimum values of this cycle and corresponds to fairly rapid transitions between relatively dry and relatively wet conditions.
In contrast, RQA has been applied in the neuroscientific context for almost two decades. In the final part, RQA statistics are used to quantify the complexity in a specific frequency band of multivariate EEG (electroencephalography) data. By analyzing experimental data, it can be shown that the complexity of the signal measured in this way across the sensorimotor cortex decreases as motor tasks are performed. The results are consistent with and comple- ment the well known concepts of motor-related brain processes. We assume that the thus discovered features of neuronal dynamics in the sensorimotor cortex together with the robust RQA methods for identifying and classifying these contribute to the non-invasive EEG-based development of brain-computer interfaces (BCI) for motor control and rehabilitation.
The present work is an important step towards a robust analysis of complex systems based on recurrence.
Towards seasonal prediction: stratosphere-troposphere coupling in the atmospheric model ICON-NWP
(2020)
Stratospheric variability is one of the main potential sources for sub-seasonal to seasonal predictability in mid-latitudes in winter. Stratospheric pathways play an important role for long-range teleconnections between tropical phenomena, such as the quasi-biennial oscillation (QBO) and El Niño-Southern Oscillation (ENSO), and the mid-latitudes on the one hand, and linkages between Arctic climate change and the mid-latitudes on the other hand. In order to move forward in the field of extratropical seasonal predictions, it is essential that an atmospheric model is able to realistically simulate the stratospheric circulation and variability. The numerical weather prediction (NWP) configuration of the ICOsahedral Non-hydrostatic atmosphere model ICON is currently being used by the German Meteorological Service for the regular weather forecast, and is intended to produce seasonal predictions in future. This thesis represents the first extensive evaluation of Northern Hemisphere stratospheric winter circulation in ICON-NWP by analysing a large set of seasonal ensemble experiments.
An ICON control climatology simulated with a default setup is able to reproduce the basic behaviour of the stratospheric polar vortex. However, stratospheric westerlies are significantly too weak and major stratospheric warmings too frequent, especially in January. The weak stratospheric polar vortex in ICON is furthermore connected to a mean sea level pressure (MSLP) bias pattern resembling the negative phase of the Arctic Oscillation (AO). Since a good representation of the drag exerted by gravity waves is crucial for a realistic simulation of the stratosphere, three sensitivity experiments with reduced gravity wave drag are performed. Both a reduction of the non-orographic and orographic gravity wave drag respectively, lead to a strengthening of the stratospheric vortex and thus a bias reduction in winter, in particular in January. However, the effect of the non-orographic gravity wave drag on the stratosphere is stronger. A third experiment, combining a reduced orographic and non-orographic drag, exhibits the largest stratospheric bias reductions. The analysis of stratosphere-troposphere coupling based on an index of the Northern Annular Mode demonstrates that ICON realistically represents downward coupling. This coupling is intensified and more realistic in experiments with a reduced gravity wave drag, in particular with reduced non-orographic drag. Tropospheric circulation is also affected by the reduced gravity wave drag, especially in January, when the strongly improved stratospheric circulation reduces biases in the MSLP patterns. Moreover, a retuning of the subgrid-scale orography parameterisations leads to a significant error reduction in the MSLP in all months. In conclusion, the combination of these adjusted parameterisations is recommended as a current optimal setup for seasonal simulations with ICON.
Additionally, this thesis discusses further possible influences on the stratospheric polar vortex, including the influence of tropical phenomena, such as QBO and ENSO, as well as the influence of a rapidly warming Arctic. ICON does not simulate the quasi-oscillatory behaviour of the QBO and favours weak easterlies in the tropical stratosphere. A comparison with a reanalysis composite of the easterly QBO phase reveals, that the shift towards the easterly QBO in ICON further weakens the stratospheric polar vortex. On the other hand, the stratospheric reaction to ENSO events in ICON is realistic. ICON and the reanalysis exhibit a weakened stratospheric vortex in warm ENSO years. Furthermore, in particular in winter, warm ENSO events favour the negative phase of the Arctic Oscillation, whereas cold events favour the positive phase. The ICON simulations also suggest a significant effect of ENSO on the Atlantic-European sector in late winter. To investigate the influence of Arctic climate change on mid-latitude circulation changes, two differing approaches with transient and fixed sea ice conditions are chosen. Neither ICON approach exhibits the mid-latitude tropospheric negative Arctic Oscillation circulation response to amplified Arctic warming, as it is discussed on the basis of observational evidence. Nevertheless, adding a new model to the current and active discussion on Arctic-midlatitude linkages, further contributes to the understanding of divergent conclusions between model and observational studies.
