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Additive manufacturing (AM) processes enable the production of metal structures with exceptional design freedom, of which laser powder bed fusion (PBF-LB) is one of the most common. In this process, a laser melts a bed of loose feedstock powder particles layer-by-layer to build a structure with the desired geometry. During fabrication, the repeated melting and rapid, directional solidification create large temperature gradients that generate large thermal stress. This thermal stress can itself lead to cracking or delamination during fabrication. More often, large residual stresses remain in the final part as a footprint of the thermal stress. This residual stress can cause premature distortion or even failure of the part in service. Hence, knowledge of the residual stress field is critical for both process optimization and structural integrity.
Diffraction-based techniques allow the non-destructive characterization of the residual stress fields. However, such methods require a good knowledge of the material of interest, as certain assumptions must be made to accurately determine residual stress. First, the measured lattice plane spacings must be converted to lattice strains with the knowledge of a strain-free material state. Second, the measured lattice strains must be related to the macroscopic stress using Hooke's law, which requires knowledge of the stiffness of the material. Since most crystal structures exhibit anisotropic material behavior, the elastic behavior is specific to each lattice plane of the single crystal. Thus, the use of individual lattice planes in monochromatic diffraction residual stress analysis requires knowledge of the lattice plane-specific elastic properties. In addition, knowledge of the microstructure of the material is required for a reliable assessment of residual stress.
This work presents a toolbox for reliable diffraction-based residual stress analysis. This is presented for a nickel-based superalloy produced by PBF-LB. First, this work reviews the existing literature in the field of residual stress analysis of laser-based AM using diffraction-based techniques. Second, the elastic and plastic anisotropy of the nickel-based superalloy Inconel 718 produced by PBF-LB is studied using in situ energy dispersive synchrotron X-ray and neutron diffraction techniques. These experiments are complemented by ex situ material characterization techniques. These methods establish the relationship between the microstructure and texture of the material and its elastic and plastic anisotropy. Finally, surface, sub-surface, and bulk residual stress are determined using a texture-based approach. Uncertainties of different methods for obtaining stress-free reference values are discussed.
The tensile behavior in the as-built condition is shown to be controlled by texture and cellular sub-grain structure, while in the heat-treated condition the precipitation of strengthening phases and grain morphology dictate the behavior. In fact, the results of this thesis show that the diffraction elastic constants depend on the underlying microstructure, including texture and grain morphology. For columnar microstructures in both as-built and heat-treated conditions, the diffraction elastic constants are best described by the Reuss iso-stress model. Furthermore, the low accumulation of intergranular strains during deformation demonstrates the robustness of using the 311 reflection for the diffraction-based residual stress analysis with columnar textured microstructures. The differences between texture-based and quasi-isotropic approaches for the residual stress analysis are shown to be insignificant in the observed case. However, the analysis of the sub-surface residual stress distributions show, that different scanning strategies result in a change in the orientation of the residual stress tensor. Furthermore, the location of the critical sub-surface tensile residual stress is related to the surface roughness and the microstructure. Finally, recommendations are given for the diffraction-based determination and evaluation of residual stress in textured additively manufactured alloys.
Organic solar cells (OSCs) represent a new generation of solar cells with a range of captivating attributes including low-cost, light-weight, aesthetically pleasing appearance, and flexibility. Different from traditional silicon solar cells, the photon-electron conversion in OSCs is usually accomplished in an active layer formed by blending two kinds of organic molecules (donor and acceptor) with different energy levels together.
The first part of this thesis focuses on a better understanding of the role of the energetic offset and each recombination channel on the performance of these low-offset OSCs. By combining advanced experimental techniques with optical and electrical simulation, the energetic offsets between CT and excitons, several important insights were achieved: 1. The short circuit current density and fill-factor of low-offset systems are largely determined by field-dependent charge generation in such low-offset OSCs. Interestingly, it is strongly evident that such field-dependent charge generation originates from a field-dependent exciton dissociation yield. 2. The reduced energetic offset was found to be accompanied by strongly enhanced bimolecular recombination coefficient, which cannot be explained solely by exciton repopulation from CT states. This implies the existence of another dark decay channel apart from CT.
