530 Physik
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Institute
- Institut für Physik und Astronomie (296)
- Extern (25)
- Potsdam Institute for Climate Impact Research (PIK) e. V. (4)
- Institut für Biochemie und Biologie (3)
- Institut für Geowissenschaften (3)
- Institut für Mathematik (2)
- Mathematisch-Naturwissenschaftliche Fakultät (2)
- Institut für Chemie (1)
- Institut für Umweltwissenschaften und Geographie (1)
- Interdisziplinäres Zentrum für Dynamik komplexer Systeme (1)
Shape change is a fundamental process occurring in biological tissues during embryonic development and regeneration of tissues and organs. This process is regulated by cells that are constrained within a complex environment of biochemical and physical cues. The spatial constraint due to geometry has a determining role on tissue mechanics and the spatial distribution of force patterns that, in turn, influences the organization of the tissue structure. An understanding of the underlying principles of tissue organization may have wide consequences for the understanding of healing processes and the development of organs and, as such, is of fundamental interest for the tissue engineering community.
This thesis aims to further our understanding of how the collective behaviour of cells is influenced by the 3D geometry of the environment. Previous research studying the role of geometry on tissue growth has mainly focused either on flat surfaces or on substrates where at least one of the principal curvatures is zero. In the present work, tissue growth from MC3T3-E1 pre-osteoblasts was investigated on surfaces of controlled mean curvature.
One key aspect of this thesis was the development of substrates of controlled mean curvature and their visualization in 3D. It was demonstrated that substrates of controlled mean curvature suitable for cell culture can be fabricated using liquid polymers and surface tension effects.
Using these substrates, it was shown that the mean surface curvature has a strong impact on the rate of tissue growth and on the organization of the tissue structure. It was thereby not only demonstrated that the amount of tissue produced (i.e. growth rates) by the cells depends on the mean curvature of the substrate but also that the tissue surface behaves like a viscous fluid with an equilibrium shape governed by the Laplace-Young-law. It was observed that more tissue was formed on highly concave surfaces compared to flat or convex surfaces.
Motivated by these observations, an analytical model was developed, where the rate of tissue growth is a function of the mean curvature, which could successfully describe the growth kinetics. This model was also able to reproduce the growth kinetics of previous experiments where tissues have been cultured in straight-sided prismatic pores.
A second part of this thesis focuses on the tissue structure, which influences the mechanical properties of the mature bone tissue. Since the extracellular matrix is produced by the cells, the cell orientation has a strong impact on the direction of the tissue fibres. In addition, it was recently shown that some cell types exhibit collective alignment similar to liquid crystals.
Based on this observation, a computational model of self-propelled active particles was developed to explore in an abstract manner how the collective behaviour of cells is influenced by 3D curvature. It was demonstrated that the 3D curvature has a strong impact on the self-organization of active particles and gives, therefore, first insights into the principles of self-organization of cells on curved surfaces.
Dark matter, DM, has not yet been directly observed, but it has a very solid theoretical basis. There are observations that provide indirect evidence, like galactic rotation curves that show that the galaxies are rotating too fast to keep their constituent parts, and galaxy clusters that bends the light coming from behind-lying galaxies more than expected with respect to the mass that can be calculated from what can be visibly seen. These observations, among many others, can be explained with theories that include DM. The missing piece is to detect something that can exclusively be explained by DM. Direct observation in a particle accelerator is one way and indirect detection using telescopes is another. This thesis is focused on the latter method.
The Very Energetic Radiation Imaging Telescope Array System, V ERITAS, is a telescope array that detects Cherenkov radiation. Theory predicts that DM particles annihilate into, e.g., a γγ pair and create a distinctive energy spectrum when detected by such telescopes, e.i., a monoenergetic line at the same energy as the particle mass. This so called ”smoking-gun” signature is sought with a sliding window line search within the sub-range ∼ 0.3 − 10 TeV of the VERITAS energy range, ∼ 0.01 − 30 TeV.
Standard analysis within the VERITAS collaboration uses Hillas analysis and look-up tables, acquired by analysing particle simulations, to calculate the energy of the particle causing the Cherenkov shower. In this thesis, an improved analysis method has been used. Modelling each shower as a 3Dgaussian should increase the energy recreation quality. Five dwarf spheroidal galaxies were chosen as targets with a total of ∼ 224 hours of data. The targets were analysed individually and stacked. Particle simulations were based on two simulation packages, CARE and GrISU.
Improvements have been made to the energy resolution and bias correction, up to a few percent each, in comparison to standard analysis. Nevertheless, no line with a relevant significance has been detected. The most promising line is at an energy of ∼ 422 GeV with an upper limit cross section of 8.10 · 10^−24 cm^3 s^−1 and a significance of ∼ 2.73 σ, before trials correction and ∼ 1.56 σ after. Upper limit cross sections have also been calculated for the γγ annihilation process and four other outcomes. The limits are in line with current limits using other methods, from ∼ 8.56 · 10^−26 − 6.61 · 10^−23 cm^3s^−1. Future larger telescope arrays, like the upcoming Cherenkov Telescope Array, CTA, will provide better results with the help of this analysis method.
Bacteria respond to changing environmental conditions by switching the global pattern of expressed genes. In response to specific environmental stresses the cell activates several stress-specific molecules such as sigma factors. They reversibly bind the RNA polymerase to form the so-called holoenzyme and direct it towards the appropriate stress response genes. In exponentially growing E. coli cells, the majority of the transcriptional activity is carried out by the housekeeping sigma factor, while stress responses are often under the control of alternative sigma factors. Different sigma factors compete for binding to a limited pool of RNA polymerase (RNAP) core enzymes, providing a mechanism for cross talk between genes or gene classes via the sharing of expression machinery. To quantitatively analyze the contribution of sigma factor competition to global changes in gene expression, we develop a thermodynamic model that describes binding between sigma factors and core RNAP at equilibrium, transcription, non-specific binding to DNA and the modulation of the availability of the molecular components.
Association of housekeeping sigma factor to RNAP is generally favored by its abundance and higher binding affinity to the core. In order to promote transcription by alternative sigma subunits, the bacterial cell modulates the transcriptional efficiency in a reversible manner through several strategies such as anti-sigma factors, 6S RNA and generally any kind of transcriptional regulators (e.g. activators or inhibitors). By shifting the outcome of sigma factor competition for the core, these modulators bias the transcriptional program of the cell. The model is validated by comparison with in vitro competition experiments, with which excellent agreement is found. We observe that transcription is affected via the modulation of the concentrations of the different types of holoenzymes, so saturated promoters are only weakly affected by sigma factor competition. However, in case of overlapping promoters or promoters recognized by two types of sigma factors, we find that even saturated promoters are strongly affected.
Active transcription effectively lowers the affinity between the sigma factor driving it and the core RNAP, resulting in complex cross talk effects and raising the question of how their in vitro measure is relevant in the cell. We also estimate that sigma factor competition is not strongly affected by non-specific binding of core RNAPs, sigma factors, and holoenzymes to DNA. Finally, we analyze the role of increased core RNAP availability upon the shut-down of ribosomal RNA transcription during stringent response. We find that passive up-regulation of alternative sigma-dependent transcription is not only possible, but also displays hypersensitivity based on the sigma factor competition. Our theoretical analysis thus provides support for a significant role of passive control during that global switch of the gene expression program and gives new insights into RNAP partitioning in the cell.
Additive Manufacturing (AM) in terms of laser powder-bed fusion (L-PBF) offers new prospects regarding the design of parts and enables therefore the production of lattice structures. These lattice structures shall be implemented in various industrial applications (e.g. gas turbines) for reasons of material savings or cooling channels. However, internal defects, residual stress, and structural deviations from the nominal geometry are unavoidable.
In this work, the structural integrity of lattice structures manufactured by means of L-PBF was non-destructively investigated on a multiscale approach.
A workflow for quantitative 3D powder analysis in terms of particle size, particle shape, particle porosity, inter-particle distance and packing density was established. Synchrotron computed tomography (CT) was used to correlate the packing density with the particle size and particle shape. It was also observed that at least about 50% of the powder porosity was released during production of the struts.
Struts are the component of lattice structures and were investigated by means of laboratory CT. The focus was on the influence of the build angle on part porosity and surface quality. The surface topography analysis was advanced by the quantitative characterisation of re-entrant surface features. This characterisation was compared with conventional surface parameters showing their complementary information, but also the need for AM specific surface parameters.
The mechanical behaviour of the lattice structure was investigated with in-situ CT under compression and successive digital volume correlation (DVC). The deformation was found to be knot-dominated, and therefore the lattice folds unit cell layer wise.
The residual stress was determined experimentally for the first time in such lattice structures. Neutron diffraction was used for the non-destructive 3D stress investigation. The principal stress directions and values were determined in dependence of the number of measured directions. While a significant uni-axial stress state was found in the strut, a more hydrostatic stress state was found in the knot. In both cases, strut and knot, seven directions were at least needed to find reliable principal stress directions.
This thesis is focused on the electronic, spin-dependent and dynamical properties of thin magnetic systems. Photoemission-related techniques are combined with synchrotron radiation to study the spin-dependent properties of these systems in the energy and time domains. In the first part of this thesis, the strength of electron correlation effects in the spin-dependent electronic structure of ferromagnetic bcc Fe(110) and hcp Co(0001) is investigated by means of spin- and angle-resolved photoemission spectroscopy. The experimental results are compared to theoretical calculations within the three-body scattering approximation and within the dynamical mean-field theory, together with one-step model calculations of the photoemission process. From this comparison it is demonstrated that the present state of the art many-body calculations, although improving the description of correlation effects in Fe and Co, give too small mass renormalizations and scattering rates thus demanding more refined many-body theories including nonlocal fluctuations. In the second part, it is shown in detail monitoring by photoelectron spectroscopy how graphene can be grown by chemical vapour deposition on the transition-metal surfaces Ni(111) and Co(0001) and intercalated by a monoatomic layer of Au. For both systems, a linear E(k) dispersion of massless Dirac fermions is observed in the graphene pi-band in the vicinity of the Fermi energy. Spin-resolved photoemission from the graphene pi-band shows that the ferromagnetic polarization of graphene/Ni(111) and graphene/Co(0001) is negligible and that graphene on Ni(111) is after intercalation of Au spin-orbit split by the Rashba effect. In the last part, a time-resolved x-ray magnetic circular dichroic-photoelectron emission microscopy study of a permalloy platelet comprising three cross-tie domain walls is presented. It is shown how a fast picosecond magnetic response in the precessional motion of the magnetization can be induced by means of a laser-excited photoswitch. From a comparision to micromagnetic calculations it is demonstrated that the relatively high precessional frequency observed in the experiments is directly linked to the nature of the vortex/antivortex dynamics and its response to the magnetic perturbation. This includes the time-dependent reversal of the vortex core polarization, a process which is beyond the limit of detection in the present experiments.
