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- Institut für Physik und Astronomie (1486) (remove)
Three furan-fused BODIPYs were synthesized with perfluorinated methyl, ethyl and n-propyl groups on the meso-carbon. They were obtained with high yields by reacting the furan-fused 2-carboxylpyrrole in corresponding perfluorinated acid and anhydride. With the increase in perfluorinated alkyl chain length, the molecular packing in the single crystal is influenced, showing increasing stacking distance and decreasing slope angle. All the BODIPYs were characterized as intense absorbers in near infrared region in solid state, peaking at similar to 800 nm with absorption coefficient of over 280 000 cm(-1). Facilitated by high thermal stability, the furan-fused BODIPYs were employed in vacuum-deposited organic solar cells as electron donors. All devices exhibit PCE over 6.0% with the EQE maximum reaching 70% at similar to 790 nm. The chemical modification of the BODIPY donors have certain influence on the active layer morphology, and the highest PCE of 6.4% was obtained with a notably high jsc of 13.6 mA cm(-2). Sensitive EQE and electroluminance studies indicated that the energy losses generated by the formation of a charge transfer state and the radiative recombination at the donor-acceptor interface were comparable in the range of 0.14-0.19 V, while non-radiative recombination energy loss of 0.38 V was the main energy loss route resulting in the moderate V-oc of 0.76 V.
Border effect corrections for diagonal line based recurrence quantification analysis measures
(2019)
Recurrence Quantification Analysis (RQA) defines a number of quantifiers, which base upon diagonal line structures in the recurrence plot (RP). Due to the finite size of an RP, these lines can be cut by the borders of the RP and, thus, bias the length distribution of diagonal lines and, consequently, the line based RQA measures. In this letter we investigate the impact of the mentioned border effects and of the thickening of diagonal lines in an RP (caused by tangential motion) on the estimation of the diagonal line length distribution, quantified by its entropy. Although a relation to the Lyapunov spectrum is theoretically expected, the mentioned entropy yields contradictory results in many studies. Here we summarize correction schemes for both, the border effects and the tangential motion and systematically compare them to methods from the literature. We show that these corrections lead to the expected behavior of the diagonal line length entropy, in particular meaning zero values in case of a regular motion and positive values for chaotic motion. Moreover, we test these methods under noisy conditions, in order to supply practical tools for applied statistical research.
In globally coupled ensembles of identical oscillators so-called chimera states can be observed. The chimera state is a symmetry-broken regime, where a subset of oscillators forms a cluster, a synchronized population, while the rest of the system remains a collection of nonsynchronized, scattered units. We describe here a blinking chimera regime in an ensemble of seven globally coupled rotators (Kuramoto oscillators with inertia). It is characterized by a death-birth process, where a long-term stable cluster of four oscillators suddenly dissolves and is very quickly reborn with a new reshuffled configuration. We identify three different kinds of rare blinking events and give a quantitative characterization by applying stability analysis to the long-lived chaotic state and to the short-lived regular regimes that arise when the cluster dissolves.
The first detections of black hole-neutron star mergers (GW200105 and GW200115) by the LIGO-Virgo-Kagra Collaboration mark a significant scientific breakthrough. The physical interpretation of pre- and postmerger signals requires careful cross-examination between observational and theoretical modelling results. Here we present the first set of black hole-neutron star simulations that were obtained with the numerical-relativity code BAM. Our initial data are constructed using the public LORENE spectral library, which employs an excision of the black hole interior. BAM, in contrast, uses the moving-puncture gauge for the evolution. Therefore, we need to "stuff" the black hole interior with smooth initial data to evolve the binary system in time. This procedure introduces constraint violations such that the constraint damping properties of the evolution system are essential to increase the accuracy of the simulation and in particular to reduce spurious center-of-mass drifts. Within BAM we evolve the Z4c equations and we compare our gravitational-wave results with those of the SXS collaboration and results obtained with the SACRA code. While we find generally good agreement with the reference solutions and phase differences less than or similar to 0.5 rad at the moment of merger, the absence of a clean convergence order in our simulations does not allow for a proper error quantification. We finally present a set of different initial conditions to explore how the merger of black hole neutron star systems depends on the involved masses, spins, and equations of state.
