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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.
There is a large variety of goals instructors have for laboratory courses, with different courses focusing on different subsets of goals. An often implicit, but crucial, goal is to develop students’ attitudes, views, and expectations about experimental physics to align with practicing experimental physicists. The assessment of laboratory courses upon this one dimension of learning has been intensively studied in U.S. institutions using the Colorado Learning Attitudes about Science Survey for Experimental Physics (E-CLASS). However, there is no such an instrument available to use in Germany, and the influence of laboratory courses on students views about the nature of experimental physics is still unexplored at German-speaking institutions. Motivated by the lack of an assessment tool to investigate this goal in laboratory courses at German-speaking institutions, we present a translated version of the E-CLASS adapted to the context at German-speaking institutions. We call the German version of the E-CLASS, the GE-CLASS. We describe the translation process and the creation of an automated web-based system for instructors to assess their laboratory courses. We also present first results using GE-CLASS obtained at the University of Potsdam. A first comparison between E-CLASS and GE-CLASS results shows clear differences between University of Potsdam and U.S. students’ views and beliefs about experimental physics.
We introduce and study a Lévy walk (LW) model of particle spreading with a finite propagation speed combined with soft resets, stochastically occurring periods in which an harmonic external potential is switched on and forces the particle towards a specific position. Soft resets avoid instantaneous relocation of particles that in certain physical settings may be considered unphysical. Moreover, soft resets do not have a specific resetting point but lead the particle towards a resetting point by a restoring Hookean force. Depending on the exact choice for the LW waiting time density and the probability density of the periods when the harmonic potential is switched on, we demonstrate a rich emerging response behaviour including ballistic motion and superdiffusion. When the confinement periods of the soft-reset events are dominant, we observe a particle localisation with an associated non-equilibrium steady state. In this case the stationary particle probability density function turns out to acquire multimodal states. Our derivations are based on Markov chain ideas and LWs with multiple internal states, an approach that may be useful and flexible for the investigation of other generalised random walks with soft and hard resets. The spreading efficiency of soft-rest LWs is characterised by the first-passage time statistic.
Stellar interferometry is the only method in observational astronomy for obtaining the highest resolution images of astronomical targets. This method is based on combining light from two or more separate telescopes to obtain the complex visibility that contains information about the brightness distribution of an astronomical source. The applications of stellar interferometry have made significant contributions in the exciting research areas of astronomy and astrophysics, including the precise measurement of stellar diameters, imaging of stellar surfaces, observations of circumstellar disks around young stellar objects, predictions of Einstein's General relativity at the galactic center, and the direct search for exoplanets to name a few. One important related technique is aperture masking interferometry, pioneered in the 1960s, which uses a mask with holes at the re-imaged pupil of the telescope, where the light from the holes is combined using the principle of stellar interferometry. While this can increase the resolution, it comes with a disadvantage. Due to the finite size of the holes, the majority of the starlight (typically > 80 %) is lost at the mask, thus limiting the signal-to-noise ratio (SNR) of the output images. This restriction of aperture masking only to the bright targets can be avoided using pupil remapping interferometry - a technique combining aperture masking interferometry and advances in photonic technologies using single-mode fibers. Due to the inherent spatial filtering properties, the single-mode fibers can be placed at the focal plane of the re-imaged pupil, allowing the utilization of the whole pupil of the telescope to produce a high-dynamic range along with high-resolution images. Thus, pupil remapping interferometry is one of the most promising application areas in the emerging field of astrophotonics.
At the heart of an interferometric facility, a beam combiner exists whose primary function is to combine light to obtain high-contrast fringes. A beam combiner can be as simple as a beam splitter or an anamorphic lens to combine light from 2 apertures (or telescopes) or as complex as a cascade of beam splitters and lenses to combine light for > 2 apertures. However, with the field of astrophotonics, interferometric facilities across the globe are increasingly employing some form of photonics technologies by using single-mode fibers or integrated optics (IO) chips as an efficient way to combine light from several apertures. The state-of-the-art instrument - GRAVITY at the very large telescope interferometer (VLTI) facility uses an IO-based beam combiner device reaching visibilities accuracy of better than < 0.25 %, which is roughly 50× as precise as a few decades back.