The second focus of the thesis was on the technical perspective. In this thesis, the influence of optical artifacts in differential absorption spectroscopy upon the change of sample configuration and active layer thickness was studied. It is exemplified and discussed thoroughly and systematically in terms of optical simulations and experiments, how optical artifacts originated from non-uniform carrier profile and interference can manipulate not only the measured spectra, but also the decay dynamics in various measurement conditions. In the end of this study, a generalized methodology based on an inverse optical transfer matrix formalism was provided to correct the spectra and decay dynamics manipulated by optical artifacts.
Overall, this thesis paves the way for a deeper understanding of the keys toward higher PCEs in low-offset OSC devices, from the perspectives of both device physics and characterization techniques.
The increasing number of known exoplanets raises questions about their demographics and the mechanisms that shape planets into how we observe them today. Young planets in close-in orbits are exposed to harsh environments due to the host star being magnetically highly active, which results in high X-ray and extreme UV fluxes impinging on the planet. Prolonged exposure to this intense photoionizing radiation can cause planetary atmospheres to heat up, expand and escape into space via a hydrodynamic escape process known as photoevaporation. For super-Earth and sub-Neptune-type planets, this can even lead to the complete erosion of their primordial gaseous atmospheres. A factor of interest for this particular mass-loss process is the activity evolution of the host star. Stellar rotation, which drives the dynamo and with it the magnetic activity of a star, changes significantly over the stellar lifetime. This strongly affects the amount of high-energy radiation received by a planet as stars age. At a young age, planets still host warm and extended envelopes, making them particularly susceptible to atmospheric evaporation. Especially in the first gigayear, when X-ray and UV levels can be 100 - 10,000 times higher than for the present-day sun, the characteristics of the host star and the detailed evolution of its high-energy emission are of importance.
In this thesis, I study the impact of stellar activity evolution on the high-energy-induced atmospheric mass loss of young exoplanets. The PLATYPOS code was developed as part of this thesis to calculate photoevaporative mass-loss rates over time. The code, which couples parameterized planetary mass-radius relations with an analytical hydrodynamic escape model, was used, together with Chandra and eROSITA X-ray observations, to investigate the future mass loss of the two young multiplanet systems V1298 Tau and K2-198. Further, in a numerical ensemble study, the effect of a realistic spread of activity tracks on the small-planet radius gap was investigated for the first time. The works in this thesis show that for individual systems, in particular if planetary masses are unconstrained, the difference between a young host star following a low-activity track vs. a high-activity one can have major implications: the exact shape of the activity evolution can determine whether a planet can hold on to some of its atmosphere, or completely loses its envelope, leaving only the bare rocky core behind. For an ensemble of simulated planets, an observationally-motivated distribution of activity tracks does not substantially change the final radius distribution at ages of several gigayears. My simulations indicate that the overall shape and slope of the resulting small-planet radius gap is not significantly affected by the spread in stellar activity tracks. However, it can account for a certain scattering or fuzziness observed in and around the radius gap of the observed exoplanet population.
Organic-inorganic hybrids based on P3HT and mesoporous silicon for thermoelectric applications
(2024)
This thesis presents a comprehensive study on synthesis, structure and thermoelectric transport properties of organic-inorganic hybrids based on P3HT and porous silicon. The effect of embedding polymer in silicon pores on the electrical and thermal transport is studied. Morphological studies confirm successful polymer infiltration and diffusion doping with roughly 50% of the pore space occupied by conjugated polymer. Synchrotron diffraction experiments reveal no specific ordering of the polymer inside the pores. P3HT-pSi hybrids show improved electrical transport by five orders of magnitude compared to porous silicon and power factor values comparable or exceeding other P3HT-inorganic hybrids. The analysis suggests different transport mechanisms in both materials. In pSi, the transport mechanism relates to a Meyer-Neldel compansation rule. The analysis of hybrids' data using the power law in Kang-Snyder model suggests that a doped polymer mainly provides charge carriers to the pSi matrix, similar to the behavior of a doped semiconductor. Heavily suppressed thermal transport in porous silicon is treated with a modified Landauer/Lundstrom model and effective medium theories, which reveal that pSi agrees well with the Kirkpatrick model with a 68% percolation threshold. Thermal conductivities of hybrids show an increase compared to the empty pSi but the overall thermoelectric figure of merit ZT of P3HT-pSi hybrid exceeds both pSi and P3HT as well as bulk Si.
