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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.
Understanding stars, their magnetic activity phenomena and the underlying dynamo action is the foundation for understanding 'life, the universe and everything' - as stellar magnetic fields play a fundamental role for star and planet formation and for the terrestrial atmosphere and climate. Starspots are the fingerprints of magnetic field lines and thereby the most important sign of activity in a star's photosphere. However, they cannot be observed directly, as it is not (yet) possible to spacially resolve the surfaces of even the nearest neighbouring stars. Therefore, an indirect approach called 'Doppler imaging' is applied, which allows to reconstruct the surface spot distribution on rapidly rotating, active stars. In this work, data from 11 years of continuous spectroscopic observations of the active binary star EI Eridani are reduced and analysed. 34 Doppler maps are obtained and the problem of how to parameterise the information content of Doppler maps is discussed. Three approaches for parameter extraction are introduced and applied to all maps: average temperature, separated for several latitude bands; fractional spottedness; and, for the analysis of structural temperature distribution, longitudinal and latitudinal spot-occurrence functions. The resulting values do not show a distinct correlation with the proposed activity cycle as seen from photometric long-term observations, thereby suggesting that the photometric activity cycle is not accompanied by a spot cycle as seen on the Sun. The general morphology of the spot pattern on EI Eri remains persistent for the whole period of 11 years. In addition, a detailed parameter study is performed. Improved orbital parameters suggest that EI Eri might be complemented by a third star in a wide orbit of about 19 years. Preliminary differential rotation measurements are carried out, indicating an anti-solar orientation.
Die Frage nach der Herkunft und der dynamischen Entwicklung langlebiger kosmischer Magnetfelder ist in vielen Details noch unbeantwortet. Es besteht zwar kein Zweifel daran, dass das Magnetfeld der Erde und anderer kosmischer Objekte durch den sogenannten Dynamoeffekt verursacht werden, der genaue Mechanismus als auch die notwendigen Voraussetzungen und Randbedingungen der zugrundeliegenden Strömungen sind aber weitgehend unbekannt. Die für einen Dynamo interessanten Strömungsmuster, die im Inneren von Himmelskörpern durch Konvektion und differentielle Rotation entstehen, sind Konvektionsrollen parallel zur Rotationsachse. Auf einer Strömung mit eben solcher Geometrie, der sogenannten Roberts-Strömung, basieren die in der vorliegenden Arbeit untersuchten Dynamomodelle. Mit Methoden der nichtlinearen Dynamik wird versucht, das Systemverhalten bei Änderung der Systemparamter genauer zu charakterisieren. Die numerischen Untersuchungen beginnen mit einer Analyse der Dynamoaktivität der Roberts-Strömung in Abhängigkeit von den zwei freien Parametern in den Modellgleichungen, der magnetischen Prandtl-Zahl und der Stärke des Energieinputs. Gefunden werden verschiedene Lösungstypen die von einem stationären Magnetfeld über periodische bis zu chaotischen Zuständen reichen. Die yugrundeliegenden Symmetrien werden beschrieben und die Bifurkationen, die zum Wechsel der Lösungstypen führen, charakterisiert. Zusätzlich gibt es Bereiche bei sehr kleinen Prandtl-Zahlen, in denen überhaupt kein Dynamo existiert. Dieses Verhalten wird in der Literatur auch für viele andere numerisch ausgewertete Modelle beschrieben. Im Übergangsbereich zwischen dynamoaktivem und dynamoinaktivem Bereich wird das Auftreten einer sogenannten Blowout-Bifurkation gefunden. Desweiteren beschäftigt sich die Arbeit mit der Frage, inwiefern Helizität, also eine schraubenförmige Bewegung, der Strömung den Dynamoeffekt beeinflusst. Dazu werden ähnliche Strömungstypen verglichen, die sich hauptsächlich in ihrem Helizitätswert unterscheiden. Es wird gefunden, dass ein bestimmter Wert der Helizität nicht unterschritten werden darf, um einen stabilen Roberts-Dynamo zu erhalten.