Bifurcations in rotating spherical shell convection under the influence of differential rotation
(2021)
The bifurcations of thermal convection in a rotating spherical shell heated from the inner sphere and driven by the buoyancy of a central gravity field are studied numerically. This model of spherical Rayleigh-Benard convection describes large-scale convection in planets and in the outer zones of celestial bodies. In this work, the influence of an additionally imposed differential rotation of the inner sphere with respect to the outer one on the heat transfer and, more generally, on the whole bifurcation structure is investigated. In addition to numerical simulations, path-following techniques are applied in order to compute both stable and unstable solution branches. The dynamics and the heat transfer are essentially determined by a global bifurcation, which we have identified as a homoclinic bifurcation that consists of a collision of a stable modulated rotating with an unstable rotating wave.
We report on bifurcation studies for the incompressible Navier-Stokes equations in two space dimensions with periodic boundary conditions and an external forcing of the Kolmogorov type. Fourier representations of velocity and pressure have been used to approximate the original partial differential equations by a finite-dimensional system of ordinary differential equations, which then has been studied by means of bifurcation-analysis techniques. A special route into chaos observed for increasing Reynolds number or strength of the imposed forcing is described. It includes several steady states, traveling waves, modulated traveling waves, periodic and torus solutions, as well as a period-doubling cascade for a torus solution. Lyapunov exponents and Kaplan-Yorke dimensions have been calculated to characterize the chaotic branch. While studying the dynamics of the system in Fourier space, we also have transformed solutions to real space and examined the relation between the different bifurcations in Fourier space and toplogical changes of the streamline portrait. In particular, the time-dependent solutions, such as, e.g., traveling waves, torus, and chaotic solutions, have been characterized by the associated fluid-particle motion (Lagrangian dynamics).
We have studied the bifurcation structure of the incompressible two-dimensional Navier-Stokes equations with a special external forcing driving an array of 8×8 counterrotating vortices. The study has been motivated by recent experiments with thin layers of electrolytes showing, among other things, the formation of large-scale spatial patterns. As the strength of the forcing or the Reynolds number is raised the original stationary vortex array becomes unstable and a complex sequence of bifurcations is observed. The bifurcations lead to several periodic branches, torus and chaotic solutions, and other stationary solutions. Most remarkable is the appearance of solutions characterized by structures on spatial scales large compared to the scale of the forcing. We also characterize the different dynamic regimes by means of tracers injected into the fluid. Stretching rates and Hausdorff dimensions of convected line elements are calculated to quantify the mixing process. It turns out that for time-periodic velocity fields the mixing can be very effective.
Three-dimensional bouyancy-driven convection in a horizontal fluid layer with stress-free boundary conditions at the top and bottom and periodic boundary conditions in the horizontal directions is investigated by means of numerical simulation and bifurcation-analysis techniques. The aspect ratio is fixed to a value of 2√2 and the Prandtl number to a value of 6.8. Two-dimensional convection rolls are found to be stable up to a Rayleigh number of 17 950, where a Hopf bifurcation leads to traveling waves. These are stable up to a Rayleigh number of 30 000, where a secondary Hopf bifurcation generates modulated traveling waves. We pay particular attention to the symmetries of the solutions and symmetry breaking by the bifurcations.
We report on bifurcation studies for the incompressible magnetohydrodynamic equations in three space dimensions with periodic boundary conditions and a temporally constant external forcing. Fourier reprsentations of velocity, pressure and magnetic field have been used to transform the original partial differential equations into systems of ordinary differential equations (ODE), to which then special numerical methods for the qualitative analysis of systems of ODE have been applied, supplemented by the simulative calculation of solutions for selected initial conditions. In a part of the calculations, in order to reduce the number of modes to be retained, the concept of approximate inertial manifolds has been applied. For varying (incereasing from zero) strength of the imposed forcing, or varying Reynolds number, respectively, time-asymptotic states, notably stable stationary solutions, have been traced. A primary non-magnetic steady state loses, in a Hopf bifurcation, stability to a periodic state with a non-vanishing magnetic field, showing the appearance of a generic dynamo effect. From now on the magnetic field is present for all values of the forcing. The Hopf bifurcation is followed by furhter, symmetry-breaking, bifurcations, leading finally to chaos. We pay particular attention to kinetic and magnetic helicities. The dynamo effect is observed only if the forcing is chosen such that a mean kinetic helicity is generated; otherwise the magnetic field diffuses away, and the time-asymptotic states are non-magnetic, in accordance with traditional kinematic dynamo theory.