Classical semiconductor physics has been continuously improving electronic components such as diodes, light-emitting diodes, solar cells and transistors based on highly purified inorganic crystals over the past decades. Organic semiconductors, notably polymeric, are a comparatively young field of research, the first light-emitting diode based on conjugated polymers having been demonstrated in 1990. Polymeric semiconductors are of tremendous interest for high-volume, low-cost manufacturing ("printed electronics"). Due to their rather simple device structure mostly comprising only one or two functional layers, polymeric diodes are much more difficult to optimize compared to small-molecular organic devices. Usually, functions such as charge injection and transport are handled by the same material which thus needs to be highly optimized. The present work contributes to expanding the knowledge on the physical mechanisms determining device performance by analyzing the role of charge injection and transport on device efficiency for blue and white-emitting devices, based on commercially relevant spiro-linked polyfluorene derivatives. It is shown that such polymers can act as very efficient electron conductors and that interface effects such as charge trapping play the key role in determining the overall device efficiency. This work contributes to the knowledge of how charges drift through the polymer layer to finally find neutral emissive trap states and thus allows a quantitative prediction of the emission color of multichromophoric systems, compatible with the observed color shifts upon driving voltage and temperature variation as well as with electrical conditioning effects. In a more methodically oriented part, it is demonstrated that the transient device emission observed upon terminating the driving voltage can be used to monitor the decay of geminately-bound species as well as to determine trapped charge densities. This enables direct comparisons with numerical simulations based on the known properties of charge injection, transport and recombination. The method of charge extraction under linear increasing voltages (CELIV) is investigated in some detail, correcting for errors in the published approach and highlighting the role of non-idealized conditions typically present in experiments. An improved method is suggested to determine the field dependence of charge mobility in a more accurate way. Finally, it is shown that the neglect of charge recombination has led to a misunderstanding of experimental results in terms of a time-dependent mobility relaxation.
Synchronization – the adjustment of rhythms among coupled self-oscillatory systems – is a fascinating dynamical phenomenon found in many biological, social, and technical systems.
The present thesis deals with synchronization in finite ensembles of weakly coupled self-sustained oscillators with distributed frequencies.
The standard model for the description of this collective phenomenon is the Kuramoto model – partly due to its analytical tractability in the thermodynamic limit of infinitely many oscillators. Similar to a phase transition in the thermodynamic limit, an order parameter indicates the transition from incoherence to a partially synchronized state. In the latter, a part of the oscillators rotates at a common frequency. In the finite case, fluctuations occur, originating from the quenched noise of the finite natural frequency sample.
We study intermediate ensembles of a few hundred oscillators in which fluctuations are comparably strong but which also allow for a comparison to frequency distributions in the infinite limit.
First, we define an alternative order parameter for the indication of a collective mode in the finite case. Then we test the dependence of the degree of synchronization and the mean rotation frequency of the collective mode on different characteristics for different coupling strengths.
We find, first numerically, that the degree of synchronization depends strongly on the form (quantified by kurtosis) of the natural frequency sample and the rotation frequency of the collective mode depends on the asymmetry (quantified by skewness) of the sample. Both findings are verified in the infinite limit.
With these findings, we better understand and generalize observations of other authors. A bit aside of the general line of thoughts, we find an analytical expression for the volume contraction in phase space.
The second part of this thesis concentrates on an ordering effect of the finite-size fluctuations. In the infinite limit, the oscillators are separated into coherent and incoherent thus ordered and disordered oscillators. In finite ensembles, finite-size fluctuations can generate additional order among the asynchronous oscillators. The basic principle – noise-induced synchronization – is known from several recent papers. Among coupled oscillators, phases are pushed together by the order parameter fluctuations, as we on the one hand show directly and on the other hand quantify with a synchronization measure from directed statistics between pairs of passive oscillators.
We determine the dependence of this synchronization measure from the ratio of pairwise natural frequency difference and variance of the order parameter fluctuations. We find a good agreement with a simple analytical model, in which we replace the deterministic fluctuations of the order parameter by white noise.
Wetting and phase transitions play a very important role our daily life. Molecularly thin films of long-chain alkanes at solid/vapour interfaces (e.g. C30H62 on silicon wafers) are very good model systems for studying the relation between wetting behaviour and (bulk) phase transitions. Immediately above the bulk melting temperature the alkanes wet partially the surface (drops). In this temperature range the substrate surface is covered with a molecularly thin ordered, solid-like alkane film ("surface freezing"). Thus, the alkane melt wets its own solid only partially which is a quite rare phenomenon in nature. The thesis treats about how the alkane melt wets its own solid surface above and below the bulk melting temperature and about the corresponding melting and solidification processes. Liquid alkane drops can be undercooled to few degrees below the bulk melting temperature without immediate solidification. This undercooling behaviour is quite frequent and theoretical quite well understood. In some cases, slightly undercooled drops start to build two-dimensional solid terraces without bulk solidification. The terraces grow radially from the liquid drops on the substrate surface. They consist of few molecular layers with the thickness multiple of all-trans length of the molecule. By analyzing the terrace growth process one can find that, both below and above the melting point, the entire substrate surface is covered with a thin film of mobile alkane molecules. The presence of this film explains how the solid terrace growth is feeded: the alkane molecules flow through it from the undercooled drops to the periphery of the terrace. The study shows for the first time the coexistence of a molecularly thin film ("precursor") with partially wetting bulk phase. The formation and growth of the terraces is observed only in a small temperature interval in which the 2D nucleation of terraces is more likely than the bulk solidification. The nucleation mechanisms for 2D solidification are also analyzed in this work. More surprising is the terrace behaviour above bulk the melting temperature. The terraces can be slightly overheated before they melt. The melting does not occur all over the surface as a single event; instead small drops form at the terrace edge. Subsequently these drops move on the surface "eating" the solid terraces on their way. By this they grow in size leaving behind paths from were the material was collected. Both overheating and droplet movement can be explained by the fact that the alkane melt wets only partially its own solid. For the first time, these results explicitly confirm the supposed connection between the absence of overheating in solid and "surface melting": the solids usually start to melt without an energetic barrier from the surface at temperatures below the bulk melting point. Accordingly, the surface freezing of alkanes give rise of an energetic barrier which leads to overheating.
