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Microfabricated solid-state surfaces, also called atom chip', have become a well-established technique to trap and manipulate atoms. This has simplified applications in atom interferometry, quantum information processing, and studies of many-body systems. Magnetic trapping potentials with arbitrary geommetries are generated with atom chip by miniaturized current-carrying conductors integrated on a solid substrate. Atoms can be trapped and cooled to microKelvin and even nanoKelvin temperatures in such microchip trap. However, cold atoms can be significantly perturbed by the chip surface, typically held at room temperature. The magnetic field fluctuations generated by thermal currents in the chip elements may induce spin flips of atoms and result in loss, heating and decoherence. In this thesis, we extend previous work on spin flip rates induced by magnetic noise and consider the more complex geometries that are typically encountered in atom chips: layered structures and metallic wires of finite cross-section. We also discuss a few aspects of atom chips traps built with superconducting structures that have been suggested as a means to suppress magnetic field fluctuations. The thesis describes calculations of spin flip rates based on magnetic Green functions that are computed analytically and numerically. For a chip with a top metallic layer, the magnetic noise depends essentially on the thickness of that layer, as long as the layers below have a much smaller conductivity. Based on this result, scaling laws for loss rates above a thin metallic layer are derived. A good agreement with experiments is obtained in the regime where the atom-surface distance is comparable to the skin depth of metal. Since in the experiments, metallic layers are always etched to separate wires carrying different currents, the impact of the finite lateral wire size on the magnetic noise has been taken into account. The local spectrum of the magnetic field near a metallic microstructure has been investigated numerically with the help of boundary integral equations. The magnetic noise significantly depends on polarizations above flat wires with finite lateral width, in stark contrast to an infinitely wide wire. Correlations between multiple wires are also taken into account. In the last part, superconducting atom chips are considered. Magnetic traps generated by superconducting wires in the Meissner state and the mixed state are studied analytically by a conformal mapping method and also numerically. The properties of the traps created by superconducting wires are investigated and compared to normal conducting wires: they behave qualitatively quite similar and open a route to further trap miniaturization, due to the advantage of low magnetic noise. We discuss critical currents and fields for several geometries.
In biological cells, the long-range intracellular traffic is powered by molecular motors which transport various cargos along microtubule filaments. The microtubules possess an intrinsic direction, having a 'plus' and a 'minus' end. Some molecular motors such as cytoplasmic dynein walk to the minus end, while others such as conventional kinesin walk to the plus end. Cells typically have an isopolar microtubule network. This is most pronounced in neuronal axons or fungal hyphae. In these long and thin tubular protrusions, the microtubules are arranged parallel to the tube axis with the minus ends pointing to the cell body and the plus ends pointing to the tip. In such a tubular compartment, transport by only one motor type leads to 'motor traffic jams'. Kinesin-driven cargos accumulate at the tip, while dynein-driven cargos accumulate near the cell body. We identify the relevant length scales and characterize the jamming behaviour in these tube geometries by using both Monte Carlo simulations and analytical calculations. A possible solution to this jamming problem is to transport cargos with a team of plus and a team of minus motors simultaneously, so that they can travel bidirectionally, as observed in cells. The presumably simplest mechanism for such bidirectional transport is provided by a 'tug-of-war' between the two motor teams which is governed by mechanical motor interactions only. We develop a stochastic tug-of-war model and study it with numerical and analytical calculations. We find a surprisingly complex cooperative motility behaviour. We compare our results to the available experimental data, which we reproduce qualitatively and quantitatively.
In the present dissertation paper an approach which ensures an efficient control of such diverse systems as noisy or chaotic oscillators and neural ensembles is developed. This approach is implemented by a simple linear feedback loop. The dissertation paper consists of two main parts. One part of the work is dedicated to the application of the suggested technique to a population of neurons with a goal to suppress their synchronous collective dynamics. The other part is aimed at investigating linear feedback control of coherence of a noisy or chaotic self-sustained oscillator. First we start with a problem of suppressing synchronization in a large population of interacting neurons. The importance of this task is based on the hypothesis that emergence of pathological brain activity in the case of Parkinson's disease and other neurological disorders is caused by synchrony of many thousands of neurons. The established therapy for the patients with such disorders is a permanent high-frequency electrical stimulation via the depth microelectrodes, called Deep Brain Stimulation (DBS). In spite of efficiency of such stimulation, it has several side effects and mechanisms underlying DBS remain unclear. In the present work an efficient and simple control technique is suggested. It is designed to ensure suppression of synchrony in a neural ensemble by a minimized stimulation that vanishes as soon as the tremor is suppressed. This vanishing-stimulation technique would be a useful tool of experimental neuroscience; on the other hand, control of collective dynamics in a large population of units represents an interesting physical problem. The main idea of suggested approach is related to the classical problem of oscillation theory, namely the interaction between a self-sustained (active) oscillator and a passive load (resonator). It is known that under certain conditions the passive oscillator can suppress the oscillations of an active one. In this thesis a much more complicated case of active medium, which itself consists of thousands of oscillators is considered. Coupling this medium to a specially designed passive oscillator, one can control the collective motion of the ensemble, specifically can enhance or suppress it. Having in mind a possible application in neuroscience, the problem of suppression is concentrated upon. Second, the efficiency of suggested suppression scheme is illustrated by considering more complex case, i.e. when the population of neurons generating the undesired rhythm consists of two non-overlapping subpopulations: the first one is affected by the stimulation, while the collective activity is registered from the second one. Generally speaking, the second population can be by itself both active and passive; both cases are considered here. The possible applications of suggested technique are discussed. Third, the influence of the external linear feedback on coherence of a noisy or chaotic self-sustained oscillator is considered. Coherence is one of the main properties of self-oscillating systems and plays a key role in the construction of clocks, electronic generators, lasers, etc. The coherence of a noisy limit cycle oscillator in the context of phase dynamics is evaluated by the phase diffusion constant, which is in its turn proportional to the width of the spectral peak of oscillations. Many chaotic oscillators can be described within the framework of phase dynamics, and, therefore, their coherence can be also quantified by the way of the phase diffusion constant. The analytical theory for a general linear feedback, considering noisy systems in the linear and Gaussian approximation is developed and validated by numerical results.