A numerical bifurcation analysis of the electrically driven plane sheet pinch is presented. The electrical conductivity varies across the sheet such as to allow instability of the quiescent basic state at some critical Hartmann number. The most unstable perturbation is the two-dimensional tearing mode. Restricting the whole problem to two spatial dimensions, this mode is followed up to a time-asymptotic steady state, which proves to be sensitive to three-dimensional perturbations even close to the point where the primary instability sets in. A comprehensive three-dimensional stability analysis of the two-dimensional steady tearing-mode state is performed by varying parameters of the sheet pinch. The instability with respect to three-dimensional perturbations is suppressed by a sufficiently strong magnetic field in the invariant direction of the equilibrium. For a special choice of the system parameters, the unstably perturbed state is followed up in its nonlinear evolution and is found to approach a three-dimensional steady state.
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.
We examine renewal processes with power-law waiting time distributions (WTDs) and non-zero drift via computing analytically and by computer simulations their ensemble and time averaged spreading characteristics. All possible values of the scaling exponent alpha are considered for the WTD psi(t) similar to 1/t(1+alpha). We treat continuous-time random walks (CTRWs) with 0 < alpha < 1 for which the mean waiting time diverges, and investigate the behaviour of the process for both ordinary and equilibrium CTRWs for 1 < alpha < 2 and alpha > 2. We demonstrate that in the presence of a drift CTRWs with alpha < 1 are ageing and non-ergodic in the sense of the non-equivalence of their ensemble and time averaged displacement characteristics in the limit of lag times much shorter than the trajectory length. In the sense of the equivalence of ensemble and time averages, CTRW processes with 1 < alpha < 2 are ergodic for the equilibrium and non-ergodic for the ordinary situation. Lastly, CTRW renewal processes with alpha > 2-both for the equilibrium and ordinary situation-are always ergodic. For the situations 1 < alpha < 2 and alpha > 2 the variance of the diffusion process, however, depends on the initial ensemble. For biased CTRWs with alpha > 1 we also investigate the behaviour of the ergodicity breaking parameter. In addition, we demonstrate that for biased CTRWs the Einstein relation is valid on the level of the ensemble and time averaged displacements, in the entire range of the WTD exponent alpha.
Bestimmung von Ozonabbauraten über der Arktis und Antarktis mittels Ozonsonden- und Satellitendaten
(2005)
Diese Arbeit beschäftigt sich mit der chemischen Ozonzerstörung im arktischen und antarktischen stratosphärischen Polarwirbel. Diese wird durch Abbauprodukte von anthropogen emittierten Fluorchlorkohlenwasserstoffen und Halonen, Chlor- und Bromradikale, verursacht. Studien in denen der gemessene und modellierte Ozonabbau verglichen wird zeigen, dass die Prozeße bekannt sind, der quantitative Verlauf allerdings nicht vollständig verstanden ist. Die Prozesse, die zur Ozonzerstörung führen sind in beiden Polarwirbeln ähnlich. Allerdings fällt als Konsequenz unterschiedlicher meteorologischer Bedingungen der chemische Ozonabbau im arktischen Polarwirbel weniger drastisch aus als über der Antarktis. Der arktische Polarwirbel ist im Mittel stärker dynamisch gestört als der antarktische und weist eine stärkere Jahr-zu-Jahr Variabilität auf. Das erschwert die Messung des chemischen Ozonabbaus. Zur Trennung des chemischen Ozonabbaus von der dynamischen Umverteilung des Ozons im arktischen Polarwirbel wurde die Matchmethode entwickelt. Bei dieser Methode werden Luftpakete innerhalb des Polarwirbels mehrfach beprobt, um den chemischen Anteil der Ozonänderung zu quantifizieren. Zur Identifizierung von doppelt beprobten Luftpaketen werden Trajektorien aus Windfeldern berechnet. Können zwei Messungen im Rahmen bestimmter Qualitätskriterien durch eine Trajektorie verbunden werden, kann die Ozondifferenz zwischen beiden Sondierungen berechnet und als chemischer Ozonabbau interpretiert werden. Eine solche Koinzidenz wird Match genannt. Der Matchmethode liegt ein statistischer Ansatz zugrunde, so dass eine Vielzahl solcher doppelt beprobter Luftmassen vorliegen muss, um gesicherte Aussagen über die Ozonzerstörung gewinnen zu können. So erhält man die Ozonzerstörung in einem bestimmten Zeitintervall, also Ozonabbauraten. Um die Anzahl an doppelt beprobten Luftpackten zu erhöhen wurde eine aktive Koordinierung der Ozonsondenaufstiege entwickelt. Im Rahmen dieser Arbeit wurden Matchkampagnen während des arktischen Winters 2002/2003 