In the frame of a world fighting a dramatic global warming caused by human-related activities, research towards the development of renewable energies plays a crucial role. Solar energy is one of the most important clean energy sources and its role in the satisfaction of the global energy demand is set to increase. In this context, a particular class of materials captured the attention of the scientific community for its attractive properties: halide perovskites. Devices with perovskite as light-absorber saw an impressive development within the last decade, reaching nowadays efficiencies comparable to mature photovoltaic technologies like silicon solar cells. Yet, there are still several roadblocks to overcome before a wide-spread commercialization of this kind of devices is enabled. One of the critical points lies at the interfaces: perovskite solar cells (PSCs) are made of several layers with different chemical and physical features. In order for the device to function properly, these properties have to be well-matched.
This dissertation deals with some of the challenges related to interfaces in PSCs, with a focus on the interface between the perovskite material itself and the subsequent charge transport layer. In particular, molecular assemblies with specific properties are deposited on the perovskite surface to functionalize it. The functionalization results in energy level alignment adjustment, interfacial losses reduction, and stability improvement.
First, a strategy to tune the perovskite’s energy levels is introduced: self-assembled monolayers of dipolar molecules are used to functionalize the surface, obtaining simultaneously a shift in the vacuum level position and a saturation of the dangling bonds at the surface. A shift in the vacuum level corresponds to an equal change in work function, ionization energy, and electron affinity. The direction of the shift depends on the direction of the collective interfacial dipole. The magnitude of the shift can be tailored by controlling the deposition parameters, such as the concentration of the solution used for the deposition. The shift for different molecules is characterized by several non-invasive techniques, including in particular Kelvin probe. Overall, it is shown that it is possible to shift the perovskite energy levels in both directions by several hundreds of meV. Moreover, interesting insights on the molecules deposition dynamics are revealed.
Secondly, the application of this strategy in perovskite solar cells is explored. Devices with different perovskite compositions (“triple cation perovskite” and MAPbBr3) are prepared. The two resulting model systems present different energetic offsets at the perovskite/hole-transport layer interface. Upon tailored perovskite surface functionalization, the devices show a stabilized open circuit voltage (Voc) enhancement of approximately 60 meV on average for devices with MAPbBr3, while the impact is limited on triple-cation solar cells. This suggests that the proposed energy level tuning method is valid, but its effectiveness depends on factors such as the significance of the energetic offset compared to the other losses in the devices.
Finally, the above presented method is further developed by incorporating the ability to interact with the perovskite surface directly into a novel hole-transport material (HTM), named PFI. The HTM can anchor to the perovskite halide ions via halogen bonding (XB). Its behaviour is compared to that of another HTM (PF) with same chemical structure and properties, except for the ability of forming XB. The interaction of perovskite with PFI and PF is characterized through UV-Vis, atomic force microscopy and Kelvin probe measurements combined with simulations. Compared to PF, PFI exhibits enhanced resilience against solvent exposure and improved energy level alignment with the perovskite layer. As a consequence, devices comprising PFI show enhanced Voc and operational stability during maximum-power-point tracking, in addition to hysteresis reduction. XB promotes the formation of a high-quality interface by anchoring to the halide ions and forming a stable and ordered interfacial layer, showing to be a particularly interesting candidate for the development of tailored charge transport materials in PSCs.
Overall, the results exposed in this dissertation introduce and discuss a versatile tool to functionalize the perovskite surface and tune its energy levels. The application of this method in devices is explored and insights on its challenges and advantages are given. Within this frame, the results shed light on XB as ideal interaction for enhancing stability and efficiency in perovskite-based devices.
In this thesis, the two prototype catalysts Fe(CO)₅ and Cr(CO)₆ are investigated with time-resolved photoelectron spectroscopy at a high harmonic setup. In both of these metal carbonyls, a UV photon can induce the dissociation of one or more ligands of the complex. The mechanism of the dissociation has been debated over the last decades. The electronic dynamics of the first dissociation occur on the femtosecond timescale.
For the experiment, an existing high harmonic setup was moved to a new location, was extended, and characterized. The modified setup can induce dynamics in gas phase samples with photon energies of 1.55eV, 3.10eV, and 4.65eV. The valence electronic structure of the samples can be probed with photon energies between 20eV and 40eV. The temporal resolution is 111fs to 262fs, depending on the combination of the two photon energies.