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.
The interaction between neuronal cells can be identified as the computing mechanism of the brain. Neurons are complex cells that do not operate in isolation, but they are organized in a highly connected network structure. There is experimental evidence that groups of neurons dynamically synchronize their activity and process brain functions at all levels of complexity. A fundamental step to prove this hypothesis is to analyze large sets of single neurons recorded in parallel. Techniques to obtain these data are meanwhile available, but advancements are needed in the pre-processing of the large volumes of acquired data and in data analysis techniques. Major issues include extracting the signal of single neurons from the noisy recordings (referred to as spike sorting) and assessing the significance of the synchrony. This dissertation addresses these issues with two complementary strategies, both founded on the manipulation of point processes under rigorous analytical control. On the one hand I modeled the effect of spike sorting errors on correlated spike trains by corrupting them with realistic failures, and studied the corresponding impact on correlation analysis. The results show that correlations between multiple parallel spike trains are severely affected by spike sorting, especially by erroneously missing spikes. When this happens sorting strategies characterized by classifying only good'' spikes (conservative strategies) lead to less accurate results than tolerant'' strategies. On the other hand, I investigated the effectiveness of methods for assessing significance that create surrogate data by displacing spikes around their original position (referred to as dithering). I provide analytical expressions of the probability of coincidence detection after dithering. The effectiveness of spike dithering in creating surrogate data strongly depends on the dithering method and on the method of counting coincidences. Closed-form expressions and bounds are derived for the case where the dither equals the allowed coincidence interval. This work provides new insights into the methodologies of identifying synchrony in large-scale neuronal recordings, and of assessing its significance.
Atmospheric circulation and the surface mass balance in a regional climate model of Antarctica
(2007)
Understanding the Earth's climate system and particularly climate variability presents one of the most difficult and urgent challenges in science. The Antarctic plays a crucial role in the global climate system, since it is the principal region of radiative energy deficit and atmospheric cooling. An assessment of regional climate model HIRHAM is presented. The simulations are generated with the HIRHAM model, which is modified for Antarctic applications. With a horizontal resolution of 55km, the model has been run for the period 1958-1998 creating long-term simulations from initial and boundary conditions provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA40 re-analysis. The model output is compared with observations from observation stations, upper air data, global atmospheric analyses and satellite data. In comparison with the observations, the evaluation shows that the simulations with the HIRHAM model capture both the large and regional scale circulation features with generally small bias in the modeled variables. On the annual time scale the largest errors in the model simulations are the overestimation total cloud cover and the colder near-surface temperature over the interior of the Antarctic plateau. The low-level temperature inversion as well as low-level wind jet is well captured by the model. The decadal scale processes were studied based on trend calculations. The long-term run was divided into two 20 years parts. The 2m temperature, 500 hPa temperature, MSLP, precipitation and net mass balance trends were calculated for both periods and over 1958 - 1998. During the last two decades the strong surface cooling was observed over the Eastern Antarctica, this result is in good agreement with the result of Chapman and Walsh (2005) who calculated the temperature trend based on the observational data. The MSLP trend reveals a big disparity between the first and second parts of the 40 year run. The overall trend shows the strengthening of the circumpolar vortex and continental anticyclone. The net mass balance as well as precipitation show a positive trend over the Antarctic Peninsula region, along Wilkes Land and in Dronning Maud Land. The Antarctic ice sheet grows over the Eastern part of Antarctica with small exceptions in Dronning Maud Land and Wilkes Land and sinks in the Antarctic Peninsula; this result is in good agreement with the satellite-measured altitude presented in Davis (2005) . To better understand the horizontal structure of MSLP, temperature and net mass balance trends the influence of the Southern Annual Mode (SAM) on the Antarctic climate was investigated. The main meteorological parameters during the positive and negative Antarctic Oscillation (AAO) phases were compared to each other. A positive/negative AAO index means strengthening/weakening of the circumpolar vortex, poleward/northward storm tracks and prevailing/weakening westerly winds. For detailed investigation of global teleconnection, two positive and one negative periods of AAO phase were chosen. The differences in MSLP and 2m temperature between positive and negative AAO years during the winter months partly explain the surface cooling during the last decades.