und zum ersten Mal während eines antarktischen Winter (2003) durchgeführt. Aus den gewonnenen Daten wurden Ozonabbauraten in beiden Polarwirbeln bestimmt. Diese Abbauraten dienen zum einen der Evaluierung von Modellen, ermöglichen aber auch den direkten Vergleich von Ozonabbauraten in beiden Polarwirbeln. Der Winter 2002/2003 war zu Beginn durch sehr tiefe Temperaturen in der mittleren und unteren Stratosphäre charakterisiert, so dass die Matchkampagne Ende November gestartet wurde. Ab Januar war der Polarwirbel zeitweise stark dynamisch gestört. Die Kampagne ging bis Mitte März. Für den Höhenbereich von 400 bis 550 K potentieller Temperatur (15-23 km) konnten Ozonabbauraten und der Verlust in der Gesamtsäule berechnet werden. Die Ozonabbauraten wurden in verschiedenen Tests auf ihre Stabilität überprüft. Der antarktische Polarwirbel war vom Beginn des Winters bis Mitte Oktober 2003 sehr kalt und stellte Ende September kurzzeitig den Rekord für die größte bisher aufgetretene Ozonloch-Fläche ein. Es konnten für den Kampagnenzeitraum, Anfang Juni bis Anfang Oktober, Ozonabbauraten im Höhenbereich von 400 bis 550 K potentieller Temperatur ermittelt werden. Der zeitliche Verlauf des Ozonabbaus war dabei auf fast allen Höhenniveaus identisch. Die Zunahme des Sonnenlichtes im Polarwirbel mit der Zeit führt zu einem starken Anwachsen der Ozonabbauraten. Ab Mitte September gingen die Ozonabbauraten auf Null zurück, da bis zu diesem Zeitpunkt das gesamte Ozon zwischen ca. 14 und 21 km zerstört wurde. Im letzten Teil der Arbeit wird ein neuer Algorithmus auf Basis der multivariaten Regression vorgestellt, mit dem Ozonabbauraten aus Ozonprofilen verschiedener Sensoren gleichzeitig berechnet werden können. Dabei können neben der Ozonabbaurate die systematischen Fehler zwischen den einzelnen Sensoren bestimmt werden. Dies wurde exemplarisch am antarktischen Winter 2003 für das 475 K potentielle Temperatur Niveau gezeigt. Neben den Ozonprofilen der Sonden wurden Daten von zwei Satellitenexperimenten verwendet. Die mit der multivariaten Matchtechnik berechneten Ozonabbauraten stimmen gut mit den Ozonabbauraten der Einzelsensor-Matchansätze überein.
Microswimmers, i.e. swimmers of micron size experiencing low Reynolds numbers, have received a great deal of attention in the last years, since many applications are envisioned in medicine and bioremediation. A promising field is the one of magnetic swimmers, since magnetism is biocom-patible and could be used to direct or actuate the swimmers. This thesis studies two examples of magnetic microswimmers from a physics point of view.
The first system to be studied are magnetic cells, which can be magnetic biohybrids (a swimming cell coupled with a magnetic synthetic component) or magnetotactic bacteria (naturally occurring bacteria that produce an intracellular chain of magnetic crystals). A magnetic cell can passively interact with external magnetic fields, which can be used for direction. The aim of the thesis is to understand how magnetic cells couple this magnetic interaction to their swimming strategies, mainly how they combine it with chemotaxis (the ability to sense external gradient of chemical species and to bias their walk on these gradients). In particular, one open question addresses the advantage given by these magnetic interactions for the magnetotactic bacteria in a natural environment, such as porous sediments. In the thesis, a modified Active Brownian Particle model is used to perform simulations and to reproduce experimental data for different systems such as bacteria swimming in the bulk, in a capillary or in confined geometries. I will show that magnetic fields speed up chemotaxis under special conditions, depending on parameters such as their swimming strategy (run-and-tumble or run-and-reverse), aerotactic strategy (axial or polar), and magnetic fields (intensities and orientations), but it can also hinder bacterial chemotaxis depending on the system.
The second example of magnetic microswimmer are rigid magnetic propellers such as helices or random-shaped propellers. These propellers are actuated and directed by an external rotating magnetic field. One open question is how shape and magnetic properties influence the propeller behavior; the goal of this research field is to design the best propeller for a given situation. The aim of the thesis is to propose a simulation method to reproduce the behavior of experimentally-realized propellers and to determine their magnetic properties. The hydrodynamic simulations are based on the use of the mobility matrix. As main result, I propose a method to match the experimental data, while showing that not only shape but also the magnetic properties influence the propellers swimming characteristics.