A task-based parallel elliptic solver for numerical relativity with discontinuous Galerkin methods
(2022)
Elliptic partial differential equations are ubiquitous in physics. In numerical relativity---the study of computational solutions to the Einstein field equations of general relativity---elliptic equations govern the initial data that seed every simulation of merging black holes and neutron stars. In the quest to produce detailed numerical simulations of these most cataclysmic astrophysical events in our Universe, numerical relativists resort to the vast computing power offered by current and future supercomputers. To leverage these computational resources, numerical codes for the time evolution of general-relativistic initial value problems are being developed with a renewed focus on parallelization and computational efficiency. Their capability to solve elliptic problems for accurate initial data must keep pace with the increasing detail of the simulations, but elliptic problems are traditionally hard to parallelize effectively.
In this thesis, I develop new numerical methods to solve elliptic partial differential equations on computing clusters, with a focus on initial data for orbiting black holes and neutron stars. I develop a discontinuous Galerkin scheme for a wide range of elliptic equations, and a stack of task-based parallel algorithms for their iterative solution. The resulting multigrid-Schwarz preconditioned Newton-Krylov elliptic solver proves capable of parallelizing over 200 million degrees of freedom to at least a few thousand cores, and already solves initial data for a black hole binary about ten times faster than the numerical relativity code SpEC. I also demonstrate the applicability of the new elliptic solver across physical disciplines, simulating the thermal noise in thin mirror coatings of interferometric gravitational-wave detectors to unprecedented accuracy. The elliptic solver is implemented in the new open-source SpECTRE numerical relativity code, and set up to support simulations of astrophysical scenarios for the emerging era of gravitational-wave and multimessenger astronomy.
The unceasing impact of intense sunlight on earth constitutes a continuous source of energy fueling countless natural processes. On a molecular level, the energy contained in the electromagnetic radiation is transferred through photochemical processes into chemical or thermal energy. In the course of such processes, photo-excitations promote molecules into thermally inaccessible excited states. This induces adaptations of their molecular geometry according to the properties of the excited state. Decay processes towards energetically lower lying states in transient molecular geometries result in the formation of excited state relaxation pathways. The photo-chemical relaxation mechanisms depend on the studied system itself, the interactions with its chemical environment and the character of the involved states. This thesis focuses on systems in which photo-induced deprotonation processes occur at specific atomic sites.
To detect these excited-state proton dynamics at the affected atoms, a local probe of molecular electronic structure is required. Therefore, site-selective and orbital-specific K-edge soft X-ray spectroscopy techniques are used here to detect photo-induced proton dynamics in gaseous and liquid sample environments. The protonation of nitrogen (N) sites in organic molecules and the oxygen (O) atom in the water molecule are probed locally through transitions between 1s orbitals and the p-derived molecular valence electronic structure. The used techniques are X-ray absorption spectroscopy (XAS) and resonant inelastic X-ray scattering (RIXS). Both yield access to the unoccupied local valence electronic structure, whereas the latter additionally probes occupied states.
We apply these probes in optical pump X-ray probe experiments to investigate valence excited-state proton transfer capabilities of aqueous 2-thiopyridone. A characteristic shift of N K-edge X-ray absorption resonances as well as a distinct X-ray emission line are established by us as spectral fingerprints of N deprotonation in the system. We utilize them to identify photo-induced N deprotonation of 2-thiopyridone on femtosecond timescales, in optical pump N K-edge RIXS probe measurements. We further establish excited state proton transfer mechanisms on picosecond and nanosecond timescales along the dominant relaxation pathways of 2-thiopyridone using transient N K-edge XAS.
Despite being an excellent probe mechanism for valence excited-state proton dynamics, the K-edge core-excitation itself also disturbs the electronic structure at specific sites of a molecule. The rapid reaction of protons to 1s photo-excitations can yield directional structural distortions within the femtosecond core-excited state lifetime. These directional proton dynamics can change the energetic separation of eigenstates of the system and alter probabilities for radiative decay between them. Both effects yield spectral signatures of the dynamics in RIXS spectra.
Using these signatures of RIXS transitions into electronically excited states, we investigate proton dynamics induced by N K-edge excitation in the amino-acid histidine. The minor core-excited state dynamics of histidine in basic and neutral chemical environments allow us to establish XAS and RIXS spectral signatures of different N protonation states at its imidazole N sites. Based on these signatures, we identify an excitation-site-independent N-H dissociation for N K-edge excitation under acidic conditions.
Such directional structural deformations, induced by core-excitations, also make proton dynamics in electronic ground states accessible through RIXS transitions into vibrationally excited states. In that context, we interpret high resolution RIXS spectra of the water molecule for three O K-edge resonances based on quantum-chemical wave packet propagation simulations. We show that highly oriented ground state vibrational modes of coupled nuclear motion can be populated through RIXS processes by preparation of core-excited state nuclear wave packets with the same directionality. Based on that, we analytically derive the possibility to extract one-dimensional directional cuts through potential energy surfaces of molecular systems from the corresponding RIXS spectra. We further verify this concept through the extraction of the gas-phase water ground state potential along three coordinates from experimental data in comparison to quantum-chemical simulations of the potential energy surface.
This thesis also contains contributions to instrumentation development for investigations of photo-induced molecular dynamics at high brilliance X-ray light sources. We characterize the setup used for the transient valence-excited state XAS measurements of 2-thiopyridone. Therein, a sub-micrometer thin liquid sample environment is established employing in-vacuum flat-jet technology, which enables a transmission experimental geometry. In combination with a MHz-laser system, we achieve a high detection sensitivity for photo-induced X-ray absorption changes. Additionally, we present conceptual improvements for temporal X-ray optical cross-correlation techniques based on transient changes of multilayer optical properties, which are crucial for the realization of femtosecond time-resolved studies at synchrotrons and free-electron lasers.
This Thesis puts its focus on the physics of neutron stars and its description with methods of numerical relativity. In the first step, a new numerical framework the Whisky2D code will be developed, which solves the relativistic equations of hydrodynamics in axisymmetry. Therefore we consider an improved formulation of the conserved form of these equations. The second part will use the new code to investigate the critical behaviour of two colliding neutron stars. Considering the analogy to phase transitions in statistical physics, we will investigate the evolution of the entropy of the neutron stars during the whole process. A better understanding of the evolution of thermodynamical quantities, like the entropy in critical process, should provide deeper understanding of thermodynamics in relativity. More specifically, we have written the Whisky2D code, which solves the general-relativistic hydrodynamics equations in a flux-conservative form and in cylindrical coordinates. This of course brings in 1/r singular terms, where r is the radial cylindrical coordinate, which must be dealt with appropriately. In the above-referenced works, the flux operator is expanded and the 1/r terms, not containing derivatives, are moved to the right-hand-side of the equation (the source term), so that the left hand side assumes a form identical to the one of the three-dimensional (3D) Cartesian formulation. We call this the standard formulation. Another possibility is not to split the flux operator and to redefine the conserved variables, via a multiplication by r. We call this the new formulation. The new equations are solved with the same methods as in the Cartesian case. From a mathematical point of view, one would not expect differences between the two ways of writing the differential operator, but, of course, a difference is present at the numerical level. Our tests show that the new formulation yields results with a global truncation error which is one or more orders of magnitude smaller than those of alternative and commonly used formulations. The second part of the Thesis uses the new code for investigations of critical phenomena in general relativity. In particular, we consider the head-on-collision of two neutron stars in a region of the parameter space where two final states a new stable neutron star or a black hole, lay close to each other. In 1993, Choptuik considered one-parameter families of solutions, S[P], of the Einstein-Klein-Gordon equations for a massless scalar field in spherical symmetry, such that for every P > P⋆, S[P] contains a black hole and for every P < P⋆, S[P] is a solution not containing singularities. He studied numerically the behavior of S[P] as P → P⋆ and found that the critical solution, S[P⋆], is universal, in the sense that it is approached by all nearly-critical solutions regardless of the particular family of initial data considered. All these phenomena have the common property that, as P approaches P⋆, S[P] approaches a universal solution S[P⋆] and that all the physical quantities of S[P] depend only on |P − P⋆|. The first study of critical phenomena concerning the head-on collision of NSs was carried out by Jin and Suen in 2007. In particular, they considered a series of families of equal-mass NSs, modeled with an ideal-gas EOS, boosted towards each other and varied the mass of the stars, their separation, velocity and the polytropic index in the EOS. In this way they could observe a critical phenomenon of type I near the threshold of black-hole formation, with the putative solution being a nonlinearly oscillating star. In a successive work, they performed similar simulations but considering the head-on collision of Gaussian distributions of matter. Also in this case they found the appearance of type-I critical behaviour, but also performed a perturbative analysis of the initial distributions of matter and of the merged object. Because of the considerable difference found in the eigenfrequencies in the two cases, they concluded that the critical solution does not represent a system near equilibrium and in particular not a perturbed Tolmann-Oppenheimer-Volkoff (TOV) solution. In this Thesis we study the dynamics of the head-on collision of two equal-mass NSs using a setup which is as similar as possible to the one considered above. While we confirm that the merged object exhibits a type-I critical behaviour, we also argue against the conclusion that the critical solution cannot be described in terms of equilibrium solution. Indeed, we show that, in analogy with what is found in, the critical solution is effectively a perturbed unstable solution of the TOV equations. Our analysis also considers fine-structure of the scaling relation of type-I critical phenomena and we show that it exhibits oscillations in a similar way to the one studied in the context of scalar-field critical collapse.