Electron transfer phenomena in proteins represent one of the most common types of biochemical reactions. They play a central role in energy conversion pathways in living cells, and are crucial components in respiration and photosynthesis. These complex biochemical reaction cascades consist of a series of proteins and protein complexes that couple a charge transfer to different forms of chemical energy. The efficiency and sophisticated optimisation of signal transfer in these natural redox chains has inspired engineering of artificial architectures mimicking essential properties of their natural analogues. Implementation of direct electron transfer (DET) in protein assemblies was a breakthrough in bioelectronics, providing a simple and efficient way for coupling biological recognition events to a signal transducer. DET avoids the use of redox mediators, reducing potential interferences and side reactions, as well as being more compatible with in vivo conditions. However, only a few haem proteins, including the redox protein cytochrome c (cyt.c), and blue copper enzymes show efficient DET on different kinds of electrodes. Previous investigations with cyt.c have mainly focused on heterogeneous electron transfer of monolayers of this protein on gold. An important advance was the fabrication of cyt.c multilayers by electrostatic layer-by-layer self-assembly. The ease of fabrication, the stability, and the controllable permeability of polyelectrolyte multilayers have made them particularly attractive for electroanalytical applications. With cyt.c and sulfonated polyaniline it was for the first time possible that fully electro-active multilayers of the redox protein could be prepared. This approach was extended to design an analytical signal chain based on multilayers of cyt.c and xanthine oxidase (XOD). The system does not need an external mediator but relies on an in situ generation of a mediating radical and thus allows a signal transfer from hypoxanthine via the substrate converting enzyme and cyt.c to the electrode. Another kind of a signal chain is based on assembling proteins in complexes on electrodes in such a way that a direct protein-protein electron transfer becomes feasible. This design does not need a redox mediator in analogy to natural protein communication. For this purpose, cyt.c and the enzyme bilirubin oxidase (BOD, EC 1.3.3.5) are co-immobilized in a self-assembled polyelectrolyte multilayer on gold electrodes. Although these two proteins are not natural reaction partners, the protein architecture facilitates an electron transfer from the electrode via multiple protein layers to molecular oxygen resulting in a significant catalytic reduction current. Finally, we describe a novel strategy for multi-protein layer-by-layer self-assembly combining cyt.c with an enzyme sulfite oxidase (SOx) without use of any additional polymer. Electrostatic interactions between these two proteins with rather separated pI values during the assembly process from a low ionic strength buffer were found sufficient for the layer-by-layer deposition of the both biomolecules. It is anticipated that the concepts described in this work will stimulate further progress in multilayer design of even more complex biomimetic signal cascades taking advantage of direct communication between proteins.
In this work, some new results to exploit the recurrence properties of quasiperiodic dynamical systems are presented by means of a two dimensional visualization technique, Recurrence Plots(RPs). Quasiperiodicity is the simplest form of dynamics exhibiting nontrivial recurrences, which are common in many nonlinear systems. The concept of recurrence was introduced to study the restricted three body problem and it is very useful for the characterization of nonlinear systems. I have analyzed in detail the recurrence patterns of systems with quasiperiodic dynamics both analytically and numerically. Based on a theoretical analysis, I have proposed a new procedure to distinguish quasiperiodic dynamics from chaos. This algorithm is particular useful in the analysis of short time series. Furthermore, this approach demonstrates to be efficient in recognizing regular and chaotic trajectories of dynamical systems with mixed phase space. Regarding the application to real situations, I have shown the capability and validity of this method by analyzing time series from fluid experiments.
The biological function and the technological applications of semiflexible polymers, such as DNA, actin filaments and carbon nanotubes, strongly depend on their rigidity. Semiflexible polymers are characterized by their persistence length, the definition of which is the subject of the first part of this thesis. Attractive interactions, that arise e.g.~in the adsorption, the condensation and the bundling of filaments, can change the conformation of a semiflexible polymer. The conformation depends on the relative magnitude of the material parameters and can be influenced by them in a systematic manner. In particular, the morphologies of semiflexible polymer rings, such as circular nanotubes or DNA, which are adsorbed onto substrates with three types of structures, are studied: (i) A topographical channel, (ii) a chemically modified stripe and (iii) a periodic pattern of topographical steps. The results are compared with the condensation of rings by attractive interactions. Furthermore, the bundling of two individual actin filaments, whose ends are anchored, is analyzed. This system geometry is shown to provide a systematic and quantitative method to extract the magnitude of the attraction between the filaments from experimentally observable conformations of the filaments.
