530 Physik
Refine
Has Fulltext
- yes (12)
Year of publication
- 2009 (12) (remove)
Document Type
- Doctoral Thesis (7)
- Master's Thesis (3)
- Postprint (2)
Language
- English (12)
Is part of the Bibliography
- yes (12)
Keywords
- Anderson (1)
- Arctic (1)
- Arktis (1)
- Augenbewegungen (1)
- Ausbreitung (1)
- CALIPSO (1)
- Casimir effect (1)
- Casimir-Effekt (1)
- Casimir-Polder Wechselwirkung (1)
- Casimir-Polder interaction (1)
Institute
Special p-forms are forms which have components fµ1…µp equal to +1, -1 or 0 in some orthonormal basis. A p-form ϕ ∈ pRd is called democratic if the set of nonzero components {ϕμ1...μp} is symmetric under the transitive action of a subgroup of O(d,Z) on the indices {1, . . . , d}. Knowledge of these symmetry groups allows us to define mappings of special democratic p-forms in d dimensions to special democratic P-forms in D dimensions for successively higher P = p and D = d. In particular, we display a remarkable nested structure of special forms including a U(3)-invariant 2-form in six dimensions, a G2-invariant 3-form in seven dimensions, a Spin(7)-invariant 4-form in eight dimensions and a special democratic 6-form O in ten dimensions. The latter has the remarkable property that its contraction with one of five distinct bivectors, yields, in the orthogonal eight dimensions, the Spin(7)-invariant 4-form. We discuss various properties of this ten dimensional form.
The recent discovery of an intricate and nontrivial interaction topology among the elements of a wide range of natural systems has altered the manner we understand complexity. For example, the axonal fibres transmitting electrical information between cortical regions form a network which is neither regular nor completely random. Their structure seems to follow functional principles to balance between segregation (functional specialisation) and integration. Cortical regions are clustered into modules specialised in processing different kinds of information, e.g. visual or auditory. However, in order to generate a global perception of the real world, the brain needs to integrate the distinct types of information. Where this integration happens, nobody knows. We have performed an extensive and detailed graph theoretical analysis of the cortico-cortical organisation in the brain of cats, trying to relate the individual and collective topological properties of the cortical areas to their function. We conclude that the cortex possesses a very rich communication structure, composed of a mixture of parallel and serial processing paths capable of accommodating dynamical processes with a wide variety of time scales. The communication paths between the sensory systems are not random, but largely mediated by a small set of areas. Far from acting as mere transmitters of information, these central areas are densely connected to each other, strongly indicating their functional role as integrators of the multisensory information. In the quest of uncovering the structure-function relationship of cortical networks, the peculiarities of this network have led us to continuously reconsider the stablished graph measures. For example, a normalised formalism to identify the “functional roles” of vertices in networks with community structure is proposed. The tools developed for this purpose open the door to novel community detection techniques which may also characterise the overlap between modules. The concept of integration has been revisited and adapted to the necessities of the network under study. Additionally, analytical and numerical methods have been introduced to facilitate understanding of the complicated statistical interrelations between the distinct network measures. These methods are helpful to construct new significance tests which may help to discriminate the relevant properties of real networks from side-effects of the evolutionary-growth processes.