In this thesis, dynamical structures and manifolds in closed chaotic flows will be investigated. The knowledge about the dynamical structures (and manifolds) of a system is of importance, since they provide us first information about the dynamics of the system - means, with their help we are able to characterize the flow and maybe even to forecast it`s dynamics. The visualization of such structures in closed chaotic flows is a difficult and often long-lasting process. Here, the so-called 'Leaking-method' will be introduced, in examples of simple mathematical maps as the baker- or sine-map, with which we are able to visualize subsets of the manifolds of the system`s chaotic saddle. Comparisons between the visualized manifolds and structures traced out by chemical or biological reactions superimposed on the same flow will be done in the example of a kinematic model of the Gulf Stream. It will be shown that with the help of the leaking method dynamical structures can be also visualized in environmental systems. In the example of a realistic model of the Mediterranean Sea, the leaking method will be extended to the 'exchange-method'. The exchange method allows us to characterize transport between two regions, to visualize transport routes and their exchange sets and to calculate the exchange times. Exchange times and sets will be shown and calculated for a northern and southern region in the western basin of the Mediterranean Sea. Furthermore, mixing properties in the Earth mantle will be characterized and geometrical properties of manifolds in a 3dimensional mathematical model (ABC map) will be investigated.
Recurrence plots, a rather promising tool of data analysis, have been introduced by Eckman et al. in 1987. They visualise recurrences in phase space and give an overview about the system's dynamics. Two features have made the method rather popular. Firstly they are rather simple to compute and secondly they are putatively easy to interpret. However, the straightforward interpretation of recurrence plots for some systems yields rather surprising results. For example indications of low dimensional chaos have been reported for stock marked data, based on recurrence plots. In this work we exploit recurrences or ``naturally occurring analogues'' as they were termed by E. Lorenz, to obtain three key results. One of which is that the most striking structures which are found in recurrence plots are hinged to the correlation entropy and the correlation dimension of the underlying system. Even though an eventual embedding changes the structures in recurrence plots considerably these dynamical invariants can be estimated independently of the special parameters used for the computation. The second key result is that the attractor can be reconstructed from the recurrence plot. This means that it contains all topological information of the system under question in the limit of long time series. The graphical representation of the recurrences can also help to develop new algorithms and exploit specific structures. This feature has helped to obtain the third key result of this study. Based on recurrences to points which have the same ``recurrence structure'', it is possible to generate surrogates of the system which capture all relevant dynamical characteristics, such as entropies, dimensions and characteristic frequencies of the system. These so generated surrogates are shadowed by a trajectory of the system which starts at different initial conditions than the time series in question. They can be used then to test for complex synchronisation.
One of the most striking features of ecological systems is their ability to undergo sudden outbreaks in the population numbers of one or a small number of species. The similarity of outbreak characteristics, which is exhibited in totally different and unrelated (ecological) systems naturally leads to the question whether there are universal mechanisms underlying outbreak dynamics in Ecology. It will be shown into two case studies (dynamics of phytoplankton blooms under variable nutrients supply and spread of epidemics in networks of cities) that one explanation for the regular recurrence of outbreaks stems from the interaction of the natural systems with periodical variations of their environment. Natural aquatic systems like lakes offer very good examples for the annual recurrence of outbreaks in Ecology. The idea whether chaos is responsible for the irregular heights of outbreaks is central in the domain of ecological modeling. This question is investigated in the context of phytoplankton blooms. The dynamics of epidemics in networks of cities is a problem which offers many ecological and theoretical aspects. The coupling between the cities is introduced through their sizes and gives rise to a weighted network which topology is generated from the distribution of the city sizes. We examine the dynamics in this network and classified the different possible regimes. It could be shown that a single epidemiological model can be reduced to a one-dimensional map. We analyze in this context the dynamics in networks of weighted maps. The coupling is a saturation function which possess a parameter which can be interpreted as an effective temperature for the network. This parameter allows to vary continously the network topology from global coupling to hierarchical network. We perform bifurcation analysis of the global dynamics and succeed to construct an effective theory explaining very well the behavior of the system.
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.