Therefore, in the context of IO-based components for applications in stellar interferometry, this Thesis describes the work towards the development of a 3-dimensional (3-D) IO device - a monolithic astrophotonics component containing both the pupil remappers and a discrete beam combiner (DBC). In this work, the pupil remappers are 3-D single-mode waveguides in a glass substrate collecting light from the re-imaged pupil of the telescope and feeding the light to a DBC, where the combination takes place. The DBC is a lattice of 3-D single-mode waveguides, which interact through evanescent coupling. By observing the output power of single-mode waveguides of the DBC, the visibilities are retrieved by using a calibrated transfer matrix ({U}) of the device.
The feasibility of the DBC in retrieving the visibilities theoretically and experimentally had already been studied in the literature but was only limited to laboratory tests with monochromatic light sources. Thus, a part of this work extends these studies by investigating the response of a 4-input DBC to a broad-band light source. Hence, the objectives of this Thesis are the following: 1) Design an IO device for broad-band light operation such that accurate and precise visibilities could be retrieved experimentally at astronomical H-band (1.5-1.65 μm), and 2) Validation of the DBC as a possible beam combination scheme for future interferometric facilities through on-sky testing at the William Herschel Telescope (WHT).
This work consisted of designing three different 3-D IO devices. One of the popular methods for fabricating 3-D photonic components in a glass substrate is ultra-fast laser inscription (ULI). Thus, manufacturing of the designed devices was outsourced to Politecnico di Milano as part of an iterative fabrication process using their state-of-the-art ULI facility. The devices were then characterized using a 2-beam Michelson interferometric setup obtaining both the monochromatic and polychromatic visibilities. The retrieved visibilities for all devices were in good agreement as predicted by the simulation results of a DBC, which confirms both the repeatability of the ULI process and the stability of the Michelson setup, thus fulfilling the first objective.
The best-performing device was then selected for the pupil-remapping of the WHT using a different optical setup consisting of a deformable mirror and a microlens array. The device successfully collected stellar photons from Vega and Altair. The visibilities were retrieved using a previously calibrated {U} but showed significant deviations from the expected results. Based on the analysis of comparable simulations, it was found that such deviations were primarily caused by the limited SNR of the stellar observations, thus constituting a first step towards the fulfillment of the second objective.
Understanding the changes that follow UV-excitation in thionucleobases is of great importance for the study of light-induced DNA lesions and, in a broader context, for their applications in medicine and biochemistry. Their ultrafast photophysical reactions can alter the chemical structure of DNA - leading to damages to the genetic code - as proven by the increased skin cancer risk observed for patients treated with thiouracil for its immunosuppressant properties.
In this thesis, I present four research papers that result from an investigation of the ultrafast dynamics of 2-thiouracil by means of ultrafast x-ray probing combined with electron spectroscopy. A molecular jet in the gas phase is excited with a uv pulse and then ionized with x-ray radiation from a Free Electron Laser. The kinetic energy of the emitted electrons is measured in a magnetic bottle spectrometer. The spectra of the measured photo and Auger electrons are used to derive a picture of the changes in the geometrical and electronic configurations. The results allow us to look at the dynamical processes from a new perspective, thanks to the element- and site- sensitivity of x-rays. The custom-built URSA-PQ apparatus used in the experiment is described. It has been commissioned and used at the FL24 beamline of the FLASH2 FEL, showing an electron kinetic energy resolution of ∆E/E ~ 40 and a pump-probe timing resolution of 190 f s. X-ray only photoelectron and Auger spectra of 2-thiouracil are extracted from the data and used as reference. Photoelectrons following the formation a 2p core hole are identified, as well as resonant and non-resonant Auger electrons. At the L 1 edge, Coster-Kronig decay is observed from the 2s core hole.
The UV-induced changes in the 2p photoline allow the study the electronic-state dynamics. With the use of an Excited-State Chemical Shift (ESCS) model, we observe a ultrafast ground-state relaxation within 250 f s. Furthermore, an oscillation with a 250 f s period is observed in the 2p binding energy, showing a coherent population exchange between electronic states. Auger electrons from the 2p core hole are analyzed and used to deduce a ultrafast C −S bond expansion on a sub 100 f s scale. A simple Coulomb-model, coupled to quantum chemical calculations, can be used to infer the geometrical changes in the molecular structure.