Gravitational-wave (GW) astrophysics is a field in full blossom. Since the landmark detection of GWs from a binary black hole on September 14th 2015, fifty-two compact-object binaries have been reported by the LIGO-Virgo collaboration. Such events carry astrophysical and cosmological information ranging from an understanding of how black holes and neutron stars are formed, what neutron stars are composed of, how the Universe expands, and allow testing general relativity in the highly-dynamical strong-field regime. It is the goal of GW astrophysics to extract such information as accurately as possible. Yet, this is only possible if the tools and technology used to detect and analyze GWs are advanced enough. A key aspect of GW searches are waveform models, which encapsulate our best predictions for the gravitational radiation under a certain set of parameters, and that need to be cross-correlated with data to extract GW signals. Waveforms must be very accurate to avoid missing important physics in the data, which might be the key to answer the fundamental questions of GW astrophysics. The continuous improvements of the current LIGO-Virgo detectors, the development of next-generation ground-based detectors such as the Einstein Telescope or the Cosmic Explorer, as well as the development of the Laser Interferometer Space Antenna (LISA), demand accurate waveform models. While available models are enough to capture the low spins, comparable-mass binaries routinely detected in LIGO-Virgo searches, those for sources from both current and next-generation ground-based and spaceborne detectors must be accurate enough to detect binaries with large spins and asymmetry in the masses. Moreover, the thousands of sources that we expect to detect with future detectors demand accurate waveforms to mitigate biases in the estimation of signals’ parameters due to the presence of a foreground of many sources that overlap in the frequency band. This is recognized as one of the biggest challenges for the analysis of future-detectors’ data, since biases might hinder the extraction of important astrophysical and cosmological information from future detectors’ data. In the first part of this thesis, we discuss how to improve waveform models for binaries with high spins and asymmetry in the masses. In the second, we present the first generic metrics that have been proposed to predict biases in the presence of a foreground of many overlapping signals in GW data.
For the first task, we will focus on several classes of analytical techniques. Current models for LIGO and Virgo studies are based on the post-Newtonian (PN, weak-field, small velocities) approximation that is most natural for the bound orbits that are routinely detected in GW searches. However, two other approximations have risen in prominence, the post-Minkowskian (PM, weak- field only) approximation natural for unbound (scattering) orbits and the small-mass-ratio (SMR) approximation typical of binaries in which the mass of one body is much bigger than the other. These are most appropriate to binaries with high asymmetry in the masses that challenge current waveform models. Moreover, they allow one to “cover” regions of the parameter space of coalescing binaries, thereby improving the interpolation (and faithfulness) of waveform models. The analytical approximations to the relativistic two-body problem can synergically be included within the effective-one-body (EOB) formalism, in which the two-body information from each approximation can be recast into an effective problem of a mass orbiting a deformed Schwarzschild (or Kerr) black hole. The hope is that the resultant models can cover both the low-spin comparable-mass binaries that are routinely detected, and the ones that challenge current models. The first part of this thesis is dedicated to a study about how to best incorporate information from the PN, PM, SMR and EOB approaches in a synergistic way. We also discuss how accurate the resulting waveforms are, as compared against numerical-relativity (NR) simulations. We begin by comparing PM models, whether alone or recast in the EOB framework, against PN models and NR simulations. We will show that PM information has the potential to improve currently-employed models for LIGO and Virgo, especially if recast within the EOB formalism. This is very important, as the PM approximation comes with a host of new computational techniques from particle physics to exploit. Then, we show how a combination of PM and SMR approximations can be employed to access previously-unknown PN orders, deriving the third subleading PN dynamics for spin-orbit and (aligned) spin1-spin2 couplings. Such new results can then be included in the EOB models currently used in GW searches and parameter estimation studies, thereby improving them when the binaries have high spins. Finally, we build an EOB model for quasi-circular nonspinning binaries based on the SMR approximation (rather than the PN one as usually done). We show how this is done in detail without incurring in the divergences that had affected previous attempts, and compare the resultant model against NR simulations. We find that the SMR approximation is an excellent approximation for all (quasi-circular nonspinning) binaries, including both the equal-mass binaries that are routinely detected in GW searches and the ones with highly asymmetric masses. In particular, the SMR-based models compare much better than the PN models, suggesting that SMR-informed EOB models might be the key to model binaries in the future. In the second task of this thesis, we work within the linear-signal ap- proximation and describe generic metrics to predict inference biases on the parameters of a GW source of interest in the presence of confusion noise from unfitted foregrounds and from residuals of other signals that have been incorrectly fitted out. We illustrate the formalism with simple (yet realistic) LISA sources, and demonstrate its validity against Monte-Carlo simulations. The metrics we describe pave the way for more realistic studies to quantify the biases with future ground-based and spaceborne detectors.
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 aim of this work is the study of silica Arrayed Waveguide Gratings (AWGs) in the context of applications in astronomy. The specific focus lies on the investigation of the feasibility and technology limits of customized silica AWG devices for high resolution near-infrared spectroscopy. In a series of theoretical and experimental studies, AWG devices of varying geometry, foot-print and spectral resolution are constructed, simulated using a combination of a numerical beam propagation method and Fraunhofer diffraction and fabricated devices are characterized with respect to transmission efficiency, spectral resolution and polarization sensitivity. The impact of effective index non-uniformities on the performance of high-resolution AWG devices is studied numerically. Characterization results of fabricated devices are used to extrapolate the technology limits of the silica platform. The important issues of waveguide birefringence and defocus aberration are discussed theoretically and addressed experimentally by selection of an appropriate aberration-minimizing anastigmatic AWG layout structure. The drawbacks of the anastigmatic AWG geometry are discussed theoretically. From the results of the experimental studies, it is concluded that fabrication-related phase errors and waveguide birefringence are the primary limiting factors for the growth of AWG spectral resolution. It is shown that, without post-processing, the spectral resolving power is phase-error-limited to R < 40, 000 and, in the case of unpolarized light, birefringence-limited to R < 30, 000 in the AWG devices presented in this work. Necessary measures, such as special waveguide geometries and post-fabrication phase error correction are proposed for future designs. The elimination of defocus aberration using an anastigmatic AWG geometry is successfully demonstrated in experiment. Finally, a novel, non-planar dispersive in-fibre waveguide structure is proposed, discussed and studied theoretically.
Advancing charge selective contacts for efficient monolithic perovskite-silicon tandem solar cells
(2019)
Hybrid organic-inorganic perovskites are one of the most promising material classes for photovoltaic energy conversion. In solar cells, the perovskite absorber is sandwiched between n- and p-type contact layers which selectively transport electrons and holes to the cell’s cathode and anode, respectively. This thesis aims to advance contact layers in perovskite solar cells and unravel the impact of interface and contact properties on the device performance. Further, the contact materials are applied in monolithic perovskite-silicon heterojunction (SHJ) tandem solar cells, which can overcome the single junction efficiency limits and attract increasing attention. Therefore, all contact layers must be highly transparent to foster light harvesting in the tandem solar cell design. Besides, the SHJ device restricts processing temperatures for the selective contacts to below 200°C.
A comparative study of various electron selective contact materials, all processed below 180°C, in n-i-p type perovskite solar cells highlights that selective contacts and their interfaces to the absorber govern the overall device performance. Combining fullerenes and metal-oxides in a TiO2/PC60BM (phenyl-C60-butyric acid methyl ester) double-layer contact allows to merge good charge extraction with minimized interface recombination. The layer sequence thereby achieved high stabilized solar cell performances up to 18.0% and negligible current-voltage hysteresis, an otherwise pronounced phenomenon in this device design. Double-layer structures are therefore emphasized as a general concept to establish efficient and highly selective contacts.
Based on this success, the concept to combine desired properties of different materials is transferred to the p-type contact. Here, a mixture of the small molecule Spiro-OMeTAD [2,2’,7,7’-tetrakis(N,N-di-p-methoxyphenylamine)-9,9’-spirobifluoren] and the doped polymer PEDOT [poly(3,4-ethylenedioxythiophene)] is presented as a novel hole selective contact. PEDOT thereby remarkably suppresses charge recombination at the perovskite surface, allowing an increase of quasi-Fermi level splitting in the absorber. Further, the addition of Spiro-OMeTAD into the PEDOT layer is shown to enhance charge extraction at the interface and allow high efficiencies up to 16.8%.
Finally, the knowledge on contact properties is applied to monolithic perovskite-SHJ tandem solar cells. The main goal is to optimize the top contact stack of doped Spiro-OMeTAD/molybdenum oxide(MoOx)/ITO towards higher transparency by two different routes. First, fine-tuning of the ITO deposition to mitigate chemical reduction of MoOx and increase the transmittance of MoOx/ITO stacks by 25%. Second, replacing Spiro-OMeTAD with the alternative hole transport materials PEDOT/Spiro-OMeTAD mixtures, CuSCN or PTAA [poly(triaryl amine)]. Experimental results determine layer thickness constrains and validate optical simulations, which subsequently allow to realistically estimate the respective tandem device performances. As a result, PTAA represents the most promising replacement for Spiro-OMeTAD, with a projected increase of the optimum tandem device efficiency for the herein used architecture by 2.9% relative to 26.5% absolute. The results also reveal general guidelines for further performance gains of the technology.
The atmosphere over the Arctic Ocean is strongly influenced by the distribution of sea ice and open water. Leads in the sea ice produce strong convective fluxes of sensible and latent heat and release aerosol particles into the atmosphere. They increase the occurrence of clouds and modify the structure and characteristics of the atmospheric boundary layer (ABL) and thereby influence the Arctic climate.
In the course of this study aircraft measurements were performed over the western Arctic Ocean as part of the campaign PAMARCMIP 2012 of the Alfred Wegener Institute for Polar and Marine Research (AWI). Backscatter from aerosols and clouds within the lower troposphere and the ABL were measured with the nadir pointing Airborne Mobile Aerosol Lidar (AMALi) and dropsondes were launched to obtain profiles of meteorological variables. Furthermore, in situ measurements of aerosol properties, meteorological variables and turbulence were part of the campaign. The measurements covered a broad range of atmospheric and sea ice conditions.
In this thesis, properties of the ABL over Arctic sea ice with a focus on the influence of open leads are studied based on the data from the PAMARCMIP campaign. The height of the ABL is determined by different methods that are applied to dropsonde and AMALi backscatter profiles. ABL heights are compared for different flights representing different conditions of the atmosphere and of sea ice and open water influence. The different criteria for ABL height that are applied show large variation in terms of agreement among each other, depending on the characteristics of the ABL and its history. It is shown that ABL height determination from lidar backscatter by methods commonly used under mid-latitude conditions is applicable to the Arctic ABL only under certain conditions. Aerosol or clouds within the ABL are needed as a tracer for ABL height detection from backscatter. Hence an aerosol source close to the surface is necessary, that is typically found under the present influence of open water and therefore convective conditions. However it is not always possible to distinguish residual layers from the actual ABL. Stable boundary layers are generally difficult to detect.