The electronically excited intermediates of the two complexes, as well as of the reaction product Fe(CO)₄, could be observed with photoelectron spectroscopy in the gas phase for the first time. However, photoelectron spectroscopy gives access only to the final ionic states. Corresponding calculations to simulate these spectra are still in development. The peak energies and their evolution in time with respect to the initiation pump pulse have been determined, these peaks have been assigned based on literature data. The spectra of the two complexes show clear differences. The dynamics have been interpreted with the assumption that the motion of peaks in the spectra relates to the movement of the wave packet in the multidimensional energy landscape. The results largely confirm existing models for the reaction pathways. In both metal carbonyls, this pathway involves a direct excitation of the wave packet to a metal-to-ligand charge transfer state and the subsequent crossing to a dissociative ligand field state. The coupling of the electronic dynamics to the nuclear dynamics could explain the slower dissociation in Fe(CO)₅ as compared to Cr(CO)₆.
Within the course of this thesis, I have investigated the complex interplay between electron and lattice dynamics in nanostructures of perovskite oxides. Femtosecond hard X-ray pulses were utilized to probe the evolution of atomic rearrangement directly, which is driven by ultrafast optical excitation of electrons. The physics of complex materials with a large number of degrees of freedom can be interpreted once the exact fingerprint of ultrafast lattice dynamics in time-resolved X-ray diffraction experiments for a simple model system is well known. The motion of atoms in a crystal can be probed directly and in real-time by femtosecond pulses of hard X-ray radiation in a pump-probe scheme. In order to provide such ultrashort X-ray pulses, I have built up a laser-driven plasma X-ray source. The setup was extended by a stable goniometer, a two-dimensional X-ray detector and a cryogen-free cryostat. The data acquisition routines of the diffractometer for these ultrafast X-ray diffraction experiments were further improved in terms of signal-to-noise ratio and angular resolution. The implementation of a high-speed reciprocal-space mapping technique allowed for a two-dimensional structural analysis with femtosecond temporal resolution. I have studied the ultrafast lattice dynamics, namely the excitation and propagation of coherent phonons, in photoexcited thin films and superlattice structures of the metallic perovskite SrRuO3. Due to the quasi-instantaneous coupling of the lattice to the optically excited electrons in this material a spatially and temporally well-defined thermal stress profile is generated in SrRuO3. This enables understanding the effect of the resulting coherent lattice dynamics in time-resolved X-ray diffraction data in great detail, e.g. the appearance of a transient Bragg peak splitting in both thin films and superlattice structures of SrRuO3. In addition, a comprehensive simulation toolbox to calculate the ultrafast lattice dynamics and the resulting X-ray diffraction response in photoexcited one-dimensional crystalline structures was developed in this thesis work. With the powerful experimental and theoretical framework at hand, I have studied the excitation and propagation of coherent phonons in more complex material systems. In particular, I have revealed strongly localized charge carriers after above-bandgap femtosecond photoexcitation of the prototypical multiferroic BiFeO3, which are the origin of a quasi-instantaneous and spatially inhomogeneous stress that drives coherent phonons in a thin film of the multiferroic. In a structurally imperfect thin film of the ferroelectric Pb(Zr0.2Ti0.8)O3, the ultrafast reciprocal-space mapping technique was applied to follow a purely strain-induced change of mosaicity on a picosecond time scale. These results point to a strong coupling of in- and out-of-plane atomic motion exclusively mediated by structural defects.
Ultrafast magnetisation dynamics have been investigated intensely for two decades. The recovery process after demagnetisation, however, was rarely studied experimentally and discussed in detail. The focus of this work lies on the investigation of the magnetisation on long timescales after laser excitation. It combines two ultrafast time resolved methods to study the relaxation of the magnetic and lattice system after excitation with a high fluence ultrashort laser pulse. The magnetic system is investigated by time resolved measurements of the magneto-optical Kerr effect. The experimental setup has been implemented in the scope of this work. The lattice dynamics were obtained with ultrafast X-ray diffraction. The combination of both techniques leads to a better understanding of the mechanisms involved in magnetisation recovery from a non-equilibrium condition. Three different groups of samples are investigated in this work: Thin Nickel layers capped with nonmagnetic materials, a continuous sample of the ordered L10 phase of Iron Platinum and a sample consisting of Iron Platinum nanoparticles embedded in a carbon matrix. The study of the remagnetisation reveals a general trend for all of the samples: The remagnetisation process can be described by two time dependences. A first exponential recovery that slows down with an increasing amount of energy absorbed in the system until an approximately linear time dependence is observed. This is followed by a second exponential recovery. In case of low fluence excitation, the first recovery is faster than the second. With increasing fluence the first recovery is slowed down and can be described as a linear function. If the pump-induced temperature increase in the sample is sufficiently high, a phase transition to a paramagnetic state is observed. In the remagnetisation process, the transition into the ferromagnetic state is characterised by a distinct transition between the linear and exponential recovery. From the combination of the transient lattice temperature Tp(t) obtained from ultrafast X-ray measurements and magnetisation M(t) gained from magneto-optical measurements we construct the transient magnetisation versus temperature relations M(Tp). If the lattice temperature remains below the Curie temperature the remagnetisation curve M(Tp) is linear and stays below the M(T) curve in equilibrium in the continuous transition metal layers. When the sample is heated above phase transition, the remagnetisation converges towards the static temperature dependence. For the granular Iron Platinum sample the M(Tp) curves for different fluences coincide, i.e. the remagnetisation follows a similar path irrespective of the initial laser-induced temperature jump.