Magnetorotational instability (MRI) is one of the most important and most common instabilities in astrophysics. Today it is widely accepted that it serves as a major source of turbulent viscosity in accretion disks, the most energy efficient objects in the universe. The importance of the MRI for astrophysics has been realized only in recent fifteen years. However, originally it was discovered much earlier, in 1959, in a very different context. Theoretical flow of a conducting liquid confined between differentially rotating cylinders in the presence of an external magnetic field was analyzed. The central conclusion is that the additional magnetic field parallel to the axis of rotation can destabilize otherwise stable flow. Theory of non-magnetized fluid motion between rotating cylinders has much longer history, though. It has been studied already in 1888 and today such setup is usually referred as a Taylor-Couette flow. To prove experimentally the existence of MRI in a magnetized Taylor-Couette flow is a demanding task and different MHD groups around the world try to achieve it. The main problem lies in the fact that laboratory liquid metals which are used in such experiments are characterized by small magnetic Prandtl number. Consequently rotation rates of the cylinders must be extremely large and vast amount of technical problems emerge. One of the most important difficulties is an influence of plates enclosing the cylinders in any experiment. For fast rotation the plates tend to dominate the whole flow and the MRI can not be observed. In this thesis we discuss a special helical configuration of the applied magnetic field which allows the critical rotation rates to be much smaller. If only the axial magnetic field is present, the cylinders must rotate with angular velocities corresponding to Reynolds numbers of order Re ≈ 10^6. With the helical field this number is dramatically reduced to Re ≈ 10^3. The azimuthal component of the magnetic field can be easily generated by letting an electric current through the axis of rotation, In a Taylor-Couette flow the (primary) instability manifests itself as Taylor vortices. The specific geometry of the helical magnetic field leads to a traveling wave solution and the vortices are drifting in a direction determined by rotation and the magnetic field. In an idealized study for infinitely long cylinders this is not a problem. However, if the cylinders have finite length and are bounded vertically by the plates the situation is different. In this dissertation it is shown, with use of numerical methods, that the traveling wave solution also exists for MHD Taylor-Couette flow at finite aspect ratio H/D, H being height of the cylinders, D width of the gap between them. The nonlinear simulations provide amplitudes of fluid velocity which are helpful in designing an experiment. Although the plates disturb the flow, parameters like the drift velocity indicate that the helical MRI operates in this case. The idea of the helical MRI was implemented in a very recent experiment PROMISE. The results provided, for the first time, an evidence that the (helical) MRI indeed exists. Nevertheless, the influence of the vertical endplates was evident and the experiment can be, in principle, improved. Exemplary methods of reduction of the end-effect are here proposed. Near the vertical boundaries develops an Ekman-Hartmann layer. Study of this layer for the MHD Taylor-Couette system as well as its impact on the global flow properties is presented. It is shown that the plates, especially if they are conducting, can disturb the flow far more then previously thought also for relatively slow rotation rates.
This work is concerned with the spatio-temporal structures that emerge when non-identical, diffusively coupled oscillators synchronize. It contains analytical results and their confirmation through extensive computer simulations. We use the Kuramoto model which reduces general oscillatory systems to phase dynamics. The symmetry of the coupling plays an important role for the formation of patterns. We have studied the ordering influence of an asymmetry (non-isochronicity) in the phase coupling function on the phase profile in synchronization and the intricate interplay between this asymmetry and the frequency heterogeneity in the system. The thesis is divided into three main parts. Chapter 2 and 3 introduce the basic model of Kuramoto and conditions for stable synchronization. In Chapter 4 we characterize the phase profiles in synchronization for various special cases and in an exponential approximation of the phase coupling function, which allows for an analytical treatment. Finally, in the third part (Chapter 5) we study the influence of non-isochronicity on the synchronization frequency in continuous, reaction diffusion systems and discrete networks of oscillators.
In the present dissertation paper we study problems related to synchronization phenomena in the presence of noise which unavoidably appears in real systems. One part of the work is aimed at investigation of utilizing delayed feedback to control properties of diverse chaotic dynamic and stochastic systems, with emphasis on the ones determining predisposition to synchronization. Other part deals with a constructive role of noise, i.e. its ability to synchronize identical self-sustained oscillators. First, we demonstrate that the coherence of a noisy or chaotic self-sustained oscillator can be efficiently controlled by the delayed feedback. We develop the analytical theory of this effect, considering noisy systems in the Gaussian approximation. Possible applications of the effect for the synchronization control are also discussed. Second, we consider synchrony of limit cycle systems (in other words, self-sustained oscillators) driven by identical noise. For weak noise and smooth systems we proof the purely synchronizing effect of noise. For slightly different oscillators and/or slightly nonidentical driving, synchrony becomes imperfect, and this subject is also studied. Then, with numerics we show moderate noise to be able to lead to desynchronization of some systems under certain circumstances. For neurons the last effect means “antireliability” (the “reliability” property of neurons is treated to be important from the viewpoint of information transmission functions), and we extend our investigation to neural oscillators which are not always limit cycle ones. Third, we develop a weakly nonlinear theory of the Kuramoto transition (a transition to collective synchrony) in an ensemble of globally coupled oscillators in presence of additional time-delayed coupling terms. We show that a linear delayed feedback not only controls the transition point, but effectively changes the nonlinear terms near the transition. A purely nonlinear delayed coupling does not affect the transition point, but can reduce or enhance the amplitude of collective oscillations.