Organic solar cells offer an efficient and cost-effective alternative for solar energy harvesting. This type of photovoltaic cell typically consists of a blend of two organic semiconductors, an electron donating polymer and a low molecular weight electron acceptor to create what is known as a bulk heterojunction (BHJ) morphology. Traditionally, fullerene-based acceptors have been used for this purpose. In recent years, the development of new acceptor molecules, so-called non-fullerene acceptors (NFA), has breathed new life into organic solar cell research, enabling record efficiencies close to 19%. Today, NFA-based solar cells are approaching their inorganic competitors in terms of photocurrent generation, but lag in terms of open circuit voltage (V_OC). Interestingly, the V_OC of these cells benefits from small offsets of orbital energies at the donor-NFA interface, although previous knowledge considered large energy offsets to be critical for efficient charge carrier generation. In addition, there are several other electronic and structural features that distinguish NFAs from fullerenes.
My thesis focuses on understanding the interplay between the unique attributes of NFAs and the physical processes occurring in solar cells. By combining various experimental techniques with drift-diffusion simulations, the generation of free charge carriers as well as their recombination in state-of-the-art NFA-based solar cells is characterized. For this purpose, solar cells based on the donor polymer PM6 and the NFA Y6 have been investigated. The generation of free charge carriers in PM6:Y6 is efficient and independent of electric field and excitation energy. Temperature-dependent measurements show a very low activation energy for photocurrent generation (about 6 meV), indicating barrierless charge carrier separation. Theoretical modeling suggests that Y6 molecules have large quadrupole moments, leading to band bending at the donor-acceptor interface and thereby reducing the electrostatic Coulomb dissociation barrier. In this regard, this work identifies poor extraction of free charges in competition with nongeminate recombination as a dominant loss process in PM6:Y6 devices. Subsequently, the spectral characteristics of PM6:Y6 solar cells were investigated with respect to the dominant process of charge carrier recombination. It was found that the photon emission under open-circuit conditions can be almost entirely attributed to the occupation and recombination of Y6 singlet excitons. Nevertheless, the recombination pathway via the singlet state contributes only 1% to the total recombination, which is dominated by the charge transfer state (CT-state) at the donor-acceptor interface. Further V_OC gains can therefore only be expected if the density and/or recombination rate of these CT-states can be significantly reduced. Finally, the role of energetic disorder in NFA solar cells is investigated by comparing Y6 with a structurally related derivative, named N4. Layer morphology studies combined with temperature-dependent charge transport experiments show significantly lower structural and energetic disorder in the case of the PM6:Y6 blend. For both PM6:Y6 and PM6:N4, disorder determines the maximum achievable V_OC, with PM6:Y6 benefiting from improved morphological order. Overall, the obtained findings point to avenues for the realization of NFA-based solar cells with even smaller V_OC losses. Further reduction of nongeminate recombination and energetic disorder should result in organic solar cells with efficiencies above 20% in the future.
We study the probability density function (PDF) of the first-reaction times between a diffusive ligand and a membrane-bound, immobile imperfect target region in a restricted 'onion-shell' geometry bounded by two nested membranes of arbitrary shapes. For such a setting, encountered in diverse molecular signal transduction pathways or in the narrow escape problem with additional steric constraints, we derive an exact spectral form of the PDF, as well as present its approximate form calculated by help of the so-called self-consistent approximation. For a particular case when the nested domains are concentric spheres, we get a fully explicit form of the approximated PDF, assess the accuracy of this approximation, and discuss various facets of the obtained distributions. Our results can be straightforwardly applied to describe the PDF of the terminal reaction event in multi-stage signal transduction processes.
Weather extremes pose a persistent threat to society on multiple layers. Besides an average of ~37,000 deaths per year, climate-related disasters cause destroyed properties and impaired economic activities, eroding people's livelihoods and prosperity. While global temperature rises – caused by anthropogenic greenhouse gas emissions – the direct impacts of climatic extreme events increase and will further intensify without proper adaptation measures. Additionally, weather extremes do not only have local direct effects. Resulting economic repercussions can propagate either upstream or downstream along trade chains causing indirect effects. One approach to analyze these indirect effects within the complex global supply network is the agent-based model Acclimate. Using and extending this loss-propagation model, I focus in this thesis on three aspects of the relation between weather extremes and economic repercussions.
First, extreme weather events cause direct impacts on local economic performance. I compute daily local direct output loss time series of heat stress, river floods, tropical cyclones, and their consecutive occurrence using (near-future) climate projection ensembles. These regional impacts are estimated based on physical drivers and local productivity distribution. Direct effects of the aforementioned disaster categories are widely heterogeneous concerning regional and temporal distribution. As well, their intensity changes differently under future warming. Focusing on the hurricane-impacted capital, I find that long-term growth losses increase with higher heterogeneity of a shock ensemble.