To illustrate the complexity of the Arctic ABL and processes therein, four case studies are analyzed each of which represents a snapshot of the interplay between atmosphere and underlying sea ice or water surface. Influences of leads and open water on the aerosol and clouds within the ABL are identified and discussed. Leads are observed to cause the formation of fog and cloud layers within the ABL by humidity emission. Furthermore they decrease the stability and increase the height of the ABL and consequently facilitate entrainment of air and aerosol layers from the free troposphere.
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.
In this thesis we provide a construction of the operator framework starting from the functional formulation of group field theory (GFT). We define operator algebras on Hilbert spaces whose expectation values in specific states provide correlation functions of the functional formulation. Our construction allows us to give a direct relation between the ingredients of the functional GFT and its operator formulation in a perturbative regime. Using this construction we provide an example of GFT states that can not be formulated as states in a Fock space and lead to math- ematically inequivalent representations of the operator algebra. We show that such inequivalent representations can be grouped together by their symmetry properties and sometimes break the left translation symmetry of the GFT action. We interpret these groups of inequivalent representations as phases of GFT, similar to the classification of phases that we use in QFT’s on space-time.
Due to advances in science and technology towards smaller and more powerful processing units, the fabrication of micrometer sized machines for different tasks becomes more and more possible. Such micro-robots could revolutionize medical treatment of diseases and shall support to work on other small machines. Nevertheless, scaling down robots and other devices is a challenging task and will probably remain limited in near future. Over the past decade the concept of bio-hybrid systems has proved to be a promising approach in order to advance the further development of micro-robots. Bio-hybrid systems combine biological cells with artificial components, thereby benefiting from the functionality of living biological cells. Cell-driven micro-transport is one of the most prominent applications in the emerging field of these systems. So far, micrometer sized cargo has been successfully transported by means of swimming bacterial cells. The potential of motile adherent cells as transport systems has largely remained unexplored.
This thesis concentrates on the social amoeba Dictyostelium discoideum as a potential candidate for an amoeboid bio-hybrid transport system. The use of this model organism comes with several advantages. Due to the unspecific properties of Dictyostelium adhesion, a wide range of different cargo materials can be used for transport. As amoeboid cells exceed bacterial cells in size by one order of magnitude, also the size of an object carried by a single cell can also be much larger for an amoeba. Finally it is possible to guide the cell-driven transport based on the chemotactic behavior of the amoeba. Since cells undergo a developmentally induced chemotactic aggregation, cargo could be assembled in a self-organized manner into a cluster. It is also possible to impose an external chemical gradient to guide the amoeboid transport system to a desired location.
To establish Dictyostelium discoideum as a possible candidate for bio-hybrid transport systems, this thesis will first investigate the movement of single cells. Secondly, the interaction of cargo and cells will be studied. Eventually, a conceptional proof will be conducted, that the cheomtactic behavior can be exploited either to transport a cargo self-organized or through an external chemical source.
Seasonal forecasts are of great interest in many areas. Knowing the amount of precipitation for the upcoming season in regions of water scarcity would facilitate a better water management. If farmers knew the weather conditions of the upcoming summer at sowing time, they could select those cereal species that are best adapted to these conditions. This would allow farmers to improve the harvest and potentially even reduce the amount of pesticides used. However, the undoubted advantages of seasonal forecasts are often opposed by their high degree of uncertainty. The great challenge of generating seasonal forecasts with lead times of several months mainly originates from the chaotic nature of the earth system. In a chaotic system, even tiny differences in the initial conditions can lead to strong deviations in the system’s state in the long run.
In this dissertation we propose an emergent machine learning approach for seasonal forecasting, called the AnlgModel. The AnlgModel combines the analogue method with myopic feature selection and bootstrapping. To benchmark the abilities of the AnlgModel we apply it to seasonal cyclone activity forecasts in the North Atlantic and Northwest Pacific. The AnlgModel demonstrates competitive hindcast skills with two operational forecasts and even outperforms these for long lead times.
In the second chapter we comprehend the forecasting strategy of the Anlg-Model. We thereby analyse the analogue selection process for the 2017 North Atlantic and the 2018 Northwest Pacific seasonal cyclone activity. The analysis shows that those climate indices which are known to influence the seasonal cyclone activity, such as the Niño 3.4 SST, are correctly represented among the selected analogues. Furthermore the selected analogues reflect large-scale climate patterns that were identified by expert reports as being determinative for these particular seasons.
In the third chapter we analyse the features that are used by the AnlgModel for its predictions. We therefore inspect the feature relevance (FR). The FR patterns learned by the AnlgModel show a high congruence with the predictor regions used by the operational forecasts. However, the AnlgModel also discovered new features, such as the SST anomaly in the Gulf of Guinea during November. This SST pattern exhibits a remarkably high predictive potential for the upcoming Atlantic hurricane activity.
In the final chapter we investigate potential mechanisms, that link two of these regions with high feature relevance to the Atlantic hurricane activity. We mainly focus on ocean surface transport. The ocean surface flow paths are calculated using Lagrangian particle analysis. We demonstrate that the FR patterns in the region of the Canary islands do not correspond with ocean surface transport. It is instead likely that these FR patterns fingerprint a wind transport of latent heat. The second region to be studied is situated in the Gulf of Guinea. Our analysis shows that the FR patterns seen there do fingerprint ocean surface transport. However, our simulations also show that at least one other mechanism is involved in linking the Gulf of Guinea SST anomaly in November to the hurricane activity of the upcoming season.
In this work the AnlgModel does not only demonstrate its outstanding forecast skills but also shows its capabilities as research tool for detecting oceanic and atmospheric mechanisms.
Die vorliegende Arbeit beschäftigt sich mit der Charakterisierung von Seismizität anhand von Erdbebenkatalogen. Es werden neue Verfahren der Datenanalyse entwickelt, die Aufschluss darüber geben sollen, ob der seismischen Dynamik ein stochastischer oder ein deterministischer Prozess zugrunde liegt und was daraus für die Vorhersagbarkeit starker Erdbeben folgt. Es wird gezeigt, dass seismisch aktive Regionen häufig durch nichtlinearen Determinismus gekennzeichent sind. Dies schließt zumindest die Möglichkeit einer Kurzzeitvorhersage ein. Das Auftreten seismischer Ruhe wird häufig als Vorläuferphaenomen für starke Erdbeben gedeutet. Es wird eine neue Methode präsentiert, die eine systematische raumzeitliche Kartierung seismischer Ruhephasen ermöglicht. Die statistische Signifikanz wird mit Hilfe des Konzeptes der Ersatzdaten bestimmt. Als Resultat erhält man deutliche Korrelationen zwischen seismischen Ruheperioden und starken Erdbeben. Gleichwohl ist die Signifikanz dafür nicht hoch genug, um eine Vorhersage im Sinne einer Aussage über den Ort, die Zeit und die Stärke eines zu erwartenden Hauptbebens zu ermöglichen.
In this thesis, we treat the extreme Newman-Penrose components of both the Maxwell field (s=±1) and the linearized gravitational perturbations (or "linearized gravity" for short) (s=±2) in the exterior of a slowly rotating Kerr black hole. Upon different rescalings, we can obtain spin s components which satisfy the separable Teukolsky master equation (TME). For each of these spin s components defined in Kinnersley tetrad, the resulting equations by performing some first-order differential operator on it once and twice (twice only for s=±2), together with the TME, are in the form of an "inhomogeneous spin-weighted wave equation" (ISWWE) with different potentials and constitute a linear spin-weighted wave system. We then prove energy and integrated local energy decay (Morawetz) estimates for this type of ISWWE, and utilize them to achieve both a uniform bound of a positive definite energy and a Morawetz estimate for the regular extreme Newman-Penrose components defined in the regular Hawking-Hartle tetrad.
We also present some brief discussions on mode stability for TME for the case of real frequencies. This says that in a fixed subextremal Kerr spacetime, there is no nontrivial separated mode solutions to TME which are purely ingoing at horizon and purely outgoing at infinity. This yields a representation formula for solutions to inhomogeneous Teukolsky equations, and will play a crucial role in generalizing the above energy and Morawetz estimates results to the full subextremal Kerr case.
The mobile-immobile model (MIM) has been established in geoscience in the context of contaminant transport in groundwater. Here the tracer particles effectively immobilise, e.g., due to diffusion into dead-end pores or sorption. The main idea of the MIM is to split the total particle density into a mobile and an immobile density. Individual tracers switch between the mobile and immobile state following a two-state telegraph process, i.e., the residence times in each state are distributed exponentially. In geoscience the focus lies on the breakthrough curve (BTC), which is the concentration at a fixed location over time. We apply the MIM to biological experiments with a special focus on anomalous scaling regimes of the mean squared displacement (MSD) and non-Gaussian displacement distributions. As an exemplary system, we have analysed the motion of tau proteins, that diffuse freely inside axons of neurons. Their free diffusion thereby corresponds to the mobile state of the MIM. Tau proteins stochastically bind to microtubules, which effectively immobilises the tau proteins until they unbind and continue diffusing. Long immobilisation durations compared to the mobile durations give rise to distinct non-Gaussian Laplace shaped distributions. It is accompanied by a plateau in the MSD for initially mobile tracer particles at relevant intermediate timescales. An equilibrium fraction of initially mobile tracers gives rise to non-Gaussian displacements at intermediate timescales, while the MSD remains linear at all times. In another setting bio molecules diffuse in a biosensor and transiently bind to specific receptors, where advection becomes relevant in the mobile state. The plateau in the MSD observed for the advection-free setting and long immobilisation durations persists also for the case with advection. We find a new clear regime of anomalous diffusion with non-Gaussian distributions and a cubic scaling of the MSD. This regime emerges for initially mobile and for initially immobile tracers. For an equilibrium fraction of initially mobile tracers we observe an intermittent ballistic scaling of the MSD. The long-time effective diffusion coefficient is enhanced by advection, which we physically explain with the variance of mobile durations. Finally, we generalize the MIM to incorporate arbitrary immobilisation time distributions and focus on a Mittag-Leffler immobilisation time distribution with power-law tail ~ t^(-1-mu) with 0<mu<1 and diverging mean immobilisation durations. A fit of our model to the BTC of experimental data from tracer particles in aquifers matches the BTC including the power-law tail. We use the fit parameters for plotting the displacement distributions and the MSD. We find Gaussian normal diffusion at short times and long-time power-law decay of mobile mass accompanied by anomalous diffusion at long times. The long-time diffusion is subdiffusive in the advection-free setting, while it is either subdiffusive for 0<mu<1/2 or superdiffusive for 1/2<mu<1 when advection is present. In the long-time limit we show equivalence of our model to a bi-fractional diffusion equation.