Actin is one of the most highly conserved proteins in eukaryotes and distinct actin-related proteins with filament-forming properties are even found in prokaryotes. Due to these commonalities, actin-modulating proteins of many species share similar structural properties and proposed functions. The polymerization and depolymerization of actin are critical processes for a cell as they can contribute to shape changes to adapt to its environment and to move and distribute nutrients and cellular components within the cell. However, to what extent functions of actin-binding proteins are conserved between distantly related species, has only been addressed in a few cases. In this work, functions of Coronin-A (CorA) and Actin-interacting protein 1 (Aip1), two proteins involved in actin dynamics, were characterized. In addition, the interchangeability and function of Aip1 were investigated in two phylogenetically distant model organisms. The flowering plant Arabidopsis thaliana (encoding two homologs, AIP1-1 and AIP1-2) and in the amoeba Dictyostelium discoideum (encoding one homolog, DdAip1) were chosen because the functions of their actin cytoskeletons may differ in many aspects. Functional analyses between species were conducted for AIP1 homologs as flowering plants do not harbor a CorA gene.
In the first part of the study, the effect of four different mutation methods on the function of Coronin-A protein and the resulting phenotype in D. discoideum was revealed in two genetic knockouts, one RNAi knockdown and a sudden loss-of-function mutant created by chemical-induced dislocation (CID). The advantages and disadvantages of the different mutation methods on the motility, appearance and development of the amoebae were investigated, and the results showed that not all observed properties were affected with the same intensity. Remarkably, a new combination of Selection-Linked Integration and CID could be established.
In the second and third parts of the thesis, the exchange of Aip1 between plant and amoeba was carried out. For A. thaliana, the two homologs (AIP1-1 and AIP1-2) were analyzed for functionality as well as in D. discoideum. In the Aip1-deficient amoeba, rescue with AIP1-1 was more effective than with AIP1-2. The main results in the plant showed that in the aip1-2 mutant background, reintroduced AIP1-2 displayed the most efficient rescue and A. thaliana AIP1-1 rescued better than DdAip1. The choice of the tagging site was important for the function of Aip1 as steric hindrance is a problem. The DdAip1 was less effective when tagged at the C-terminus, while the plant AIP1s showed mixed results depending on the tag position. In conclusion, the foreign proteins partially rescued phenotypes of mutant plants and mutant amoebae, despite the organisms only being very distantly related in evolutionary terms.
The icosahedral non-hydrostatic large eddy model (ICON-LEM) was applied around the drift track of the Multidisciplinary Observatory Study of the Arctic (MOSAiC) in 2019 and 2020. The model was set up with horizontal grid-scales between 100m and 800m on areas with radii of 17.5km and 140 km. At its lateral boundaries, the model was driven by analysis data from the German Weather Service (DWD), downscaled by ICON in limited area mode (ICON-LAM) with horizontal grid-scale of 3 km.
The aim of this thesis was the investigation of the atmospheric boundary layer near the surface in the central Arctic during polar winter with a high-resolution mesoscale model. The default settings in ICON-LEM prevent the model from representing the exchange processes in the Arctic boundary layer in accordance to the MOSAiC observations. The implemented sea-ice scheme in ICON does not include a snow layer on sea-ice, which causes a too slow response of the sea-ice surface temperature to atmospheric changes. To allow the sea-ice surface to respond faster to changes in the atmosphere, the implemented sea-ice parameterization in ICON was extended with an adapted heat capacity term.