Second, repercussions are sectorally and regionally distributed via economic ripples within the trading network, causing higher-order effects. I use Acclimate to identify three phases of those economic ripples. Furthermore, I compute indirect impacts and analyze overall regional and global production and consumption changes. Regarding heat stress, global consumer losses double while direct output losses increase by a factor 1.5 between 2000 – 2039. In my research I identify the effect of economic ripple resonance and introduce it to climate impact research. This effect occurs if economic ripples of consecutive disasters overlap, which increases economic responses such as an enhancement of consumption losses. These loss enhancements can even be more amplified with increasing direct output losses, e.g. caused by climate crises.
Transport disruptions can cause economic repercussions as well. For this, I extend the model Acclimate with a geographical transportation route and expand the decision horizon of economic agents. Using this, I show that policy-induced sudden trade restrictions (e.g. a no-deal Brexit) can significantly reduce the longer-term economic prosperity of affected regions. Analyses of transportation disruptions in typhoon seasons indicate that severely affected regions must reduce production as demand falls during a storm. Substituting suppliers may compensate for fluctuations at the beginning of the storm, which fails for prolonged disruptions.
Third, possible coping mechanisms and adaptation strategies arise from direct and indirect economic responses to weather extremes. Analyzing annual trade changes due to typhoon-induced transport disruptions depict that overall exports rise. This trade resilience increases with higher network node diversification. Further, my research shows that a basic insurance scheme may diminish hurricane-induced long-term growth losses due to faster reconstruction in disasters aftermaths. I find that insurance coverage could be an economically reasonable coping scheme towards higher losses caused by the climate crisis. Indirect effects within the global economic network from weather extremes indicate further adaptation possibilities. For one, diversifying linkages reduce the hazard of sharp price increases. Next to this, close economic interconnections with regions that do not share the same extreme weather season can be economically beneficial in the medium run. Furthermore, economic ripple resonance effects should be considered while computing costs. Overall, an increase in local adaptation measures reduces economic ripples within the trade network and possible losses elsewhere. In conclusion, adaptation measures are necessary and potential present, but it seems rather not possible to avoid all direct or indirect losses.
As I show in this thesis, dynamical modeling gives valuable insights into how direct and indirect economic impacts arise from different categories of weather extremes. Further, it highlights the importance of resolving individual extremes and reflecting amplifying effects caused by incomplete recovery or consecutive disasters.
In this thesis, the dependencies of charge localization and itinerance in two classes of aromatic molecules are accessed: pyridones and porphyrins. The focus lies on the effects of isomerism, complexation, solvation, and optical excitation, which are concomitant with different crucial biological applications of specific members of these groups of compounds. Several porphyrins play key roles in the metabolism of plants and animals. The nucleobases, which store the genetic information in the DNA and RNA are pyridone derivatives. Additionally, a number of vitamins are based on these two groups of substances.
This thesis aims to answer the question of how the electronic structure of these classes of molecules is modified, enabling the versatile natural functionality. The resulting insights into the effect of constitutional and external factors are expected to facilitate the design of new processes for medicine, light-harvesting, catalysis, and environmental remediation.
The common denominator of pyridones and porphyrins is their aromatic character. As aromaticity was an early-on topic in chemical physics, the overview of relevant theoretical models in this work also mirrors the development of this scientific field in the 20th century. The spectroscopic investigation of these compounds has long been centered on their global, optical transition between frontier orbitals.
The utilization and advancement of X-ray spectroscopic methods characterizing the local electronic structure of molecular samples form the core of this thesis. The element selectivity of the near-edge X-ray absorption fine structure (NEXAFS) is employed to probe the unoccupied density of states at the nitrogen site, which is key for the chemical reactivity of pyridones and porphyrins. The results contribute to the growing database of NEXAFS features and their interpretation, e.g., by advancing the debate on the porphyrin N K-edge through systematic experimental and theoretical arguments. Further, a state-of-the-art laser pump – NEXAFS probe scheme is used to characterize the relaxation pathway of a photoexcited porphyrin on the atomic level.
Resonant inelastic X-ray scattering (RIXS) provides complementary results by accessing the highest occupied valence levels including symmetry information. It is shown that RIXS is an effective experimental tool to gain detailed information on charge densities of individual species in tautomeric mixtures. Additionally, the hRIXS and METRIXS high-resolution RIXS spectrometers, which have been in part commissioned in the course of this thesis, will gain access to the ultra-fast and thermal chemistry of pyridones, porphyrins, and many other compounds.