Our dynamic Sun manifests its activity by different phenomena: from the 11-year cyclic sunspot pattern to the unpredictable and violent explosions in the case of solar flares. During flares, a huge amount of the stored magnetic energy is suddenly released and a substantial part of this energy is carried by the energetic electrons, considered to be the source of the nonthermal radio and X-ray radiation. One of the most important and still open question in solar physics is how the electrons are accelerated up to high energies within (the observed in the radio emission) short time scales. Because the acceleration site is extremely small in spatial extent as well (compared to the solar radius), the electron acceleration is regarded as a local process. The search for localized wave structures in the solar corona that are able to accelerate electrons together with the theoretical and numerical description of the conditions and requirements for this process, is the aim of the dissertation. Two models of electron acceleration in the solar corona are proposed in the dissertation: I. Electron acceleration due to the solar jet interaction with the background coronal plasma (the jet--plasma interaction) A jet is formed when the newly reconnected and highly curved magnetic field lines are relaxed by shooting plasma away from the reconnection site. Such jets, as observed in soft X-rays with the Yohkoh satellite, are spatially and temporally associated with beams of nonthermal electrons (in terms of the so-called type III metric radio bursts) propagating through the corona. A model that attempts to give an explanation for such observational facts is developed here. Initially, the interaction of such jets with the background plasma leads to an (ion-acoustic) instability associated with growing of electrostatic fluctuations in time for certain range of the jet initial velocity. During this process, any test electron that happen to feel this electrostatic wave field is drawn to co-move with the wave, gaining energy from it. When the jet speed has a value greater or lower than the one, required by the instability range, such wave excitation cannot be sustained and the process of electron energization (acceleration and/or heating) ceases. Hence, the electrons can propagate further in the corona and be detected as type III radio burst, for example. II. Electron acceleration due to attached whistler waves in the upstream region of coronal shocks (the electron--whistler--shock interaction) Coronal shocks are also able to accelerate electrons, as observed by the so-called type II metric radio bursts (the radio signature of a shock wave in the corona). From in-situ observations in space, e.g., at shocks related to co-rotating interaction regions, it is known that nonthermal electrons are produced preferably at shocks with attached whistler wave packets in their upstream regions. Motivated by these observations and assuming that the physical processes at shocks are the same in the corona as in the interplanetary medium, a new model of electron acceleration at coronal shocks is presented in the dissertation, where the electrons are accelerated by their interaction with such whistlers. The protons inflowing toward the shock are reflected there by nearly conserving their magnetic moment, so that they get a substantial velocity gain in the case of a quasi-perpendicular shock geometry, i.e, the angle between the shock normal and the upstream magnetic field is in the range 50--80 degrees. The so-accelerated protons are able to excite whistler waves in a certain frequency range in the upstream region. When these whistlers (comprising the localized wave structure in this case) are formed, only the incoming electrons are now able to interact resonantly with them. But only a part of these electrons fulfill the the electron--whistler wave resonance condition. Due to such resonant interaction (i.e., of these electrons with the whistlers), the electrons are accelerated in the electric and magnetic wave field within just several whistler periods. While gaining energy from the whistler wave field, the electrons reach the shock front and, subsequently, a major part of them are reflected back into the upstream region, since the shock accompanied with a jump of the magnetic field acts as a magnetic mirror. Co-moving with the whistlers now, the reflected electrons are out of resonance and hence can propagate undisturbed into the far upstream region, where they are detected in terms of type II metric radio bursts. In summary, the kinetic energy of protons is transfered into electrons by the action of localized wave structures in both cases, i.e., at jets outflowing from the magnetic reconnection site and at shock waves in the corona.
It is desirable to reduce the potential threats that result from the variability of nature, such as droughts or heat waves that lead to food shortage, or the other extreme, floods that lead to severe damage. To prevent such catastrophic events, it is necessary to understand, and to be capable of characterising, nature's variability. Typically one aims to describe the underlying dynamics of geophysical records with differential equations. There are, however, situations where this does not support the objectives, or is not feasible, e.g., when little is known about the system, or it is too complex for the model parameters to be identified. In such situations it is beneficial to regard certain influences as random, and describe them with stochastic processes. In this thesis I focus on such a description with linear stochastic processes of the FARIMA type and concentrate on the detection of long-range dependence. Long-range dependent processes show an algebraic (i.e. slow) decay of the autocorrelation function. Detection of the latter is important with respect to, e.g. trend tests and uncertainty analysis. Aiming to provide a reliable and powerful strategy for the detection of long-range dependence, I suggest a way of addressing the problem which is somewhat different from standard approaches. Commonly used methods are based either on investigating the asymptotic behaviour (e.g., log-periodogram regression), or on finding a suitable potentially long-range dependent model (e.g., FARIMA[p,d,q]) and test the fractional difference parameter d for compatibility with zero. Here, I suggest to rephrase the problem as a model selection task, i.e.comparing the most suitable long-range dependent and the most suitable short-range dependent model. Approaching the task this way requires a) a suitable class of long-range and short-range dependent models along with suitable means for parameter estimation and b) a reliable model selection strategy, capable of discriminating also non-nested models. With the flexible FARIMA model class together with the Whittle estimator the first requirement is fulfilled. Standard model selection strategies, e.g., the likelihood-ratio test, is for a comparison of non-nested models frequently not powerful enough. Thus, I suggest to extend this strategy with a simulation based model selection approach suitable for such a direct comparison. The approach follows the procedure of a statistical test, with the likelihood-ratio as the test statistic. Its distribution is obtained via simulations using the two models under consideration. For two simple models and different parameter values, I investigate the reliability of