The adapted sea-ice parameterization resulted in better agreement with the MOSAiC observations. However, the sea-ice surface temperature in the model is generally lower than observed due to biases in the downwelling long-wave radiation and the lack of complex surface structures, like leads. The large eddy resolving turbulence closure yielded a better representation of the lower boundary layer under strongly stable stratification than the non-eddy-resolving turbulence closure. Furthermore, the integration of leads into the sea-ice surface reduced the overestimation of the sensible heat flux for different weather conditions.
The results of this work help to better understand boundary layer processes in the central Arctic during the polar night. High-resolving mesoscale simulations are able to represent temporally and spatially small interactions and help to further develop parameterizations also for the application in regional and global models.
The origin and structure of magnetic fields in the Galaxy are largely unknown. What is known is that they are essential for several astrophysical processes, in particular the propagation of cosmic rays. Our ability to describe the propagation of cosmic rays through the Galaxy is severely limited by the lack of observational data needed to probe the structure of the Galactic magnetic field on many different length scales. This is particularly true for modelling the propagation of cosmic rays into the Galactic halo, where our knowledge of the magnetic field is particularly poor.
In the last decade, observations of the Galactic halo in different frequency regimes have revealed the existence of out-of-plane bubble emission in the Galactic halo. In gamma rays these bubbles have been termed Fermi bubbles with a radial extent of ≈ 3 kpc and an azimuthal height of ≈ 6 kpc. The radio counterparts of the Fermi bubbles were seen by both the S-PASS telescopes and the Planck satellite, and showed a clear spatial overlap. The X-ray counterparts of the Fermi bubbles were named eROSITA bubbles after the eROSITA satellite, with a radial width of ≈ 7 kpc and an azimuthal height of ≈ 14 kpc. Taken together, these observations suggest the presence of large extended Galactic Halo Bubbles (GHB) and have stimulated interest in exploring the less explored Galactic halo.
In this thesis, a new toy model (GHB model) for the magnetic field and non-thermal electron distribution in the Galactic halo has been proposed. The new toy model has been used to produce polarised synchrotron emission sky maps. Chi-square analysis was used to compare the synthetic skymaps with the Planck 30 GHz polarised skymaps. The obtained constraints on the strength and azimuthal height were found to be in agreement with the S-PASS radio observations.
The upper, lower and best-fit values obtained from the above chi-squared analysis were used to generate three separate toy models. These three models were used to propagate ultra-high energy cosmic rays. This study was carried out for two potential sources, Centaurus A and NGC 253, to produce magnification maps and arrival direction skymaps. The simulated arrival direction skymaps were found to be consistent with the hotspots of Centaurus A and NGC 253 as seen in the observed arrival direction skymaps provided by the Pierre Auger Observatory (PAO).
The turbulent magnetic field component of the GHB model was also used to investigate the extragalactic dipole suppression seen by PAO. UHECRs with an extragalactic dipole were forward-tracked through the turbulent GHB model at different field strengths. The suppression in the dipole due to the varying diffusion coefficient from the simulations was noted. The results could also be compared with an analytical analogy of electrostatics. The simulations of the extragalactic dipole suppression were in agreement with similar studies carried out for galactic cosmic rays.
Relativistic pair beams produced in the cosmic voids by TeV gamma rays from blazars are expected to produce a detectable GeV-scale cascade emission missing in the observations. The suppression of this secondary cascade implies either the deflection of the pair beam by intergalactic magnetic fields (IGMFs) or an energy loss of the beam due to the electrostatic beam-plasma instability. IGMF of femto-Gauss strength is sufficient to significantly deflect the pair beams reducing the flux of secondary cascade below the observational limits. A similar flux reduction may result in the absence of the IGMF from the beam energy loss by the instability before the inverse Compton cooling. This dissertation consists of two studies about the instability role in the evolution of blazar-induced beams.
Firstly, we investigated the effect of sub-fG level IGMF on the beam energy loss by the instability. Considering IGMF with correlation lengths smaller than a few kpc, we found that such fields increase the transverse momentum of the pair beam particles, dramatically reducing the linear growth rate of the electrostatic instability and hence the energy-loss rate of the pair beam. Our results show that the IGMF eliminates beam plasma instability as an effective energy-loss agent at a field strength three orders of magnitude below that needed to suppress the secondary cascade emission by magnetic deflection. For intermediate-strength IGMF, we do not know a viable process to explain the observed absence of GeV-scale cascade emission and hence can be excluded.