Complex network theory provides an elegant and powerful framework to statistically investigate the topology of local and long range dynamical interrelationships, i.e., teleconnections, in the climate system. Employing a refined methodology relying on linear and nonlinear measures of time series analysis, the intricate correlation structure within a multivariate climatological data set is cast into network form. Within this graph theoretical framework, vertices are identified with grid points taken from the data set representing a region on the the Earth's surface, and edges correspond to strong statistical interrelationships between the dynamics on pairs of grid points. The resulting climate networks are neither perfectly regular nor completely random, but display the intriguing and nontrivial characteristics of complexity commonly found in real world networks such as the internet, citation and acquaintance networks, food webs and cortical networks in the mammalian brain. Among other interesting properties, climate networks exhibit the "small-world" effect and possess a broad degree distribution with dominating super-nodes as well as a pronounced community structure. We have performed an extensive and detailed graph theoretical analysis of climate networks on the global topological scale focussing on the flow and centrality measure betweenness which is locally defined at each vertex, but includes global topological information by relying on the distribution of shortest paths between all pairs of vertices in the network. The betweenness centrality field reveals a rich internal structure in complex climate networks constructed from reanalysis and atmosphere-ocean coupled general circulation model (AOGCM) surface air temperature data. Our novel approach uncovers an elaborately woven meta-network of highly localized channels of strong dynamical information flow, that we relate to global surface ocean currents and dub the backbone of the climate network in analogy to the homonymous data highways of the internet. This finding points to a major role of the oceanic surface circulation in coupling and stabilizing the global temperature field in the long term mean (140 years for the model run and 60 years for reanalysis data). Carefully comparing the backbone structures detected in climate networks constructed using linear Pearson correlation and nonlinear mutual information, we argue that the high sensitivity of betweenness with respect to small changes in network structure may allow to detect the footprints of strongly nonlinear physical interactions in the climate system. The results presented in this thesis are thoroughly founded and substantiated using a hierarchy of statistical significance tests on the level of time series and networks, i.e., by tests based on time series surrogates as well as network surrogates. This is particularly relevant when working with real world data. Specifically, we developed new types of network surrogates to include the additional constraints imposed by the spatial embedding of vertices in a climate network. Our methodology is of potential interest for a broad audience within the physics community and various applied fields, because it is universal in the sense of being valid for any spatially extended dynamical system. It can help to understand the localized flow of dynamical information in any such system by combining multivariate time series analysis, a complex network approach and the information flow measure betweenness centrality. Possible fields of application include fluid dynamics (turbulence), plasma physics and biological physics (population models, neural networks, cell models). Furthermore, the climate network approach is equally relevant for experimental data as well as model simulations and hence introduces a novel perspective on model evaluation and data driven model building. Our work is timely in the context of the current debate on climate change within the scientific community, since it allows to assess from a new perspective the regional vulnerability and stability of the climate system while relying on global and not only on regional knowledge. The methodology developed in this thesis hence has the potential to substantially contribute to the understanding of the local effect of extreme events and tipping points in the earth system within a holistic global framework.
Many cellular processes require decision making mechanisms, which must act reliably even in the unavoidable presence of substantial amounts of noise. However, the multistable genetic switches that underlie most decision-making processes are dominated by fluctuations that can induce random jumps between alternative cellular states. Here we show, via theoretical modeling of a population of noise-driven bistable genetic switches, that reliable timing of decision-making processes can be accomplished for large enough population sizes, as long as cells are globally coupled by chemical means. In the light of these results, we conjecture that cell proliferation, in the presence of cell-cell communication, could provide a mechanism for reliable decision making in the presence of noise, by triggering cellular transitions only when the whole cell population reaches a certain size. In other words , the summation performed by the cell population would average out the noise and reduce its detrimental impact.
Due to the unique environmental conditions and different feedback mechanisms, the Arctic region is especially sensitive to climate changes. The influence of clouds on the radiation budget is substantial, but difficult to quantify and parameterize in models. In the framework of the PhD, elastic backscatter and depolarization lidar observations of Arctic clouds were performed during the international Arctic Study of Tropospheric Aerosol, Clouds and Radiation (ASTAR) from Svalbard in March and April 2007. Clouds were probed above the inaccessible Arctic Ocean with a combination of airborne instruments: The Airborne Mobile Aerosol Lidar (AMALi) of the Alfred Wegener Institute for Polar and Marine Research provided information on the vertical and horizontal extent of clouds along the flight track, optical properties (backscatter coefficient), and cloud thermodynamic phase. From the data obtained by the spectral albedometer (University of Mainz), the cloud phase and cloud optical thickness was deduced. Furthermore, in situ observations with the Polar Nephelometer, Cloud Particle Imager and Forward Scattering Spectrometer Probe (Laboratoire de Météorologie Physique, France) provided information on the microphysical properties, cloud particle size and shape, concentration, extinction, liquid and ice water content. In the thesis, a data set of four flights is analyzed and interpreted. The lidar observations served to detect atmospheric structures of interest, which were then probed by in