In processing and data storage mainly ferromagnetic (FM) materials are being used. Approaching physical limits, new concepts have to be found for faster, smaller switches, for higher data densities and more energy efficiency. Some of the discussed new concepts involve the material classes of correlated oxides and materials with antiferromagnetic coupling. Their applicability depends critically on their switching behavior, i.e., how fast and how energy efficient material properties can be manipulated. This thesis presents investigations of ultrafast non-equilibrium phase transitions on such new materials. In transition metal oxides (TMOs) the coupling of different degrees of freedom and resulting low energy excitation spectrum often result in spectacular changes of macroscopic properties (colossal magneto resistance, superconductivity, metal-to-insulator transitions) often accompanied by nanoscale order of spins, charges, orbital occupation and by lattice distortions, which make these material attractive. Magnetite served as a prototype for functional TMOs showing a metal-to-insulator-transition (MIT) at T = 123 K. By probing the charge and orbital order as well as the structure after an optical excitation we found that the electronic order and the structural distortion, characteristics of the insulating phase in thermal equilibrium, are destroyed within the experimental resolution of 300 fs. The MIT itself occurs on a 1.5 ps timescale. It shows that MITs in functional materials are several thousand times faster than switching processes in semiconductors. Recently ferrimagnetic and antiferromagnetic (AFM) materials have become interesting. It was shown in ferrimagnetic GdFeCo, that the transfer of angular momentum between two opposed FM subsystems with different time constants leads to a switching of the magnetization after laser pulse excitation. In addition it was theoretically predicted that demagnetization dynamics in AFM should occur faster than in FM materials as no net angular momentum has to be transferred out of the spin system. We investigated two different AFM materials in order to learn more about their ultrafast dynamics. In Ho, a metallic AFM below T ≈ 130 K, we found that the AFM Ho can not only be faster but also ten times more energy efficiently destroyed as order in FM comparable metals. In EuTe, an AFM semiconductor below T ≈ 10 K, we compared the loss of magnetization and laser-induced structural distortion in one and the same experiment. Our experiment shows that they are effectively disentangled. An exception is an ultrafast release of lattice dynamics, which we assign to the release of magnetostriction. The results presented here were obtained with time-resolved resonant soft x-ray diffraction at the Femtoslicing source of the Helmholtz-Zentrum Berlin and at the free-electron laser in Stanford (LCLS). In addition the development and setup of a new UHV-diffractometer for these experiments will be reported.
This publication based thesis, which consists of seven published articles, summarizes my contributions to the research field of laser excited ultrafast structural dynamics. The coherent and incoherent lattice dynamics on microscopic length scales are detected by ultrashort optical and X-ray pulses. The understanding of the complex physical processes is essential for future improvements of technological applications. For this purpose, tabletop soruces and large scale facilities, e.g. synchrotrons, are employed to study structural dynamics of longitudinal acoustic strain waves and heat transport. The investigated effects cover timescales from hundreds of femtoseconds up to several microseconds.
The main part of this thesis is dedicated to the investigation of tailored phonon wave packets propagating in perovskite nanostructures. Tailoring is achieved either by laser excitation of nanostructured bilayer samples or by a temporal series of laser pulses. Due to the propagation of longitudinal acoustic phonons, the out-of-plane lattice spacing of a thin film insulator-metal bilayer sample is modulated on an ultrafast timescale. This leads to an ultrafast modulation of the X-ray diffraction efficiency which is employed as a phonon Bragg switch to shorten hard X-ray pulses emitted from a 3rd generation synchrotron.
In addition, we have observed nonlinear mixing of high amplitude phonon wave packets which originates from an anharmonic interatomic potential. A chirped optical pulse sequence excites a narrow band phonon wave packet with specific momentum and energy. The second harmonic generation of these phonon wave packets is followed by ultrafast X-ray diffraction. Phonon upconversion takes place because the high amplitude phonon wave packet modulates the acoustic properties of the crystal which leads to self steepening and to the successive generation of higher harmonics of the phonon wave packet.
Furthermore, we have demonstrated ultrafast strain in direction parallel to the sample surface. Two consecutive so-called transient grating excitations displaced in space and time are used to coherently control thermal gradients and surface acoustic modes. The amplitude of the coherent and incoherent surface excursion is disentangled by time resolved X-ray reflectivity measurements. We calibrate the absolute amplitude of thermal and acoustic surface excursion with measurements of longitudinal phonon propagation. In addition, we develop a diffraction model which allows for measuring the surface excursion on an absolute length scale with sub-Äangström precision. Finally, I demonstrate full coherent control of an excited surface deformation by amplifying and suppressing thermal and coherent excitations at the surface of a laser-excited Yttrium-manganite sample.