Eine Nutzung der optischen Anisotropie dünner Schichten ist vor allem für die Displaytechnologie, die optische Datenspeicherung und für optische Sicherheitselemente von hoher Bedeutung. Diese Doktorarbeit befasst sich mit theoretischen und experimentellen Untersuchung von dreidimensionaler Anisotropie und dabei insbesondere mit der Untersuchung von lichtinduzierter dreidimensionaler Anisotropie in organischen dünnen Polymer-Schichten. Die gewonnenen Erkentnisse und entwickelten Methoden können wertvolle Beiträge für Optimierungsprozesse, wie bei der Kompensation der Blickwinkelabhängigkeit von Flüssigkristall-Displays, liefern. Die neue Methode der Immersions-Transmissions-Ellipsometrie (ITE) zur Untersuchung von dünneren Schichten wurde im Rahmen dieser Dissertation entwickelt. Diese Methode gestattet es, in Kombination mit konventioneller Reflexions- und Transmissionsellipsometrie, die absoluten dreidimensionalen Brechungsindices einer biaxialen Schicht zu bestimmen. Erstmals gelang es damit, das dreidimensionale Brechungsindexellipsoid von transparenten, dünneren (150 nm) Filmen hochgenau (drei Stellen hinter dem Komma) zu bestimmen. Die ITE-Methode hat demzufolge das Potential, auch bei noch dünneren Schichten mit Gewinn eingesetzt werden zu können. Die lichtinduzierte Generierung von dreidimensionaler Anisotropie wurde in dünnen Schichten von azobenzenhaltigen und zimtsäurehaltigen, amorphen und flüssig-kristallinen Homo- und Copolymeren untersucht. Erstmals wurden quantitative Untersuchungen zur Änderung von lichtinduzierten, dreidimensionalen Anisotropien in dünnen Schichten von azobenzenhaltigen und zimtsäurehaltigen Polymeren bei Tempern oberhalb der Glastemperatur durchgeführt. Bei vielen der untersuchten Polymere war die dreidimensionale Ordnung nach dem Bestrahlen mit polarisiertem Licht und anschließendem Tempern oberhalb der Glastemperatur scheinbar von der Schichtdicke abhängig. Die Ursache liegt wohl in der, mit der neuentwickelten ITE-Methode detektierten, planaren Ausgangsorientierung der aufgeschleuderten dünneren Schichten. Um Verkippungs-Gradienten in dickeren Polymerschichten in ihrem Verlauf zu bestimmen, wurde eine spezielle Methode unter Benutzung der Wellenleitermoden-Spektroskopie entwickelt. Quantenchemisch bestimmte, maximal induzierbare Doppelbrechungen in flüssig-kristallinen Polymeren wurden mit den experimentell gefundenen Ordnungen verglichen.
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”.
My thesis is concerned with several new noise-induced phenomena in excitable neural models, especially those with FitzHugh-Nagumo dynamics. In these effects the fluctuations intrinsically present in any complex neural network play a constructive role and improve functionality. I report the occurrence of Vibrational Resonance in excitable systems. Both in an excitable electronic circuit and in the FitzHugh-Nagumo model, I show that an optimal amplitude of high-frequency driving enhances the response of an excitable system to a low-frequency signal. Additionally, the influence of additive noise and the interplay between Stochastic and Vibrational Resonance is analyzed. Further, I study systems which combine both oscillatory and excitable properties, and hence intrinsically possess two internal frequencies. I show that in such a system the effect of Stochastic Resonance can be amplified by an additional high-frequency signal which is in resonance with the oscillatory frequency. This amplification needs much lower noise intensities than for conventional Stochastic Resonance in excitable systems. I study frequency selectivity in noise-induced subthreshold signal processing in a system with many noise-supported stochastic attractors. I show that the response of the coupled elements at different noise levels can be significantly enhanced or reduced by forcing some elements into resonance with these new frequencies which correspond to appropriate phase-relations. A noise-induced phase transition to excitability is reported in oscillatory media with FitzHugh-Nagumo dynamics. This transition takes place via noise-induced stabilization of a deterministically unstable fixed point of the local dynamics, while the overall phase-space structure of the system is maintained. The joint action of coupling and noise leads to a different type of phase transition and results in a stabilization of the system. The resulting noise-induced regime is shown to display properties characteristic of excitable media, such as Stochastic Resonance and wave propagation. This effect thus allows the transmission of signals through an otherwise globally oscillating medium. In particular, these theoretical findings suggest a possible mechanism for suppressing undesirable global oscillations in neural networks (which are usually characteristic of abnormal medical conditions such as Parkinson′s disease or epilepsy), using the action of noise to restore excitability, which is the normal state of neuronal ensembles.