situ technique. With this method, an optically subvisible ice cloud was characterized by the ensemble of instruments (10 April 2007). Radiative transfer simulations based on the lidar, radiation and in situ measurements allowed the calculation of the cloud forcing, amounting to -0.4 W m-2. This slight surface cooling is negligible on a local scale. However, thin Arctic clouds have been reported more frequently in winter time, when the clouds' effect on longwave radiation (a surface warming of 2.8 W m-2) is not balanced by the reduced shortwave radiation (surface cooling). Boundary layer mixed-phase clouds were analyzed for two days (8 and 9 April 2007). The typical structure consisting of a predominantly liquid water layer on cloud top and ice crystals below were confirmed by all instruments. The lidar observations were compared to European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological analyses. A change of air masses along the flight track was evidenced in the airborne data by a small completely glaciated cloud part within the mixed-phase cloud system. This indicates that the updraft necessary for the formation of new cloud droplets at cloud top is disturbed by the mixing processes. The measurements served to quantify the shortcomings of the ECMWF model to describe mixed-phase clouds. As the partitioning of cloud condensate into liquid and ice water is done by a diagnostic equation based on temperature, the cloud structures consisting of a liquid cloud top layer and ice below could not be reproduced correctly. A small amount of liquid water was calculated for the lowest (and warmest) part of the cloud only. Further, the liquid water content was underestimated by an order of magnitude compared to in situ observations. The airborne lidar observations of 9 April 2007 were compared to space borne lidar data on board of the satellite Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The systems agreed about the increase of cloud top height along the same flight track. However, during the time delay of 1 h between the lidar measurements, advection and cloud processing took place, and a detailed comparison of small-scale cloud structures was not possible. A double layer cloud at an altitude of 4 km was observed with lidar at the West coast in the direct vicinity of Svalbard (14 April 2007). The cloud system consisted of two geometrically thin liquid cloud layers (each 150 m thick) with ice below each layer. While the upper one was possibly formed by orographic lifting under the influence of westerly winds, or by the vertical wind shear shown by ECMWF analyses, the lower one might be the result of evaporating precipitation out of the upper layer. The existence of ice precipitation between the two layers supports the hypothesis that humidity released from evaporating precipitation was cooled and consequently condensed as it experienced the radiative cooling from the upper layer. In summary, a unique data set characterizing tropospheric Arctic clouds was collected with lidar, in situ and radiation instruments. The joint evaluation with meteorological analyses allowed a detailed insight in cloud properties, cloud evolution processes and radiative effects.
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.
We study buckling instabilities of filaments in biological systems. Filaments in a cell are the building blocks of the cytoskeleton. They are responsible for the mechanical stability of cells and play an important role in intracellular transport by molecular motors, which transport cargo such as organelles along cytoskeletal filaments. Filaments of the cytoskeleton are semiflexible polymers, i.e., their bending energy is comparable to the thermal energy such that they can be viewed as elastic rods on the nanometer scale, which exhibit pronounced thermal fluctuations. Like macroscopic elastic rods, filaments can undergo a mechanical buckling instability under a compressive load. In the first part of the thesis, we study how this buckling instability is affected by the pronounced thermal fluctuations of the filaments. In cells, compressive loads on filaments can be generated by molecular motors. This happens, for example, during cell division in the mitotic spindle. In the second part of the thesis, we investigate how the stochastic nature of such motor-generated forces influences the buckling behavior of filaments. In chapter 2 we review briefly the buckling instability problem of rods on the macroscopic scale and introduce an analytical model for buckling of filaments or elastic rods in two spatial dimensions in the presence of thermal fluctuations. We present an analytical treatment of the buckling instability in the presence of thermal fluctuations based on a renormalization-like procedure in terms of the non-linear sigma model where we integrate out short-wavelength fluctuations in order to obtain an effective theory for the mode of the longest wavelength governing the buckling instability. We calculate the resulting shift of the critical force by fluctuation effects and find that, in two spatial dimensions, thermal fluctuations increase this force. Furthermore, in the buckled state, thermal fluctuations lead to an increase in the mean projected length of the filament in the force direction. As a function of the contour length, the mean projected length exhibits a cusp at the buckling instability, which becomes rounded by thermal fluctuations. Our main result is the observation that a buckled filament is stretched by thermal fluctuations, i.e., its mean projected length in the direction of the applied force increases by thermal fluctuations. Our analytical results are confirmed by Monte Carlo simulations for buckling of semiflexible filaments in two spatial dimensions. We also perform Monte Carlo simulations in higher spatial dimensions and show that the increase in projected length by thermal fluctuations is less pronounced than in two dimensions and strongly depends on the choice of the boundary conditions. In the second part of this work, we present a model for buckling of semiflexible filaments under the action of molecular motors. We investigate a system in which a group of motors moves along a clamped filament carrying a second filament as a cargo. The cargo-filament is pushed against the wall and eventually buckles. The force-generating motors can stochastically unbind and rebind to the filament during the buckling process. We formulate a stochastic model of this system and calculate the mean first passage time for the unbinding of all linking motors which corresponds to the transition back to the unbuckled state of the cargo filament in a mean-field model. Our results show that for sufficiently short microtubules the movement of kinesin-I-motors is affected by the load force generated by the cargo filament. Our predictions could be tested in future experiments.