In this dissertation the lattice and the magnetic recovery dynamics of the two heavy rare-earth metals Dy and Gd after femtosecond photoexcitation are described. For the investigations, thin films of Dy and Gd were measured at low temperatures in the antiferromagnetic phase of Dy and close to room temperature in the ferromagnetic phase of Gd. Two different optical pump-x-ray probe techniques were employed: Ultrafast x-ray diffraction with hard x-rays (UXRD) yields the structural response of heavy rare-earth metals and resonant soft (elastic) x-ray diffraction (RSXD), which allows measuring directly changes in the helical antiferromagnetic order of Dy. The combination of both techniques enables to study the complex interaction between the magnetic and the phononic subsystems.
Scientific inquiry requires that we formulate not only what we know, but also what we do not know and by how much. In climate data analysis, this involves an accurate specification of measured quantities and a consequent analysis that consciously propagates the measurement errors at each step. The dissertation presents a thorough analytical method to quantify errors of measurement inherent in paleoclimate data. An additional focus are the uncertainties in assessing the coupling between different factors that influence the global mean temperature (GMT).
Paleoclimate studies critically rely on `proxy variables' that record climatic signals in natural archives. However, such proxy records inherently involve uncertainties in determining the age of the signal. We present a generic Bayesian approach to analytically determine the proxy record along with its associated uncertainty, resulting in a time-ordered sequence of correlated probability distributions rather than a precise time series. We further develop a recurrence based method to detect dynamical events from the proxy probability distributions. The methods are validated with synthetic examples and
demonstrated with real-world proxy records. The proxy estimation step reveals the interrelations between proxy variability and uncertainty. The recurrence analysis of the East Asian Summer Monsoon during the last 9000 years confirms the well-known `dry' events at 8200 and 4400 BP, plus an additional significantly dry event at 6900 BP.
We also analyze the network of dependencies surrounding GMT. We find an intricate, directed network with multiple links between the different factors at multiple time delays. We further uncover a significant feedback from the GMT to the El Niño Southern Oscillation at quasi-biennial timescales. The analysis highlights the need of a more nuanced formulation of influences between different climatic factors, as well as the limitations in trying to estimate such dependencies.
In this thesis, the dependencies of charge localization and itinerance in two classes of aromatic molecules are accessed: pyridones and porphyrins. The focus lies on the effects of isomerism, complexation, solvation, and optical excitation, which are concomitant with different crucial biological applications of specific members of these groups of compounds. Several porphyrins play key roles in the metabolism of plants and animals. The nucleobases, which store the genetic information in the DNA and RNA are pyridone derivatives. Additionally, a number of vitamins are based on these two groups of substances.
This thesis aims to answer the question of how the electronic structure of these classes of molecules is modified, enabling the versatile natural functionality. The resulting insights into the effect of constitutional and external factors are expected to facilitate the design of new processes for medicine, light-harvesting, catalysis, and environmental remediation.
The common denominator of pyridones and porphyrins is their aromatic character. As aromaticity was an early-on topic in chemical physics, the overview of relevant theoretical models in this work also mirrors the development of this scientific field in the 20th century. The spectroscopic investigation of these compounds has long been centered on their global, optical transition between frontier orbitals.
The utilization and advancement of X-ray spectroscopic methods characterizing the local electronic structure of molecular samples form the core of this thesis. The element selectivity of the near-edge X-ray absorption fine structure (NEXAFS) is employed to probe the unoccupied density of states at the nitrogen site, which is key for the chemical reactivity of pyridones and porphyrins. The results contribute to the growing database of NEXAFS features and their interpretation, e.g., by advancing the debate on the porphyrin N K-edge through systematic experimental and theoretical arguments. Further, a state-of-the-art laser pump – NEXAFS probe scheme is used to characterize the relaxation pathway of a photoexcited porphyrin on the atomic level.
Resonant inelastic X-ray scattering (RIXS) provides complementary results by accessing the highest occupied valence levels including symmetry information. It is shown that RIXS is an effective experimental tool to gain detailed information on charge densities of individual species in tautomeric mixtures. Additionally, the hRIXS and METRIXS high-resolution RIXS spectrometers, which have been in part commissioned in the course of this thesis, will gain access to the ultra-fast and thermal chemistry of pyridones, porphyrins, and many other compounds.
With respect to both classes of bio-inspired aromatic molecules, this thesis establishes that even though pyridones and porphyrins differ largely by their optical absorption bands and hydrogen bonding abilities, they all share a global stabilization of local constitutional changes and relevant external perturbation. It is because of this wide-ranging response that pyridones and porphyrins can be applied in a manifold of biological and technical processes.