Secondly, we probed how the beam-plasma instability feeds back on the beam, using a realistic two-dimensional beam distribution. We found that the instability broadens the beam opening angles significantly without any significant energy loss, thus confirming a recent feedback study on a simplified one-dimensional beam distribution. However, narrowing diffusion feedback of the beam particles with Lorentz factors less than 1e6 might become relevant even though initially it is negligible. Finally, when considering the continuous creation of TeV pairs, we found that the beam distribution and the wave spectrum reach a new quasi-steady state, in which the scattering of beam particles persists and the beam opening angle may increase by a factor of hundreds. This new intrinsic scattering of the cascade can result in time delays of around ten years, thus potentially mimicking the IGMF deflection. Understanding the implications on the GeV cascade emission requires accounting for inverse Compton cooling and simulating the beam-plasma system at different points in the IGM.
The Arctic is the hot spot of the ongoing, global climate change. Over the last decades, near-surface temperatures in the Arctic have been rising almost four times faster than on global average. This amplified warming of the Arctic and the associated rapid changes of its environment are largely influenced by interactions between individual components of the Arctic climate system. On daily to weekly time scales, storms can have major impacts on the Arctic sea-ice cover and are thus an important part of these interactions within the Arctic climate. The sea-ice impacts of storms are related to high wind speeds, which enhance the drift and deformation of sea ice, as well as to changes in the surface energy budget in association with air mass advection, which impact the seasonal sea-ice growth and melt.
The occurrence of storms in the Arctic is typically associated with the passage of transient cyclones. Even though the above described mechanisms how storms/cyclones impact the Arctic sea ice are in principal known, there is a lack of statistical quantification of these effects. In accordance with that, the overarching objective of this thesis is to statistically quantify cyclone impacts on sea-ice concentration (SIC) in the Atlantic Arctic Ocean over the last four decades. In order to further advance the understanding of the related mechanisms, an additional objective is to separate dynamic and thermodynamic cyclone impacts on sea ice and assess their relative importance. Finally, this thesis aims to quantify recent changes in cyclone impacts on SIC. These research objectives are tackled utilizing various data sets, including atmospheric and oceanic reanalysis data as well as a coupled model simulation and a cyclone tracking algorithm.
Results from this thesis demonstrate that cyclones are significantly impacting SIC in the Atlantic Arctic Ocean from autumn to spring, while there are mostly no significant impacts in summer. The strength and the sign (SIC decreasing or SIC increasing) of the cyclone impacts strongly depends on the considered daily time scale and the region of the Atlantic Arctic Ocean. Specifically, an initial decrease in SIC (day -3 to day 0 relative to the cyclone) is found in the Greenland, Barents and Kara Seas, while SIC increases following cyclones (day 0 to day 5 relative to the cyclone) are mostly limited to the Barents and Kara Seas.
For the cold season, this results in a pronounced regional difference between overall (day -3 to day 5 relative to the cyclone) SIC-decreasing cyclone impacts in the Greenland Sea and overall SIC-increasing cyclone impacts in the Barents and Kara Seas. A cyclone case study based on a coupled model simulation indicates that both dynamic and thermodynamic mechanisms contribute to cyclone impacts on sea ice in winter. A typical pattern consisting of an initial dominance of dynamic sea-ice changes followed by enhanced thermodynamic ice growth after the cyclone passage was found. This enhanced ice growth after the cyclone passage most likely also explains the (statistical) overall SIC-increasing effects of cyclones in the Barents and Kara Seas in the cold season.