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.
Subject of this work is the study of applications of the Galactic Microlensing effect, where the light of a distant star (source) is bend according to Einstein's theory of gravity by the gravitational field of intervening compact mass objects (lenses), creating multiple (however not resolvable) images of the source. Relative motion of source, observer and lens leads to a variation of deflection/magnification and thus to a time dependant observable brightness change (lightcurve), a so-called microlensing event, lasting weeks to months. The focus lies on the modeling of binary-lens events, which provide a unique tool to fully characterize the lens-source system and to detect extra-solar planets around the lens star. Making use of the ability of genetic algorithms to efficiently explore large and intricate parameter spaces in the quest for the global best solution, a modeling software (Tango) for binary lenses is developed, presented and applied to data sets from the PLANET microlensing campaign. For the event OGLE-2002-BLG-069 the 2nd ever lens mass measurement has been achieved, leading to a scenario, where a G5III Bulge giant at 9.4 kpc is lensed by an M-dwarf binary with total mass of M=0.51 solar masses at distance 2.9 kpc. Furthermore a method is presented to use the absence of planetary lightcurve signatures to constrain the abundance of extra-solar planets.
Corvino, Corvino and Schoen, Chruściel and Delay have shown the existence of a large class of asymptotically flat vacuum initial data for Einstein's field equations which are static or stationary in a neighborhood of space-like infinity, yet quite general in the interior. The proof relies on some abstract, non-constructive arguments which makes it difficult to calculate such data numerically by using similar arguments. A quasilinear elliptic system of equations is presented of which we expect that it can be used to construct vacuum initial data which are asymptotically flat, time-reflection symmetric, and asymptotic to static data up to a prescribed order at space-like infinity. A perturbation argument is used to show the existence of solutions. It is valid when the order at which the solutions approach staticity is restricted to a certain range. Difficulties appear when trying to improve this result to show the existence of solutions that are asymptotically static at higher order. The problems arise from the lack of surjectivity of a certain operator. Some tensor decompositions in asymptotically flat manifolds exhibit some of the difficulties encountered above. The Helmholtz decomposition, which plays a role in the preparation of initial data for the Maxwell equations, is discussed as a model problem. A method to circumvent the difficulties that arise when fast decay rates are required is discussed. This is done in a way that opens the possibility to perform numerical computations. The insights from the analysis of the Helmholtz decomposition are applied to the York decomposition, which is related to that part of the quasilinear system which gives rise to the difficulties. For this decomposition analogous results are obtained. It turns out, however, that in this case the presence of symmetries of the underlying metric leads to certain complications. The question, whether the results obtained so far can be used again to show by a perturbation argument the existence of vacuum initial data which approach static solutions at infinity at any given order, thus remains open. The answer requires further analysis and perhaps new methods.
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.
Atmospheric interactions with land surface in the arctic based on regional climate model solutions
(2014)
The characterization of exoplanets applying high-resolution transmission spectroscopy ini- tiated a new era making it possible to trace atmospheric signature at high altitudes in exoplanet atmospheres and to determine atmospheric properties which enrich our under- standing of the formation and evolution of the solar system. In contrast to what is observed in our solar system, where gaseous planets orbit at wide orbits, Jupiter type exoplanets were detected in foreign stellar systems surrounding their host stars within few days, in close orbits, the so called hot- and ultra-hot Jupiters. The most well studied ones are HD209458b and HD189733b, which are the first exoplanets where absorption is detected in their atmospheres, namely from the alkali line sodium. For hot Jupiters, the resonant alkali lines are the atmospheric species with one of the strongest absorption signatures, due to their large absorption cross-section. However, al- though the alkali lines sodium and potassium were detected in low-resolution observations for various giant exoplanets, potassium was absent in different high-resolution investiga- tions in contrast to sodium. The reason for this is quite puzzling, since both alkalis have very similar physical and chemical properties (e.g. condensation and ionization proper- ties). Obtaining high-resolution transit observations of HD189733b and HD209458b, we were able to detect potassium on HD189733b (Manuscript 1), which was the first high-resolution detection of potassium on an exoplanet. The absence of potassium on HD209458b could be reasoned by depletion processes, such as condensation or photo-ionization or high-altitude clouds. In a further study (Manuscript II), we resolved the potassium line and compared this to a previously detected sodium absorption on this planet. The comparison showed, that the potassium lines are either tracing different altitudes and temperatures compared to the sodium lines, or are depleted so that the planetary Na/K- ratio is way larger than the stellar one. A comparison of the alkali lines with synthetic line profiles showed that the sodium lines were much broader than the potassium lines, probably being induced by winds. To investigate this, the effect of zonal streaming winds on the sodium lines on Jupiter-type planets is investigated in a further study (Manuscript III), showing that such winds can significantly broaden the Na- lines and that high-resolution observations can trace such winds with different properties. Furthermore, investigating the Na-line observations for different exoplanets, I showed that the Na-line broadening follows a trend with cooler planets showing stronger line broadening and so hinting on stronger winds, matching well into theoretical predictions. Each presented manuscript depends on the re- sults published within the previous manuscript, yielding a unitary study of the exoplanet HD189733b. The investigation of the potassium absorption required to account for different effects: The telluric lines removal and the effect of center-to-limb variation (see Manuscript I), the residual Rossiter-Mc-Laughlin effect (see Manuscript II) and the broadening of spectral lines on a translucent atmospheric ring by zonal jet streams (see Manuscript III). This thesis shows that high-resolution transmission spectroscopy is a powerful tool to probe sharp alkali line absorption on giant exoplanet atmospheres and to investigate on the properties and dynamics of hot Jupiter type atmospheres.
In the presence of a solid-liquid or liquid-air interface, bacteria can choose between a planktonic and a sessile lifestyle. Depending on environmental conditions, cells swimming in close proximity to the interface can irreversibly attach to the surface and grow into three-dimensional aggregates where the majority of cells is sessile and embedded in an extracellular polymer matrix (biofilm). We used microfluidic tools and time lapse microscopy to perform experiments with the polarly flagellated soil bacterium Pseudomonas putida (P. putida), a bacterial species that is able to form biofilms. We analyzed individual trajectories of swimming cells, both in the bulk fluid and in close proximity to a glass-liquid interface. Additionally, surface related growth during the early phase of biofilm formation was investigated. In the bulk fluid, P.putida shows a typical bacterial swimming pattern of alternating periods of persistent displacement along a line (runs) and fast reorientation events (turns) and cells swim with an average speed around 24 micrometer per second. We found that the distribution of turning angles is bimodal with a dominating peak around 180 degrees. In approximately six out of ten turning events, the cell reverses its swimming direction. In addition, our analysis revealed that upon a reversal, the cell systematically changes its swimming speed by a factor of two on average. Based on the experimentally observed values of mean runtime and rotational diffusion, we presented a model to describe the spreading of a population of cells by a run-reverse random walker with alternating speeds. We successfully recover the mean square displacement and, by an extended version of the model, also the negative dip in the directional autocorrelation function as observed in the experiments. The analytical solution of the model demonstrates that alternating speeds enhance a cells ability to explore its environment as compared to a bacterium moving at a constant intermediate speed. As compared to the bulk fluid, for cells swimming near a solid boundary we observed an increase in swimming speed at distances below d= 5 micrometer and an increase in average angular velocity at distances below d= 4 micrometer. While the average speed was maximal with an increase around 15% at a distance of d= 3 micrometer, the angular velocity was highest in closest proximity to the boundary at d=1 micrometer with an increase around 90% as compared to the bulk fluid. To investigate the swimming behavior in a confinement between two solid boundaries, we developed an experimental setup to acquire three-dimensional trajectories using a piezo driven objective mount coupled to a high speed camera. Results on speed and angular velocity were consistent with motility statistics in the presence of a single boundary. Additionally, an analysis of the probability density revealed that a majority of cells accumulated near the upper and lower boundaries of the microchannel. The increase in angular velocity is consistent with previous studies, where bacteria near a solid boundary were shown to swim on circular trajectories, an effect which can be attributed to a wall induced torque. The increase in speed at a distance of several times the size of the cell body, however, cannot be explained by existing theories which either consider the drag increase on cell body and flagellum near a boundary (resistive force theory) or model the swimming microorganism by a multipole expansion to account for the flow field interaction between cell and boundary. An accumulation of swimming bacteria near solid boundaries has been observed in similar experiments. Our results confirm that collisions with the surface play an important role and hydrodynamic interactions alone cannot explain the steady-state accumulation of cells near the channel walls. Furthermore, we monitored the number growth of cells in the microchannel under medium rich conditions. We observed that, after a lag time, initially isolated cells at the surface started to grow by division into colonies of increasing size, while coexisting with a comparable smaller number of swimming cells. After 5:50 hours, we observed a sudden jump in the number of swimming cells, which was accompanied by a breakup of bigger clusters on the surface. After approximately 30 minutes where planktonic cells dominated in the microchannel, individual swimming cells reattached to the surface. We interpret this process as an emigration and recolonization event. A number of complementary experiments were performed to investigate the influence of collective effects or a depletion of the growth medium on the transition. Similar to earlier observations on another bacterium from the same family we found that the release of cells to the swimming phase is most likely the result of an individual adaption process, where syntheses of proteins for flagellar motility are upregulated after a number of division cycles at the surface.
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.
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.
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.