The near-Earth space environment is a highly complex system comprised of several regions and particle populations hazardous to satellite operations. The trapped particles in the radiation belts and ring current can cause significant damage to satellites during space weather events, due to deep dielectric and surface charging. Closer to Earth is another important region, the ionosphere, which delays the propagation of radio signals and can adversely affect navigation and positioning. In response to fluctuations in solar and geomagnetic activity, both the inner-magnetospheric and ionospheric populations can undergo drastic and sudden changes within minutes to hours, which creates a challenge for predicting their behavior. Given the increasing reliance of our society on satellite technology, improving our understanding and modeling of these populations is a matter of paramount importance.
In recent years, numerous spacecraft have been launched to study the dynamics of particle populations in the near-Earth space, transforming it into a data-rich environment. To extract valuable insights from the abundance of available observations, it is crucial to employ advanced modeling techniques, and machine learning methods are among the most powerful approaches available. This dissertation employs long-term satellite observations to analyze the processes that drive particle dynamics, and builds interdisciplinary links between space physics and machine learning by developing new state-of-the-art models of the inner-magnetospheric and ionospheric particle dynamics.
The first aim of this thesis is to investigate the behavior of electrons in Earth's radiation belts and ring current. Using ~18 years of electron flux observations from the Global Positioning System (GPS), we developed the first machine learning model of hundreds-of-keV electron flux at Medium Earth Orbit (MEO) that is driven solely by solar wind and geomagnetic indices and does not require auxiliary flux measurements as inputs. We then proceeded to analyze the directional distributions of electrons, and for the first time, used Fourier sine series to fit electron pitch angle distributions (PADs) in Earth's inner magnetosphere. We performed a superposed epoch analysis of 129 geomagnetic storms during the Van Allen Probes era and demonstrated that electron PADs have a strong energy-dependent response to geomagnetic activity. Additionally, we showed that the solar wind dynamic pressure could be used as a good predictor of the PAD dynamics. Using the observed dependencies, we created the first PAD model with a continuous dependence on L, magnetic local time (MLT) and activity, and developed two techniques to reconstruct near-equatorial electron flux observations from low-PA data using this model.
The second objective of this thesis is to develop a novel model of the topside ionosphere. To achieve this goal, we collected observations from five of the most widely used ionospheric missions and intercalibrated these data sets. This allowed us to use these data jointly for model development, validation, and comparison with other existing empirical models. We demonstrated, for the first time, that ion density observations by Swarm Langmuir Probes exhibit overestimation (up to ~40-50%) at low and mid-latitudes on the night side, and suggested that the influence of light ions could be a potential cause of this overestimation. To develop the topside model, we used 19 years of radio occultation (RO) electron density profiles, which were fitted with a Chapman function with a linear dependence of scale height on altitude. This approximation yields 4 parameters, namely the peak density and height of the F2-layer and the slope and intercept of the linear scale height trend, which were modeled using feedforward neural networks (NNs). The model was extensively validated against both RO and in-situ observations and was found to outperform the International Reference Ionosphere (IRI) model by up to an order of magnitude. Our analysis showed that the most substantial deviations of the IRI model from the data occur at altitudes of 100-200 km above the F2-layer peak. The developed NN-based ionospheric model reproduces the effects of various physical mechanisms observed in the topside ionosphere and provides highly accurate electron density predictions.
This dissertation provides an extensive study of geospace dynamics, and the main results of this work contribute to the improvement of models of plasma populations in the near-Earth space environment.
We calculate the additional carbon emissions as a result of the conversion of natural land in a process of urbanisation; and the change of carbon flows by “urbanised” ecosystems, when the atmospheric carbon is exported to the neighboring territories, from 1980 till 2050 for the eight regions of the world. As a scenario we use combined UN and demographic model′s prognoses for regional total and urban population growth. The calculations of urban areas dynamics are based on two models: the regression model and the Gamma-model. The urbanised area is sub-divided on built-up, „green“ (parks, etc.) and informal settlements (favelas) areas. The next step is to calculate the regional and world dynamics of carbon emission and export, and the annual total carbon balance. Both models give similar results with some quantitative differences. In the first model, the world annual emissions attain a maximum of 205 MtC/year between 2020-2030. Emissions will then slowly decrease. The maximum contributions are given by China and the Asia and Pacific regions. In the second model, world annual emissions increase to 1.25 GtC in 2005, beginning to decrease afterwards. If we compare the emission maximum with the annual emission caused by deforestation, 1.36GtC per year, then we can say that the role of urbanised territories (UT) is of a comparable magnitude. Regarding the world annual export of carbon by UT, we observe its monotonous growth by three times, from 24 MtC to 66 MtC in the first model, and from 249 MtC to 505 MtC in the second one. The latter, is therefore comparable to the amount of carbon transported by rivers into the ocean (196-537 MtC). By estimating the total balance we find that urbanisation shifts the total balance towards a “sink” state. The urbanisation is inhibited in the interval 2020-2030, and by 2050 the growth of urbanised areas would almost stop. Hence, the total emission of natural carbon at that stage will stabilise at the level of the 1980s (80 MtC per year). As estimated by the second model, the total balance, being almost constant until 2000, then starts to decrease at an almost constant rate. We can say that by the end of the XXI century, the total carbon balance will be equal to zero, when the exchange flows are fully balanced, and may even be negative, when the system begins to take up carbon from the atmosphere, i.e., becomes a “sink”.