p-value and power estimates obtained from the simulated distributions. The result turned out to be dependent on the model parameters. However, in many cases the estimates allow an adequate model selection to be established. An important feature of this approach is that it immediately reveals the ability or inability to discriminate between the two models under consideration. Two applications, a trend detection problem in temperature records and an uncertainty analysis for flood return level estimation, accentuate the importance of having reliable methods at hand for the detection of long-range dependence. In the case of trend detection, falsely concluding long-range dependence implies an underestimation of a trend and possibly leads to a delay of measures needed to take in order to counteract the trend. Ignoring long-range dependence, although present, leads to an underestimation of confidence intervals and thus to an unjustified belief in safety, as it is the case for the return level uncertainty analysis. A reliable detection of long-range dependence is thus highly relevant in practical applications. Examples related to extreme value analysis are not limited to hydrological applications. The increased uncertainty of return level estimates is a potentially problem for all records from autocorrelated processes, an interesting examples in this respect is the assessment of the maximum strength of wind gusts, which is important for designing wind turbines. The detection of long-range dependence is also a relevant problem in the exploration of financial market volatility. With rephrasing the detection problem as a model selection task and suggesting refined methods for model comparison, this thesis contributes to the discussion on and development of methods for the detection of long-range dependence.
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.
In this thesis the interplay between hydrodynamic transport and specific adhesion is theoretically investigated. An important biological motivation for this work is the rolling adhesion of white blood cells experimentally investigated in flow chambers. There, specific adhesion is mediated by weak bonds between complementary molecular building blocks which are either located on the cell surface (receptors) or attached to the bottom plate of the flow chamber (ligands). The model system under consideration is a hard sphere covered with receptors moving above a planar ligand-bearing wall. The motion of the sphere is influenced by a simple shear flow, deterministic forces, and Brownian motion. An algorithm is given that allows to numerically simulate this motion as well as the formation and rupture of bonds between receptors and ligands. The presented algorithm spatially resolves receptors and ligands. This opens up the perspective to apply the results also to flow chamber experiments done with patterned substrates based on modern nanotechnological developments. In the first part the influence of flow rate, as well as of the number and geometry of receptors and ligands, on the probability for initial binding is studied. This is done by determining the mean time that elapses until the first encounter between a receptor and a ligand occurs. It turns out that besides the number of receptors, especially the height by which the receptors are elevated above the surface of the sphere plays an important role. These findings are in good agreement with observations of actual biological systems like white blood cells or malaria-infected red blood cells. Then, the influence of bonds which have formed between receptors and ligands, but easily rupture in response to force, on the motion of the sphere is studied. It is demonstrated that different states of motion-for example rolling-can be distinguished. The appearance of these states depending on important model parameters is then systematically investigated. Furthermore, it is shown by which bond property the ability of cells to stably roll in a large range of applied flow rates is increased. Finally, the model is applied to another biological process, the transport of spherical cargo particles by molecular motors. In analogy to the so far described systems molecular motors can be considered as bonds that are able to actively move. In this part of the thesis the mean distance the cargo particles are transported is determined.
The separation of natural and anthropogenically caused climatic changes is an important task of contemporary climate research. For this purpose, a detailed knowledge of the natural variability of the climate during warm stages is a necessary prerequisite. Beside model simulations and historical documents, this knowledge is mostly derived from analyses of so-called climatic proxy data like tree rings or sediment as well as ice cores. In order to be able to appropriately interpret such sources of palaeoclimatic information, suitable approaches of statistical modelling as well as methods of time series analysis are necessary, which are applicable to short, noisy, and non-stationary uni- and multivariate data sets. Correlations between different climatic proxy data within one or more climatological archives contain significant information about the climatic change on longer time scales. Based on an appropriate statistical decomposition of such multivariate time series, one may estimate dimensions in terms of the number of significant, linear independent components of the considered data set. In the presented work, a corresponding approach is introduced, critically discussed, and extended with respect to the analysis of palaeoclimatic time series. Temporal variations of the resulting measures allow to derive information about climatic changes. For an example of trace element abundances and grain-size distributions obtained near the Cape Roberts (Eastern Antarctica), it is shown that the variability of the dimensions of the investigated data sets clearly correlates with the Oligocene/Miocene transition about 24 million years before present as well as regional deglaciation events. Grain-size distributions in sediments give information about the predominance of different transportation as well as deposition mechanisms. Finite mixture models may be used to approximate the corresponding distribution functions appropriately. In order to give a complete description of the statistical uncertainty of the parameter estimates in such models, the concept of asymptotic uncertainty distributions is introduced. The relationship with the mutual component overlap as well as with the information missing due to grouping and truncation of the measured data is discussed for a particular geological example. An analysis of a sequence of grain-size distributions obtained in Lake Baikal reveals that there are certain problems accompanying the application of finite mixture models, which cause an extended climatological interpretation of the results to fail. As an appropriate alternative, a linear principal component analysis is used to decompose the data set into suitable fractions whose temporal variability correlates well with the variations of the average solar insolation on millenial to multi-millenial time scales. The abundance of coarse-grained material is obviously related to the annual snow cover, whereas a significant fraction of fine-grained sediments is likely transported from the Taklamakan desert via dust storms in the spring season.