With respect to both classes of bio-inspired aromatic molecules, this thesis establishes that even though pyridones and porphyrins differ largely by their optical absorption bands and hydrogen bonding abilities, they all share a global stabilization of local constitutional changes and relevant external perturbation. It is because of this wide-ranging response that pyridones and porphyrins can be applied in a manifold of biological and technical processes.
Proteine sind an praktisch allen Prozessen in lebenden Zellen maßgeblich beteiligt. Auch in der Biotechnologie werden Proteine in vielfältiger Weise eingesetzt.
Ein Protein besteht aus einer Kette von Aminosäuren. Häufig lagern sich mehrere dieser Ketten zu größeren Strukturen und Funktionseinheiten, sogenannten Proteinkomplexen,
zusammen. Kürzlich wurde gezeigt, dass eine Proteinkomplexbildung bereits während der Biosynthese der Proteine (co-translational) stattfinden kann
und nicht stets erst danach (post-translational) erfolgt. Da Fehlassemblierungen von Proteinen zu Funktionsverlusten und adversen Effekten führen, ist eine präzise und verlässliche Proteinkomplexbildung sowohl für zelluläre Prozesse als auch für biotechnologische Anwendungen essenziell. Mit experimentellen Methoden lassen sich zwar u.a. die Stöchiometrie und die Struktur von Proteinkomplexen bestimmen,
jedoch bisher nicht die Dynamik der Komplexbildung auf unterschiedlichen Zeitskalen. Daher sind grundlegende Mechanismen der Proteinkomplexbildung noch nicht vollständig verstanden. Die hier vorgestellte, auf experimentellen Erkenntnissen aufbauende, computergestützte Modellierung der Proteinkomplexbildung erlaubt eine umfassende Analyse des Einflusses physikalisch-chemischer Parameter
auf den Assemblierungsprozess. Die Modelle bilden möglichst realistisch die experimentellen Systeme der Kooperationspartner (Bar-Ziv, Weizmann-Institut, Israel; Bukau und Kramer, Universität Heidelberg) ab, um damit die Assemblierung von Proteinkomplexen einerseits in einem quasi-zweidimensionalen synthetischen Expressionssystem (in vitro) und andererseits im Bakterium Escherichia coli (in vivo) untersuchen zu können. Mit Hilfe eines vereinfachten Expressionssystems, in dem die Proteine nur an die Chip-Oberfläche, aber nicht aneinander binden können, wird das theoretische Modell parametrisiert. In diesem vereinfachten in-vitro-System durchläuft die Effizienz der Komplexbildung drei Regime – ein bindedominiertes Regime, ein Mischregime und ein produktionsdominiertes Regime. Ihr Maximum erreicht die Effizienz dabei kurz nach dem Übergang vom bindedominierten ins Mischregime und fällt anschließend monoton ab. Sowohl im nicht-vereinfachten in-vitro- als auch im in-vivo-System koexistieren je zwei konkurrierende Assemblierungspfade: Im in-vitro-System erfolgt die Komplexbildung entweder spontan in wässriger Lösung (Lösungsassemblierung) oder aber in einer definierten Schrittfolge an der Chip-Oberfläche (Oberflächenassemblierung); Im in-vivo-System konkurrieren hingegen die co- und die post-translationale Komplexbildung. Es zeigt sich, dass die Dominanz der Assemblierungspfade im in-vitro-System zeitabhängig ist und u.a. durch die Limitierung und Stärke der Bindestellen auf der Chip-Oberfläche beeinflusst werden kann. Im in-vivo-System hat der räumliche Abstand zwischen den Syntheseorten der beiden Proteinkomponenten nur dann einen Einfluss auf die Komplexbildung, wenn die Untereinheiten schnell degradieren. In diesem Fall dominiert die co-translationale Assemblierung auch auf kurzen Zeitskalen deutlich, wohingegen es bei stabilen Untereinheiten zu einem Wechsel von der Dominanz der post- hin zu einer geringen Dominanz der co-translationalen Assemblierung kommt. Mit den in-silico-Modellen lässt sich neben der Dynamik u.a. auch die Lokalisierung der Komplexbildung und -bindung darstellen, was einen Vergleich der theoretischen Vorhersagen mit experimentellen Daten und somit eine Validierung der Modelle ermöglicht. Der hier präsentierte in-silico Ansatz ergänzt die experimentellen Methoden, und erlaubt so, deren Ergebnisse zu interpretieren und neue Erkenntnisse davon abzuleiten.