One of the most exciting predictions of Einstein's theory of gravitation that have not yet been proven experimentally by a direct detection are gravitational waves. These are tiny distortions of the spacetime itself, and a world-wide effort to directly measure them for the first time with a network of large-scale laser interferometers is currently ongoing and expected to provide positive results within this decade. One potential source of measurable gravitational waves is the inspiral and merger of two compact objects, such as binary black holes. Successfully finding their signature in the noise-dominated data of the detectors crucially relies on accurate predictions of what we are looking for. In this thesis, we present a detailed study of how the most complete waveform templates can be constructed by combining the results from (A) analytical expansions within the post-Newtonian framework and (B) numerical simulations of the full relativistic dynamics. We analyze various strategies to construct complete hybrid waveforms that consist of a post-Newtonian inspiral part matched to numerical-relativity data. We elaborate on exsisting approaches for nonspinning systems by extending the accessible parameter space and introducing an alternative scheme based in the Fourier domain. Our methods can now be readily applied to multiple spherical-harmonic modes and precessing systems. In addition to that, we analyze in detail the accuracy of hybrid waveforms with the goal to quantify how numerous sources of error in the approximation techniques affect the application of such templates in real gravitational-wave searches. This is of major importance for the future construction of improved models, but also for the correct interpretation of gravitational-wave observations that are made utilizing any complete waveform family. In particular, we comprehensively discuss how long the numerical-relativity contribution to the signal has to be in order to make the resulting hybrids accurate enough, and for currently feasible simulation lengths we assess the physics one can potentially do with template-based searches.
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.
Noise is ubiquitous in nature and usually results in rich dynamics in stochastic systems such as oscillatory systems, which exist in such various fields as physics, biology and complex networks. The correlation and synchronization of two or many oscillators are widely studied topics in recent years.
In this thesis, we mainly investigate two problems, i.e., the stochastic bursting phenomenon in noisy excitable systems and synchronization in a three-dimensional Kuramoto model with noise. Stochastic bursting here refers to a sequence of coherent spike train, where each spike has random number of followers due to the combined effects of both time delay and noise. Synchronization, as a universal phenomenon in nonlinear dynamical systems, is well illustrated in the Kuramoto model, a prominent model in the description of collective motion.
In the first part of this thesis, an idealized point process, valid if the characteristic timescales in the problem are well separated, is used to describe statistical properties such as the power spectral density and the interspike interval distribution. We show how the main parameters of the point process, the spontaneous excitation rate, and the probability to induce a spike during the delay action can be calculated from the solutions of a stationary and a forced Fokker-Planck equation. We extend it to the delay-coupled case and derive analytically the statistics of the spikes in each neuron, the pairwise correlations between any two neurons, and the spectrum of the total output from the network.
In the second part, we investigate the three-dimensional noisy Kuramoto model, which can be used to describe the synchronization in a swarming model with helical trajectory. In the case without natural frequency, the Kuramoto model can be connected with the Vicsek model, which is widely studied in collective motion and swarming of active matter. We analyze the linear stability of the incoherent state and derive the critical coupling strength above which the incoherent state loses stability. In the limit of no natural frequency, an exact self-consistent equation of the mean field is derived and extended straightforward to any high-dimensional case.
The Casimir-Polder interaction between a single neutral atom and a nearby surface, arising from the (quantum and thermal) fluctuations of the electromagnetic field, is a cornerstone of cavity quantum electrodynamics (cQED), and theoretically well established. Recently, Bose-Einstein condensates (BECs) of ultracold atoms have been used to test the predictions of cQED. The purpose of the present thesis is to upgrade single-atom cQED with the many-body theory needed to describe trapped atomic BECs. Tools and methods are developed in a second-quantized picture that treats atom and photon fields on the same footing. We formulate a diagrammatic expansion using correlation functions for both the electromagnetic field and the atomic system. The formalism is applied to investigate, for BECs trapped near surfaces, dispersion interactions of the van der Waals-Casimir-Polder type, and the Bosonic stimulation in spontaneous decay of excited atomic states. We also discuss a phononic Casimir effect, which arises from the quantum fluctuations in an interacting BEC.
Changes in extratropical storm track activity and their implications for extreme weather events
(2016)
This work investigates diffusion in nonlinear Hamiltonian systems. The diffusion, more precisely subdiffusion, in such systems is induced by the intrinsic chaotic behavior of trajectories and thus is called chaotic diffusion''. Its properties are studied on the example of one- or two-dimensional lattices of harmonic or nonlinear oscillators with nearest neighbor couplings. The fundamental observation is the spreading of energy for localized initial conditions. Methods of quantifying this spreading behavior are presented, including a new quantity called excitation time. This new quantity allows for a more precise analysis of the spreading than traditional methods. Furthermore, the nonlinear diffusion equation is introduced as a phenomenologic description of the spreading process and a number of predictions on the density dependence of the spreading are drawn from this equation. Two mathematical techniques for analyzing nonlinear Hamiltonian systems are introduced. The first one is based on a scaling analysis of the Hamiltonian equations and the results are related to similar scaling properties of the NDE. From this relation, exact spreading predictions are deduced. Secondly, the microscopic dynamics at the edge of spreading states are thoroughly analyzed, which again suggests a scaling behavior that can be related to the NDE. Such a microscopic treatment of chaotically spreading states in nonlinear Hamiltonian systems has not been done before and the results present a new technique of connecting microscopic dynamics with macroscopic descriptions like the nonlinear diffusion equation. All theoretical results are supported by heavy numerical simulations, partly obtained on one of Europe's fastest supercomputers located in Bologna, Italy. In the end, the highly interesting case of harmonic oscillators with random frequencies and nonlinear coupling is studied, which resembles to some extent the famous Discrete Anderson Nonlinear Schroedinger Equation. For this model, a deviation from the widely believed power-law spreading is observed in numerical experiments. Some ideas on a theoretical explanation for this deviation are presented, but a conclusive theory could not be found due to the complicated phase space structure in this case. Nevertheless, it is hoped that the techniques and results presented in this work will help to eventually understand this controversely discussed case as well.
In this work, binding interactions between biomolecules were analyzed by a technique that is based on electrically controllable DNA nanolevers. The technique was applied to virus-receptor interactions for the first time. As receptors, primarily peptides on DNA nanostructures and antibodies were utilized. The DNA nanostructures were integrated into the measurement technique and enabled the presentation of the peptides in a controllable geometrical order. The number of peptides could be varied to be compatible to the binding sites of the viral surface proteins.
Influenza A virus served as a model system, on which the general measurability was demonstrated. Variations of the receptor peptide, the surface ligand density, the measurement temperature and the virus subtypes showed the sensitivity and applicability of the technology. Additionally, the immobilization of virus particles enabled the measurement of differences in oligovalent binding of DNA-peptide nanostructures to the viral proteins in their native environment.
When the coronavirus pandemic broke out in 2020, work on binding interactions of a peptide from the hACE2 receptor and the spike protein of the SARS-CoV-2 virus revealed that oligovalent binding can be quantified in the switchSENSE technology. It could also be shown that small changes in the amino acid sequence of the spike protein resulted in complete loss of binding. Interactions of the peptide and inactivated virus material as well as pseudo virus particles could be measured. Additionally, the switchSENSE technology was utilized to rank six antibodies for their binding affinity towards the nucleocapsid protein of SARS-CoV-2 for the development of a rapid antigen test device.
The technique was furthermore employed to show binding of a non-enveloped virus (adenovirus) and a virus-like particle (norovirus-like particle) to antibodies. Apart from binding interactions, the use of DNA origami levers with a length of around 50 nm enabled the switching of virus material. This proved that the technology is also able to size objects with a hydrodynamic diameter larger than 14 nm.
A theoretical work on diffusion and reaction-limited binding interactions revealed that the technique and the chosen parameters enable the determination of binding rate constants in the reaction-limited regime.
Overall, the applicability of the switchSENSE technique to virus-receptor binding interactions could be demonstrated on multiple examples. While there are challenges that remain, the setup enables the determination of affinities between viruses and receptors in their native environment. Especially the possibilities regarding the quantification of oligo- and multivalent binding interactions could be presented.
We investigate properties of quantum mechanical systems in the light of quantum information theory. We put an emphasize on systems with infinite-dimensional Hilbert spaces, so-called continuous-variable systems'', which are needed to describe quantum optics beyond the single photon regime and other Bosonic quantum systems. We present methods to obtain a description of such systems from a series of measurements in an efficient manner and demonstrate the performance in realistic situations by means of numerical simulations. We consider both unconditional quantum state tomography, which is applicable to arbitrary systems, and tomography of matrix product states. The latter allows for the tomography of many-body systems because the necessary number of measurements scales merely polynomially with the particle number, compared to an exponential scaling in the generic case. We also present a method to realize such a tomography scheme for a system of ultra-cold atoms in optical lattices. Furthermore, we discuss in detail the possibilities and limitations of using continuous-variable systems for measurement-based quantum computing. We will see that the distinction between Gaussian and non-Gaussian quantum states and measurements plays an crucial role. We also provide an algorithm to solve the large and interesting class of naturally occurring Hamiltonians, namely frustration free ones, efficiently and use this insight to obtain a simple approximation method for slightly frustrated systems. To achieve this goals, we make use of, among various other techniques, the well developed theory of matrix product states, tensor networks, semi-definite programming, and matrix analysis.
Over the past decades, there has been a growing interest in ‘extreme events’ owing to the increasing threats that climate-related extremes such as floods, heatwaves, droughts, etc., pose to society. While extreme events have diverse definitions across various disciplines, ranging from earth science to neuroscience, they are characterized mainly as dynamic occurrences within a limited time frame that impedes the normal functioning of a system. Although extreme events are rare in occurrence, it has been found in various hydro-meteorological and physiological time series (e.g., river flows, temperatures, heartbeat intervals) that they may exhibit recurrent behavior, i.e., do not end the lifetime of the system. The aim of this thesis to develop some
sophisticated methods to study various properties of extreme events.
One of the main challenges in analyzing such extreme event-like time series is that they have large temporal gaps due to the paucity of the number of observations of extreme events. As a result, existing time series analysis tools are usually not helpful to decode the underlying
information. I use the edit distance (ED) method to analyze extreme event-like time series in their unaltered form. ED is a specific distance metric, mainly designed to measure the similarity/dissimilarity between point process-like data. I combine ED with recurrence plot techniques to identify the recurrence property of flood events in the Mississippi River in the United States. I also use recurrence quantification analysis to show the deterministic properties
and serial dependency in flood events.