The primary objective of this work was to develop a laser source for fundamental investigations in the field of laser – materials interactions. In particular it is supposed to facilitate the study of the influence of the temporal energy distribution such as the interaction between adjacent pulses on ablation processes. Therefore, the aim was to design a laser with a highly flexible and easily controllable temporal energy distribution. The laser to meet these demands is an SBS-laser with optional active mode-locking. The nonlinear reflectivity of the SBS-mirror leads to a passive Q-switching and issues ns-pulse bursts with µs spacing. The pulse train parameters such as pulse duration, pulse spacing, pulse energy and number of pulses within a burst can be individually adjusted by tuning the pump parameters and the starting conditions for the laser. Another feature of the SBS-reflection is phase conjugation, which leads to an excellent beam quality thanks to the compensation of phase distortions. Transverse fundamental mode operation and a beam quality better than 1.4 times diffraction limited can be maintained for average output powers of up to 10 W. In addition to the dynamics on a ns-timescale described above, a defined splitting up of each ns-pulse into a train of ps-pulses can be achieved by additional active mode-locking. This twofold temporal focussing of the intensity leads to single pulse energies of up to 2 mJ at pulse durations of approximately 400 ps which corresponds to a pulse peak power of 5 MW. While the pulse duration is of the same order of magnitude as those of other passively Q-switched lasers with simultaneous mode-locking, the pulse energy and pulse peak power exceeds the values of these systems found in the literature by an order of magnitude. To the best of my knowledge the laser presented here is the first implementation of a self-starting mode-locked SBS-laser oscillator. In order to gain a better understanding and control of the transient output of the laser two complementary numerical models were developed. The first is based on laser rate equations which are solved for each laser mode individually while the mode-locking dynamics are calculated from the resultant transient spectrum. The rate equations consider the mean photon densities in the resonator, therefore the propagation of the light inside the resonator is not properly displayed. The second model, in contrast, introduces a spatial resolution of the resonator and hence the propagation inside the resonator can more accurately be considered. Consequently, a mismatch between the loss modulation frequency and the resonator round trip time can be conceived. The model calculates all dynamics in the time domain and therefore the spectral influences such as the Stokes-shift have to be neglected. Both models achieve an excellent reproduction of the ns-dynamics that are generated by the SBS-Q-switch. Separately, each model fails to reproduce all aspects of the ps-dynamics of the SBS-laser in detail. This can be attributed to the complexity of the numerous physical processes involved in this system. But thanks to their complementary nature they provide a very useful tool for investigating the various influences on the dynamics of the mode-locked SBS-laser individually. These aspects can eventually be recomposed to give a complete picture of the mechanisms which govern the output dynamics. Among the aspects under scrutiny were in particular the start resonator quality which determines the starting condition for the SBS-Q-switch, the modulation depth of the AOM and the phonon lifetime as well as the Brillouin-frequency of the SBS-medium. The numerical simulations and the experiments have opened several doors inviting further investigations and promising a potential for further improvement of the experimental results: The results of the simulations in combination with the experimental results which determined the starting conditions for the simulations leave no doubt that the bandwidth generation can primarily be attributed to the SBS-Stokes-shift during the buildup of the Q-switch pulse. For each resonator round trip, bandwidth is generated by shifting a part of the revolving light in frequency. The magnitude of the frequency shift corresponds to the Brillouin-frequency which is a constant of the SBS material and amounts in the case of SF6 to 240 MHz. The modulation of the AOM merely provides an exchange of population between spectrally adjacent modes and therefore diminishes a modulation in the spectrum. By use of a material with a Brillouin-frequency in the GHz range the bandwidth generation can be considerably accelerated thereby shortening the pulse duration. Also, it was demonstrated that yet another nonlinear effect of the SBS can be exploited: If the phonon lifetime is short compared to the resonator round trip time we obtain a modulation in the SBS-reflectivity that supports the modulation of the AOM. The application of an external optical feedback by a conventional mirror turns out to be an alternative to the AOM in synchronizing the longitudinal resonator modes. The interesting feature about this system is that it is ― although highly complex in the physical processes and the temporal output dynamics ― very simple and inexpensive from a technical point of view. No expensive modulators and no control electronics are necessary. Finally, the numerical models constitute a powerful tool for the investigation of emission dynamics of complex laser systems on arbitrary timescales and can also display the spectral evolution of the laser output. In particular it could be demonstrated that differences in the results of the complementary models vanish for systems of lesser complexity.