Significant changes in cyclone impacts on SIC over the last four decades have emerged throughout the year. These recent changes are strongly varying from region to region and month to month. The strongest trends in cyclone impacts on SIC are found in autumn in the Barents and Kara Seas. Here, the magnitude of destructive cyclone impacts on SIC has approximately doubled over the last four decades. The SIC-increasing effects following the cyclone passage have particularly weakened in the Barents Sea in autumn. As a consequence, previously existing overall SIC-increasing cyclone impacts in this region in autumn have recently disappeared. Generally, results from this thesis show that changes in the state of the sea-ice cover (decrease in mean sea-ice concentration and thickness) and near-surface air temperature are most important for changed cyclone impacts on SIC, while changes in cyclone properties (i.e. intensity) do not play a significant role.
The central gas in half of all galaxy clusters shows short cooling times. Assuming unimpeded cooling, this should lead to high star formation and mass cooling rates, which are not observed. Instead, it is believed that condensing gas is accreted by the central black hole that powers an active galactic nuclei jet, which heats the cluster. The detailed heating mechanism remains uncertain. A promising mechanism invokes cosmic ray protons that scatter on self-generated magnetic fluctuations, i.e. Alfvén waves. Continuous damping of Alfvén waves provides heat to the intracluster medium. Previous work has found steady state solutions for a large sample of clusters where cooling is balanced by Alfvénic wave heating. To verify modeling assumptions, we set out to study cosmic ray injection in three-dimensional magnetohydrodynamical simulations of jet feedback in an idealized cluster with the moving-mesh code arepo. We analyze the interaction of jet-inflated bubbles with the turbulent magnetized intracluster medium.
Furthermore, jet dynamics and heating are closely linked to the largely unconstrained jet composition. Interactions of electrons with photons of the cosmic microwave background result in observational signatures that depend on the bubble content. Those recent observations provided evidence for underdense bubbles with a relativistic filling while adopting simplifying modeling assumptions for the bubbles. By reproducing the observations with our simulations, we confirm the validity of their modeling assumptions and as such, confirm the important finding of low-(momentum) density jets.
In addition, the velocity and magnetic field structure of the intracluster medium have profound consequences for bubble evolution and heating processes. As velocity and magnetic fields are physically coupled, we demonstrate that numerical simulations can help link and thereby constrain their respective observables. Finally, we implement the currently preferred accretion model, cold accretion, into the moving-mesh code arepo and study feedback by light jets in a radiatively cooling magnetized cluster. While self-regulation is attained independently of accretion model, jet density and feedback efficiencies, we find that in order to reproduce observed cold gas morphology light jets are preferred.
In recent decades, astronomy has seen a boom in large-scale stellar surveys of the Galaxy. The detailed information obtained about millions of individual stars in the Milky Way is bringing us a step closer to answering one of the most outstanding questions in astrophysics: how do galaxies form and evolve? The Milky Way is the only galaxy where we can dissect many stars into their high-dimensional chemical composition and complete phase space, which analogously as fossil records can unveil the past history of the genesis of the Galaxy. The processes that lead to large structure formation, such as the Milky Way, are critical for constraining cosmological models; we call this line of study Galactic archaeology or near-field cosmology.
At the core of this work, we present a collection of efforts to chemically and dynamically characterise the disks and bulge of our Galaxy. The results we present in this thesis have only been possible thanks to the advent of the Gaia astrometric satellite, which has revolutionised the field of Galactic archaeology by precisely measuring the positions, parallax distances and motions of more than a billion stars. Another, though not less important, breakthrough is the APOGEE survey, which has observed spectra in the near-infrared peering into the dusty regions of the Galaxy, allowing us to determine detailed chemical abundance patterns in hundreds of thousands of stars. To accurately depict the Milky Way structure, we use and develop the Bayesian isochrone fitting tool/code called StarHorse; this software can predict stellar distances, extinctions and ages by combining astrometry, photometry and spectroscopy based on stellar evolutionary models. The StarHorse code is pivotal to calculating distances where Gaia parallaxes alone cannot allow accurate estimates.