After that, I use this non-linear similarity measure (ED) to compute the pairwise dependency in extreme precipitation event series. I incorporate the similarity measure within the framework of complex network theory to study the collective behavior of climate extremes. Under this architecture, the nodes are defined by the spatial grid points of the given spatio-temporal climate dataset. Each node is associated with a time series corresponding to the temporal evolution
of the climate observation at that grid point. Finally, the network links are functions of the pairwise statistical interdependence between the nodes. Various network measures, such as degree, betweenness centrality, clustering coefficient, etc., can be used to quantify the network’s topology. We apply the methodology mentioned above to study the spatio-temporal coherence pattern of extreme rainfall events in the United States and the Ganga River basin, which reveals its relation to various climate processes and the orography of the region.
The identification of precursors associated with the occurrence of extreme events in the near future is extremely important to prepare the masses for an upcoming disaster and mitigate the potential risks associated with such events. Under this motivation, I propose an in-data prediction recipe for predicting the data structures that typically occur prior to extreme events using the Echo state network, a type of Recurrent Neural Network which is a part of the reservoir
computing framework. However, unlike previous works that identify precursory structures in the same variable in which extreme events are manifested (active variable), I try to predict these structures by using data from another dynamic variable (passive variable) which does not show large excursions from the nominal condition but carries imprints of these extreme events. Furthermore, my results demonstrate that the quality of prediction depends on the magnitude
of events, i.e., the higher the magnitude of the extreme, the better is its predictability skill. I show quantitatively that this is because the input signals collectively form a more coherent pattern for an extreme event of higher magnitude, which enhances the efficiency of the machine to predict the forthcoming extreme events.
This thesis discusses heat and charge transport phenomena in single-crystalline Silicon penetrated by nanometer-sized pores, known as mesoporous Silicon (pSi). Despite the extensive attention given to it as a thermoelectric material of interest, studies on microscopic thermal and electronic transport beyond its macroscopic characterizations are rarely reported. In contrast, this work reports the interplay of both.
PSi samples synthesized by electrochemical anodization display a temperature dependence of specific heat 𝐶𝑝 that deviates from the characteristic 𝑇^3 behaviour (at 𝑇<50𝐾). A thorough analysis reveals that both 3D and 2D Einstein and Debye modes contribute to this specific heat. Additional 2D Einstein modes (~3 𝑚𝑒𝑉) agree reasonably well with the boson peak of SiO2 in pSi pore walls. 2D Debye modes are proposed to account for surface acoustic modes causing a significant deviation from the well-known 𝑇^3 dependence of 𝐶𝑝 at 𝑇<50𝐾.
A novel theoretical model gives insights into the thermal conductivity of pSi in terms of porosity and phonon scattering on the nanoscale. The thermal conductivity analysis utilizes the peculiarities of the pSi phonon dispersion probed by the inelastic neutron scattering experiments. A phonon mean-free path of around 10 𝑛𝑚 extracted from the presented model is proposed to cause the reduced thermal conductivity of pSi by two orders of magnitude compared to p-doped bulk Silicon. Detailed analysis indicates that compound averaging may cause a further 10-50% reduction. The percolation threshold of 65% for thermal conductivity of pSi samples is subsequently determined by employing theoretical effective medium models.
Temperature-dependent electrical conductivity measurements reveal a thermally activated transport process. A detailed analysis of the activation energy 𝐸𝐴𝜎 in the thermally activated transport exhibits a Meyer Neldel compensation rule between different samples that originates in multi-phonon absorption upon carrier transport. Activation energies 𝐸𝐴𝑆 obtained from temperature-dependent thermopower measurements provide further evidence for multi-phonon assisted hopping between localized states as a dominant charge transport mechanism in pSi, as they systematically differ from the determined 𝐸𝐴𝜎 values.
Tremendous progress in the development of thin film solar cell techniques has been made over the last decade. The field of organic solar cells is constantly developing, new material classes like Perowskite solar cells are emerging and different types of hybrid organic/inorganic material combinations are being investigated for their physical properties and their applicability in thin film electronics. Besides typical single-junction architectures for solar cells, multi-junction concepts are also being investigated as they enable the overcoming of theoretical limitations of a single-junction. In multi-junction devices each sub-cell operates in different wavelength regimes and should exhibit optimized band-gap energies. It is exactly this tunability of the band-gap energy that renders organic solar cell materials interesting candidates for multi-junction applications. Nevertheless, only few attempts have been made to combine inorganic and organic solar cells in series connected multi-junction architectures. Even though a great diversity of organic solar cells exists nowadays, their open circuit voltage is usually low compared to the band-gap of the active layer. Hence, organic low band-gap solar cells in particular show low open circuit voltages and the key factors that determine the voltage losses are not yet fully understood. Besides open circuit voltage losses the recombination of charges in organic solar cells is also a prevailing research topic, especially with respect to the influence of trap states.
The exploratory focus of this work is therefore set, on the one hand, on the development of hybrid organic/inorganic multi-junctions and, on the other hand, on gaining a deeper understanding of the open circuit voltage and the recombination processes of organic solar cells.
In the first part of this thesis, the development of a hybrid organic/inorganic triple-junction will be discussed which showed at that time (Jan. 2015) a record power conversion efficiency of 11.7%. The inorganic sub-cells of these devices consist of hydrogenated amorphous silicon and were delivered by the Competence Center Thin-Film and Nanotechnology for Photovoltaics in Berlin. Different recombination contacts and organic sub-cells were tested in conjunction with these inorganic sub-cells on the basis of optical modeling predictions for the optimal layer thicknesses to finally reach record efficiencies for this type of solar cells.
In the second part, organic model systems will be investigated to gain a better understanding of the fundamental loss mechanisms that limit the open circuit voltage of organic solar cells. First, bilayer systems with different orientation of the donor and acceptor molecules were investigated to study the influence of the donor/acceptor orientation on non-radiative voltage loss. Secondly, three different bulk heterojunction solar cells all comprising the same amount of fluorination and the same polymer backbone in the donor component were examined to study the influence of long range electrostatics on the open circuit voltage. Thirdly, the device performance of two bulk heterojunction solar cells was compared which consisted of the same donor polymer but used different fullerene acceptor molecules. By this means, the influence of changing the energetics of the acceptor component on the open circuit voltage was investigated and a full analysis of the charge carrier dynamics was presented to unravel the reasons for the worse performance of the solar cell with the higher open circuit voltage. In the third part, a new recombination model for organic solar cells will be introduced and its applicability shown for a typical low band-gap cell. This model sheds new light on the recombination process in organic solar cells in a broader context as it re-evaluates the recombination pathway of charge carriers in devices which show the presence of trap states. Thereby it addresses a current research topic and helps to resolve alleged discrepancies which can arise from the interpretation of data derived by different measurement techniques.
In view of the importance of charge storage in polymer electrets for electromechanical transducer applications, the aim of this work is to contribute to the understanding of the charge-retention mechanisms. Furthermore, we will try to explain how the long-term storage of charge carriers in polymeric electrets works and to identify the probable trap sites. Charge trapping and de-trapping processes were investigated in order to obtain evidence of the trap sites in polymeric electrets. The charge de-trapping behavior of two particular polymer electrets was studied by means of thermal and optical techniques. In order to obtain evidence of trapping or de-trapping, charge and dipole profiles in the thickness direction were also monitored. In this work, the study was performed on polyethylene terephthalate (PETP) and on cyclic-olefin copolymers (COCs). PETP is a photo-electret and contains a net dipole moment that is located in the carbonyl group (C = O). The electret behavior of PETP arises from both the dipole orientation and the charge storage. In contrast to PETP, COCs are not photo-electrets and do not exhibit a net dipole moment. The electret behavior of COCs arises from the storage of charges only. COC samples were doped with dyes in order to probe their internal electric field. COCs show shallow charge traps at 0.6 and 0.11 eV, characteristic for thermally activated processes. In addition, deep charge traps are present at 4 eV, characteristic for optically stimulated processes. PETP films exhibit a photo-current transient with a maximum that depends on the temperature with an activation energy of 0.106 eV. The pair thermalization length (rc) calculated from this activation energy for the photo-carrier generation in PETP was estimated to be approx. 4.5 nm. The generated photo-charge carriers can recombine, interact with the trapped charge, escape through the electrodes or occupy an empty trap. PETP possesses a small quasi-static pyroelectric coefficient (QPC): ~0.6 nC/(m²K) for unpoled samples, ~60 nC/(m²K) for poled samples and ~60 nC/(m²K) for unpoled samples under an electric bias (E ~10 V/µm). When stored charges generate an internal electric field of approx. 10 V/µm, they are able to induce a QPC comparable to that of the oriented dipoles. Moreover, we observe charge-dipole interaction. Since the raw data of the QPC-experiments on PETP samples is noisy, a numerical Fourier-filtering procedure was applied. Simulations show that the data analysis is reliable when the noise level is up to 3 times larger than the calculated pyroelectric current for the QPC. PETP films revealed shallow traps at approx. 0.36 eV during thermally-stimulated current measurements. These energy traps are associated with molecular dipole relaxations (C = O). On the other hand, photo-activated measurements yield deep charge traps at 4.1 and 5.2 eV. The observed wavelengths belong to the transitions in PETP that are analogous to the π - π* benzene transitions. The observed charge de-trapping selectivity in the photocharge decay indicates that the charge detrapping is from a direct photon-charge interaction. Additionally, the charge de-trapping can be facilitated by photo-exciton generation and the interaction of the photo-excitons with trapped charge carriers. These results indicate that the benzene rings (C6H4) and the dipolar groups (C = O) can stabilize and share an extra charge carrier in a chemical resonance. In this way, this charge could be de-trapped in connection with the photo-transitions of the benzene ring and with the dipole relaxations. The thermally-activated charge release shows a difference in the trap depth to its optical counterpart. This difference indicates that the trap levels depend on the de-trapping process and on the chemical nature of the trap site. That is, the processes of charge detrapping from shallow traps are related to secondary forces. The processes of charge de-trapping from deep traps are related to primary forces. Furthermore, the presence of deep trap levels causes the stability of the charge for long periods of time.