Estimation of the self-similarity exponent has attracted growing interest in recent decades and became a research subject in various fields and disciplines. Real-world data exhibiting self-similar behavior and/or parametrized by self-similarity exponent (in particular Hurst exponent) have been collected in different fields ranging from finance and human sciencies to hydrologic and traffic networks. Such rich classes of possible applications obligates researchers to investigate qualitatively new methods for estimation of the self-similarity exponent as well as identification of long-range dependencies (or long memory). In this thesis I present the Bayesian estimation of the Hurst exponent. In contrast to previous methods, the Bayesian approach allows the possibility to calculate the point estimator and confidence intervals at the same time, bringing significant advantages in data-analysis as discussed in this thesis. Moreover, it is also applicable to short data and unevenly sampled data, thus broadening the range of systems where the estimation of the Hurst exponent is possible. Taking into account that one of the substantial classes of great interest in modeling is the class of Gaussian self-similar processes, this thesis considers the realizations of the processes of fractional Brownian motion and fractional Gaussian noise. Additionally, applications to real-world data, such as the data of water level of the Nile River and fixational eye movements are also discussed.
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed systems. We here augment recently proposed machine-learning techniques for decoding anomalous-diffusion data to include an uncertainty estimate in addition to the predicted output. To avoid the Black-Box-Problem a Bayesian-Deep-Learning technique named Stochastic-Weight-Averaging-Gaussian is used to train models for both the classification of the diffusionmodel and the regression of the anomalous diffusion exponent of single-particle-trajectories. Evaluating their performance, we find that these models can achieve a wellcalibrated error estimate while maintaining high prediction accuracies. In the analysis of the output uncertainty predictions we relate these to properties of the underlying diffusion models, thus providing insights into the learning process of the machine and the relevance of the output.
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed systems. We here augment recently proposed machine-learning techniques for decoding anomalous-diffusion data to include an uncertainty estimate in addition to the predicted output. To avoid the Black-Box-Problem a Bayesian-Deep-Learning technique named Stochastic-Weight-Averaging-Gaussian is used to train models for both the classification of the diffusion model and the regression of the anomalous diffusion exponent of single-particle-trajectories. Evaluating their performance, we find that these models can achieve a well-calibrated error estimate while maintaining high prediction accuracies. In the analysis of the output uncertainty predictions we relate these to properties of the underlying diffusion models, thus providing insights into the learning process of the machine and the relevance of the output. <br /> Diffusive motions in complex environments such as living biological cells or soft matter systems can be analyzed with single-particle-tracking approaches, where accuracy of output may vary. The authors involve a machine-learning technique for decoding anomalous-diffusion data and provide an uncertainty estimate together with predicted output.
Sprache
Englisch
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed systems. We here augment recently proposed machine-learning techniques for decoding anomalous-diffusion data to include an uncertainty estimate in addition to the predicted output. To avoid the Black-Box-Problem a Bayesian-Deep-Learning technique named Stochastic-Weight-Averaging-Gaussian is used to train models for both the classification of the diffusionmodel and the regression of the anomalous diffusion exponent of single-particle-trajectories. Evaluating their performance, we find that these models can achieve a wellcalibrated error estimate while maintaining high prediction accuracies. In the analysis of the output uncertainty predictions we relate these to properties of the underlying diffusion models, thus providing insights into the learning process of the machine and the relevance of the output.
We employ Bayesian statistics using the nested-sampling algorithm to compare and rank multiple models of ergodic diffusion (including anomalous diffusion) as well as to assess their optimal parameters for in silico-generated and real time-series. We focus on the recently-introduced model of Brownian motion with "diffusing diffusivity'-giving rise to widely-observed non-Gaussian displacement statistics-and its comparison to Brownian and fractional Brownian motion, also for the time-series with some measurement noise. We conduct this model-assessment analysis using Bayesian statistics and the nested-sampling algorithm on the level of individual particle trajectories. We evaluate relative model probabilities and compute best-parameter sets for each diffusion model, comparing the estimated parameters to the true ones. We test the performance of the nested-sampling algorithm and its predictive power both for computer-generated (idealised) trajectories as well as for real single-particle-tracking trajectories. Our approach delivers new important insight into the objective selection of the most suitable stochastic model for a given time-series. We also present first model-ranking results in application to experimental data of tracer diffusion in polymer-based hydrogels.