In this work we investigated ultrafast demagnetization in a Heusler-alloy. This material belongs to the halfmetal and exists in a ferromagnetic phase. A special feature of investigated alloy is a structure of electronic bands. The last leads to the specific density of the states. Majority electrons form a metallic like structure while minority electrons form a gap near the Fermi-level, like in semiconductor. This particularity offers a good possibility to use this material as model-like structure and to make some proof of principles concerning demagnetization. Using pump-probe experiments we carried out time-resolved measurements to figure out the times of demagnetization. For the pumping we used ultrashort laser pulses with duration around 100 fs. Simultaneously we used two excitation regimes with two different wavelengths namely 400 nm and 1240 nm. Decreasing the energy of photons to the gap size of the minority electrons we explored the effect of the gap on the demagnetization dynamics. During this work we used for the first time OPA (Optical Parametrical Amplifier) for the generation of the laser irradiation in a long-wave regime. We tested it on the FETOSPEX-beamline in BASSYII electron storage ring. With this new technique we measured wavelength dependent demagnetization dynamics. We estimated that the demagnetization time is in a correlation with photon energy of the excitation pulse. Higher photon energy leads to the faster demagnetization in our material. We associate this result with the existence of the energy-gap for minority electrons and explained it with Elliot-Yaffet-scattering events. Additionally we applied new probe-method for magnetization state in this work and verified their effectivity. It is about the well-known XMCD (X-ray magnetic circular dichroism) which we adopted for the measurements in reflection geometry. Static experiments confirmed that the pure electronic dynamics can be separated from the magnetic one. We used photon energy fixed on the L3 of the corresponding elements with circular polarization. Appropriate incidence angel was estimated from static measurements. Using this probe method in dynamic measurements we explored electronic and magnetic dynamics in this alloy.
What can we learn from climate data? : Methods for fluctuation, time/scale and phase analysis
(2006)
Since Galileo Galilei invented the first thermometer, researchers have tried to understand the complex dynamics of ocean and atmosphere by means of scientific methods. They observe nature and formulate theories about the climate system. Since some decades powerful computers are capable to simulate the past and future evolution of climate. Time series analysis tries to link the observed data to the computer models: Using statistical methods, one estimates characteristic properties of the underlying climatological processes that in turn can enter the models. The quality of an estimation is evaluated by means of error bars and significance testing. On the one hand, such a test should be capable to detect interesting features, i.e. be sensitive. On the other hand, it should be robust and sort out false positive results, i.e. be specific. This thesis mainly aims to contribute to methodological questions of time series analysis with a focus on sensitivity and specificity and to apply the investigated methods to recent climatological problems. First, the inference of long-range correlations by means of Detrended Fluctuation Analysis (DFA) is studied. It is argued that power-law scaling of the fluctuation function and thus long-memory may not be assumed a priori but have to be established. This requires to investigate the local slopes of the fluctuation function. The variability characteristic for stochastic processes is accounted for by calculating empirical confidence regions. The comparison of a long-memory with a short-memory model shows that the inference of long-range correlations from a finite amount of data by means of DFA is not specific. When aiming to infer short memory by means of DFA, a local slope larger than $\alpha=0.5$ for large scales does not necessarily imply long-memory. Also, a finite scaling of the autocorrelation function is shifted to larger scales in the fluctuation function. It turns out that long-range correlations cannot be concluded unambiguously from the DFA results for the Prague temperature data set. In the second part of the thesis, an equivalence class of nonstationary Gaussian stochastic processes is defined in the wavelet domain. These processes are characterized by means of wavelet multipliers and exhibit well defined time dependent spectral properties; they allow one to generate realizations of any nonstationary Gaussian process. The dependency of the realizations on the wavelets used for the generation is studied, bias and variance of the wavelet sample spectrum are calculated. To overcome the difficulties of multiple testing, an areawise significance test is developed and compared to the conventional pointwise test in terms of sensitivity and specificity. Applications to Climatological and Hydrological questions are presented. The thesis at hand mainly aims to contribute to methodological questions of time series analysis and to apply the investigated methods to recent climatological problems. In the last part, the coupling between El Nino/Southern Oscillation (ENSO) and the Indian Monsoon on inter-annual time scales is studied by means of Hilbert transformation and a curvature defined phase. This method allows one to investigate the relation of two oscillating systems with respect to their phases, independently of their amplitudes. The performance of the technique is evaluated using a toy model. From the data, distinct epochs are identified, especially two intervals of phase coherence, 1886-1908 and 1964-1980, confirming earlier findings from a new point of view. A significance test of high specificity corroborates these results. Also so far unknown periods of coupling invisible to linear methods are detected. These findings suggest that the decreasing correlation during the last decades might be partly inherent to the ENSO/Monsoon system. Finally, a possible interpretation of how volcanic radiative forcing could cause the coupling is outlined.