This work explores the equilibrium structure and thermodynamic phase behavior of complexes formed by charged polymer chains (polyelectrolytes) and oppositely charged spheres (macroions). Polyelectrolyte-macroion complexes form a common pattern in soft-matter physics, chemistry and biology, and enter in numerous technological applications as well. From a fundamental point of view, such complexes are interesting in that they combine the subtle interplay between electrostatic interactions and elastic as well as entropic effects due to conformational changes of the polymer chain, giving rise to a wide range of structural properties. This forms the central theme of theoretical studies presented in this thesis, which concentrate on a number of different problems involving strongly coupled complexes, i.e. complexes that are characterized by a large adsorption energy and small chain fluctuations. In the first part, a global analysis of the structural phase behavior of a single polyelectrolyte-macroion complex is presented based on a dimensionless representation, yielding results that cover a wide range of realistic system parameters. Emphasize is made on the interplay between the effects due to the polyelectrolytes chain length, salt concentration and the macroion charge as well as the mechanical chain persistence length. The results are summarized into generic phase diagrams characterizing the wrapping-dewrapping behavior of a polyelectrolyte chain on a macroion. A fully wrapped chain state is typically obtained at intermediate salt concentrations and chain lengths, where the amount of polyelectrolyte charge adsorbed on the macroion typically exceeds the bare macroion charge leading thus to a highly overcharged complex. Perhaps the most striking features occur when a single long polyelectrolyte chain is complexed with many oppositely charged spheres. In biology, such complexes form between DNA (which carries the cell's genetic information) and small oppositely charged histone proteins serving as an efficient mechanism for packing a huge amount of DNA into the micron-size cell nucleus in eucaryotic cells. The resultant complex fiber, known as the chromatin fiber, appears with a diameter of 30~nm under physiological conditions. Recent experiments indicate a zig-zag spatial arrangement for individual DNA-histone complexes (nucleosome core particles) along the chromatin fiber. A numerical method is introduced in this thesis based on a simple generic chain-sphere cell model that enables one to investigate the mechanism of fiber formation on a systematic level by incorporating electrostatic and elastic contributions. As will be shown, stable complex fibers exhibit an impressive variety of structures including zig-zag, solenoidal and beads-on-a-string patterns, depending on system parameters such as salt concentration, sphere charge as well as the chain contour length (per sphere). The present results predict fibers of compact zig-zag structure within the physiologically relevant regime with a diameter of about 30~nm, when DNA-histone parameters are adopted. In the next part, a numerical method is developed in order to investigate the role of thermal fluctuations on the structure and thermodynamic phase behavior of polyelectrolyte-macroion complexes. This is based on a saddle-point approximation, which allows to describe the experimentally observed reaction (or complexation) equilibrium in a dilute solution of polyelectrolytes and macroions on a systematic level. This equilibrium is determined by the entropy loss a single polyelectrolyte chain suffers as it binds to an oppositely charged macroion. This latter quantity can be calculated from the spectrum of polyelectrolyte fluctuations around a macroion, which is determined by means of a normal-mode analysis. Thereby, a stability phase diagram is obtained, which exhibits qualitative agreement with experimental findings. At elevated complex concentrations, one needs to account for the inter-complex interactions as well. It will be shown that at small separations, complexes undergo structural changes in such a way that positive patches from one complex match up with negative patches on the other. Furthermore, one of the polyelectrolyte chains may bridge between the two complexes. These mechanisms lead to a strong inter-complex attraction. As a result, the second virial coefficient associated with the inter-complex interaction becomes negative at intermediate salt concentrations in qualitative agreement with recent experiments on solutions of nucleosome core particles.
One of the rules-of-thumb of colloid and surface physics is that most surfaces are charged when in contact with a solvent, usually water. This is the case, for instance, in charge-stabilized colloidal suspensions, where the surface of the colloidal particles are charged (usually with a charge of hundreds to thousands of e, the elementary charge), monolayers of ionic surfactants sitting at an air-water interface (where the water-loving head groups become charged by releasing counterions), or bilayers containing charged phospholipids (as cell membranes). In this work, we look at some model-systems that, although being a simplified version of reality, are expected to capture some of the physical properties of real charged systems (colloids and electrolytes). We initially study the simple double layer, composed by a charged wall in the presence of its counterions. The charges at the wall are smeared out and the dielectric constant is the same everywhere. The Poisson-Boltzmann (PB) approach gives asymptotically exact counterion density profiles around charged objects in the weak-coupling limit of systems with low-valent counterions, surfaces with low charge density and high temperature (or small Bjerrum length). Using Monte Carlo simulations, we obtain the profiles around the charged wall and compare it with both Poisson-Boltzmann (in the low coupling limit) and the novel strong coupling (SC) theory in the opposite limit of high couplings. In the latter limit, the simulations show that the SC leads in fact to asymptotically correct density profiles. We also compare the Monte Carlo data with previously calculated corrections to the Poisson-Boltzmann theory. We also discuss in detail the methods used to perform the computer simulations. After studying the simple double layer in detail, we introduce a dielectric jump at the charged wall and investigate its effect on the counterion density distribution. As we will show, the Poisson-Boltzmann description of the double layer remains a good approximation at low coupling values, while the strong coupling theory is shown to lead to the correct density profiles close to the wall (and at all couplings). For very large couplings, only systems where the difference between the dielectric constants of the wall and of the solvent is small are shown to be well described by SC. Another experimentally relevant modification to the simple double layer is to make the charges at the plane discrete. The counterions are still assumed to be point-like, but we constraint the distance of approach between ions in the plane and counterions to a minimum distance D. The ratio between D and the distance between neighboring ions in the plane is, as we will see, one of the important quantities in determining the influence of the discrete nature of the charges at the wall over the density profiles. Another parameter that plays an important role, as in the previous case, is the coupling as we will demonstrate, systems with higher coupling are more subject to discretization effects than systems with low coupling parameter. After studying the isolated double layer, we look at the interaction between two double layers. The system is composed by two equally charged walls at distance d, with the counterions confined between them. The charge at the walls is smeared out and the dielectric constant is the same everywhere. Using Monte-Carlo simulations we obtain the inter-plate pressure in the global parameter space, and the pressure is shown to be negative (attraction) at certain conditions. The simulations also show that the equilibrium plate separation (where the pressure changes from attractive to repulsive) exhibits a novel unbinding transition. We compare the Monte Carlo results with the strong-coupling theory, which is shown to describe well the bound states of systems with moderate and high couplings. The regime where the two walls are very close to each other is also shown to be well described by the SC theory. Finally, Using a field-theoretic approach, we derive the exact low-density ("virial") expansion of a binary mixture of positively and negatively charged hard spheres (two-component hard-core plasma, TCPHC). The free energy obtained is valid for systems where the diameters d_+ and d_- and the charge valences q_+ and q_- of positive and negative ions are unconstrained, i.e., the same expression can be used to treat dilute salt solutions (where typically d_+ ~ d_- and q_+ ~ q_-) as well as colloidal suspensions (where the difference in size and valence between macroions and counterions can be very large). We also discuss some applications of our results.
In the living cell, the organization of the complex internal structure relies to a large extent on molecular motors. Molecular motors are proteins that are able to convert chemical energy from the hydrolysis of adenosine triphosphate (ATP) into mechanical work. Being about 10 to 100 nanometers in size, the molecules act on a length scale, for which thermal collisions have a considerable impact onto their motion. In this way, they constitute paradigmatic examples of thermodynamic machines out of equilibrium. This study develops a theoretical description for the energy conversion by the molecular motor myosin V, using many different aspects of theoretical physics. Myosin V has been studied extensively in both bulk and single molecule experiments. Its stepping velocity has been characterized as a function of external control parameters such as nucleotide concentration and applied forces. In addition, numerous kinetic rates involved in the enzymatic reaction of the molecule have been determined. For forces that exceed the stall force of the motor, myosin V exhibits a 'ratcheting' behaviour: For loads in the direction of forward stepping, the velocity depends on the concentration of ATP, while for backward loads there is no such influence. Based on the chemical states of the motor, we construct a general network theory that incorporates experimental observations about the stepping behaviour of myosin V. The motor's motion is captured through the network description supplemented by a Markov process to describe the motor dynamics. This approach has the advantage of directly addressing the chemical kinetics of the molecule, and treating the mechanical and chemical processes on equal grounds. We utilize constraints arising from nonequilibrium thermodynamics to determine motor parameters and demonstrate that the motor behaviour is governed by several chemomechanical motor cycles. In addition, we investigate the functional dependence of stepping rates on force by deducing the motor's response to external loads via an appropriate Fokker-Planck equation. For substall forces, the dominant pathway of the motor network is profoundly different from the one for superstall forces, which leads to a stepping behaviour that is in agreement with the experimental observations. The extension of our analysis to Markov processes with absorbing boundaries allows for the calculation of the motor's dwell time distributions. These reveal aspects of the coordination of the motor's heads and contain direct information about the backsteps of the motor. Our theory provides a unified description for the myosin V motor as studied in single motor experiments.
We present electrical impedance measurements of amoeboid cells on microelectrodes. The model organism Dictyostelium discoideum shows under starvation conditions a transition to collective behavior when chemotactic cells collect in multicellular aggregates. We show how impedance recordings give a precise picture of the stages of aggregation by tracing the dynamics of cell-substrate adhesion. Furthermore, we present for the first time systematic single cell measurements of wild type cells and four mutant strains that differ in their substrate adhesion strength. We recorded the projected cell area by time lapse microscopy and found a correlation between quasi-periodic oscillations in the kinetics of the projected area - the cell shape oscillation - and the long-term trend in the impedance signal. Typically, amoeboid motility advances via a cycle of membrane protrusion, substrate adhesion, traction of the cell body and tail retraction. This motility cycle results in the quasi-periodic oscillations of the projected cell area and the impedance. In all cell lines measured, similar periods were observed for this cycle, despite the differences in attachment strength. We observed that cell-substrate attachment strength strongly affects the impedance in that the deviations from mean (the magnitude of fluctuations) are enhanced in cells that effectively transmit forces, generated by the cytoskeleton, to the substrate. For example, in talA- cells, which lack the actin anchoring protein talin, the fluctuations are strongly reduced. Single cell force spectroscopy and results from a detachment assay, where adhesion is measured by exposing cells to shear stress, confirm that the magnitude of impedance fluctuations is a correct measure for the strength of substrate adhesion. Finally, we also worked on the integration of cell-substrate impedance sensors into microfluidic devices. A chip-based electrical chemotaxis assay is designed which measures the speed of chemotactic cells migrating over microelectrodes along a chemical concentration gradient.
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.