Uncertainties are pervasive in the Earth System modelling. This is not just due to a lack of knowledge about physical processes but has its seeds in intrinsic, i.e. inevitable and irreducible, uncertainties concerning the process of modelling as well. Therefore, it is indispensable to quantify uncertainty in order to determine, which are robust results under this inherent uncertainty. The central goal of this thesis is to explore how uncertainties map on the properties of interest such as phase space topology and qualitative dynamics of the system. We will address several types of uncertainty and apply methods of dynamical systems theory on a trendsetting field of climate research, i.e. the Indian monsoon. For the systematic analysis concerning the different facets of uncertainty, a box model of the Indian monsoon is investigated, which shows a saddle node bifurcation against those parameters that influence the heat budget of the system and that goes along with a regime shift from a wet to a dry summer monsoon. As some of these parameters are crucially influenced by anthropogenic perturbations, the question is whether the occurrence of this bifurcation is robust against uncertainties in parameters and in the number of considered processes and secondly, whether the bifurcation can be reached under climate change. Results indicate, for example, the robustness of the bifurcation point against all considered parameter uncertainties. The possibility of reaching the critical point under climate change seems rather improbable. A novel method is applied for the analysis of the occurrence and the position of the bifurcation point in the monsoon model against parameter uncertainties. This method combines two standard approaches: a bifurcation analysis with multi-parameter ensemble simulations. As a model-independent and therefore universal procedure, this method allows investigating the uncertainty referring to a bifurcation in a high dimensional parameter space in many other models. With the monsoon model the uncertainty about the external influence of El Niño / Southern Oscillation (ENSO) is determined. There is evidence that ENSO influences the variability of the Indian monsoon, but the underlying physical mechanism is discussed controversially. As a contribution to the debate three different hypotheses are tested of how ENSO and the Indian summer monsoon are linked. In this thesis the coupling through the trade winds is identified as key in linking these two key climate constituents. On the basis of this physical mechanism the observed monsoon rainfall data can be reproduced to a great extent. Moreover, this mechanism can be identified in two general circulation models (GCMs) for the present day situation and for future projections under climate change. Furthermore, uncertainties in the process of coupling models are investigated, where the focus is on a comparison of forced dynamics as opposed to fully coupled dynamics. The former describes a particular type of coupling, where the dynamics from one sub-module is substituted by data. Intrinsic uncertainties and constraints are identified that prevent the consistency of a forced model with its fully coupled counterpart. Qualitative discrepancies between the two modelling approaches are highlighted, which lead to an overestimation of predictability and produce artificial predictability in the forced system. The results suggest that bistability and intermittent predictability, when found in a forced model set-up, should always be cross-validated with alternative coupling designs before being taken for granted. All in this, this thesis contributes to the fundamental issue of dealing with uncertainties the climate modelling community is confronted with. Although some uncertainties allow for including them in the interpretation of the model results, intrinsic uncertainties could be identified, which are inevitable within a certain modelling paradigm and are provoked by the specific modelling approach.
This Thesis was devoted to the study of the coupled system composed by El Niño/Southern Oscillation and the Annual Cycle. More precisely, the work was focused on two main problems: 1. How to separate both oscillations into an affordable model for understanding the behaviour of the whole system. 2. How to model the system in order to achieve a better understanding of the interaction, as well as to predict future states of the system. We focused our efforts in the Sea Surface Temperature equations, considering that atmospheric effects were secondary to the ocean dynamics. The results found may be summarised as follows: 1. Linear methods are not suitable for characterising the dimensionality of the sea surface temperature in the tropical Pacific Ocean. Therefore they do not help to separate the oscillations by themselves. Instead, nonlinear methods of dimensionality reduction are proven to be better in defining a lower limit for the dimensionality of the system as well as in explaining the statistical results in a more physical way [1]. In particular, Isomap, a nonlinear modification of Multidimensional Scaling methods, provides a physically appealing method of decomposing the data, as it substitutes the euclidean distances in the manifold by an approximation of the geodesic distances. We expect that this method could be successfully applied to other oscillatory extended systems and, in particular, to meteorological systems. 2. A three dimensional dynamical system could be modeled, using a backfitting algorithm, for describing the dynamics of the sea surface temperature in the tropical Pacific Ocean. We observed that, although there were few data points available, we could predict future behaviours of the coupled ENSO-Annual Cycle system with an accuracy of less than six months, although the constructed system presented several drawbacks: few data points to input in the backfitting algorithm, untrained model, lack of forcing with external data and simplification using a close system. Anyway, ensemble prediction techniques showed that the prediction skills of the three dimensional time series were as good as those found in much more complex models. This suggests that the climatological system in the tropics is mainly explained by ocean dynamics, while the atmosphere plays a secondary role in the physics of the process. Relevant predictions for short lead times can be made using a low dimensional system, despite its simplicity. The analysis of the SST data suggests that nonlinear interaction between the oscillations is small, and that noise plays a secondary role in the fundamental dynamics of the oscillations [2]. A global view of the work shows a general procedure to face modeling of climatological systems. First, we should find a suitable method of either linear or nonlinear dimensionality reduction. Then, low dimensional time series could be extracted out of the method applied. Finally, a low dimensional model could be found using a backfitting algorithm in order to predict future states of the system.