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.
This thesis investigates the Casimir effect between plates made of normal and superconducting metals over a broad range of temperatures, as well as the Casimir-Polder interaction of an atom to such a surface. Numerical and asymptotical calculations have been the main tools in order to do so. The optical properties of the surfaces are described by dielectric functions or optical conductivities, which are reviewed for common models and have been analyzed with special weight on distributional properties and causality. The calculation of the Casimir energy between two normally conducting plates (cavity) is reviewed and previous work on the contribution to the Casimir energy due to the surface plasmons, present in all metallic cavities, has been generalized to finite temperatures for the first time. In the field of superconductivity, a new analytical continuation of the BCS conductivity to to purely imaginary frequencies has been obtained both inside and outside the extremely dirty limit of vanishing mean free path. The Casimir free energy calculated from this description was shown to coincide well with the values obtained from the two fluid model of superconductivity in certain regimes of the material parameters. The Casimir entropy in a superconducting cavity fulfills the third law of thermodynamics and features a characteristic discontinuity at the phase transition temperature. These effects were equally encountered in the Casimir-Polder interaction of an atom with a superconducting wall. The magnetic dipole coupling of an atom to a metal was shown to be highly sensible to dissipation and especially to the surface currents. This leads to a strong quenching of the magnetic Casimir-Polder energy at finite temperature. Violations of the third law of thermodynamics are encountered in special models, similar to phenomena in the Casimir-effect between two plates, that are debated controversely. None of these effects occurs in the analog electric dipole interaction. The results of this work suggest to reestablish the well-known plasma model as the low temperature limit of a superconductor as in London theory rather than use it for the description of normal metals. Superconductors offer the opportunity to control the dissipation of surface currents to a great extent. This could be used to access experimentally the low frequency optical response of metals, which is strongly connected to the thermal Casimir-effect. Here, differently from corresponding microwave experiments, energy and momentum are independent quantities. A measurement of the total Casimir-Polder interaction of atoms with superconductors seems to be in reach in today’s microchip-based atom-traps and the contribution due to magnetic coupling might be accessed by spectroscopic techniques
In this thesis, the properties of nonlinear disordered one dimensional lattices is investigated. Part I gives an introduction to the phenomenon of Anderson Localization, the Discrete Nonlinear Schroedinger Equation and its properties as well as the generalization of this model by introducing the nonlinear index α. In Part II, the spreading behavior of initially localized states in large, disordered chains due to nonlinearity is studied. Therefore, different methods to measure localization are discussed and the structural entropy as a measure for the peak structure of probability distributions is introduced. Finally, the spreading exponent for several nonlinear indices is determined numerically and compared with analytical approximations. Part III deals with the thermalization in short disordered chains. First, the term thermalization and its application to the system in use is explained. Then, results of numerical simulations on this topic are presented where the focus lies especially on the energy dependence of the thermalization properties. A connection with so-called breathers is drawn.