We show that by combining Gaia, APOGEE, photometric surveys and using StarHorse, we can produce a chemical cartography of the Milky way disks from their outermost to innermost parts. Such a map is unprecedented in the inner Galaxy. It reveals a continuity of the bimodal chemical pattern previously detected in the solar neighbourhood, indicating two populations with distinct formation histories. Furthermore, the data reveals a chemical gradient within the thin disk where the content of 𝛼-process elements and metals is higher towards the centre. Focusing on a sample in the inner MW we confirm the extension of the chemical duality to the innermost regions of the Galaxy. We find stars with bar shape orbits to show both high- and low-𝛼 abundances, suggesting the bar formed by secular evolution trapping stars that already existed. By analysing the chemical orbital space of the inner Galactic regions, we disentangle the multiple populations that inhabit this complex region. We reveal the presence of the thin disk, thick disk, bar, and a counter-rotating population, which resembles the outcome of a perturbed proto-Galactic disk. Our study also finds that the inner Galaxy holds a high quantity of super metal-rich stars up to three times solar suggesting it is a possible repository of old super-metal-rich stars found in the solar neighbourhood.
We also enter into the complicated task of deriving individual stellar ages. With StarHorse, we calculate the ages of main-sequence turn-off and sub-giant stars for several public spectroscopic surveys. We validate our results by investigating linear relations between chemical abundances and time since the 𝛼 and neutron capture elements are sensitive to age as a reflection of the different enrichment timescales of these elements. For further study of the disks in the solar neighbourhood, we use an unsupervised machine learning algorithm to delineate a multidimensional separation of chrono-chemical stellar groups revealing the chemical thick disk, the thin disk, and young 𝛼-rich stars. The thick disk is shown to have a small age dispersion indicating its fast formation contrary to the thin disk that spans a wide range of ages.
With groundbreaking data, this thesis encloses a detailed chemo-dynamical view of the disk and bulge of our Galaxy. Our findings on the Milky Way can be linked to the evolution of high redshift disk galaxies, helping to solve the conundrum of galaxy formation.
Cosmic rays (CRs) constitute an important component of the interstellar medium (ISM) of galaxies and are thought to play an essential role in governing their evolution. In particular, they are able to impact the dynamics of a galaxy by driving galactic outflows or heating the ISM and thereby affecting the efficiency of star-formation. Hence, in order to understand galaxy formation and evolution, we need to accurately model this non-thermal constituent of the ISM. But except in our local environment within the Milky Way, we do not have the ability to measure CRs directly in other galaxies. However, there are many ways to indirectly observe CRs via the radiation they emit due to their interaction with magnetic and interstellar radiation fields as well as with the ISM.
In this work, I develop a numerical framework to calculate the spectral distribution of CRs in simulations of isolated galaxies where a steady-state between injection and cooling is assumed. Furthermore, I calculate the non-thermal emission processes arising from the modelled CR proton and electron spectra ranging from radio wavelengths up to the very high-energy gamma-ray regime.
I apply this code to a number of high-resolution magneto-hydrodynamical (MHD) simulations of isolated galaxies, where CRs are included. This allows me to study their CR spectra and compare them to observations of the CR proton and electron spectra by the Voyager-1 satellite and the AMS-02 instrument in order to reveal the origin of the measured spectral features.
Furthermore, I provide detailed emission maps, luminosities and spectra of the non-thermal emission from our simulated galaxies that range from dwarfs to Milk-Way analogues to starburst galaxies at different evolutionary stages. I successfully reproduce the observed relations between the radio and gamma-ray luminosities with the far-infrared (FIR) emission of star-forming (SF) galaxies, respectively, where the latter is a good tracer of the star-formation rate. I find that highly SF galaxies are close to the limit where their CR population would lose all of their energy due to the emission of radiation, whereas CRs tend to escape low SF galaxies more quickly. On top of that, I investigate the properties of CR transport that are needed in order to match the observed gamma-ray spectra.
Furthermore, I uncover the underlying processes that enable the FIR-radio correlation (FRC) to be maintained even in starburst galaxies and find that thermal free-free-emission naturally explains the observed radio spectra in SF galaxies like M82 and NGC 253 thus solving the riddle of flat radio spectra that have been proposed to contradict the observed tight FRC.
Lastly, I scrutinise the steady-state modelling of the CR proton component by investigating for the first time the influence of spectrally resolved CR transport in MHD simulations on the hadronic gamma-ray emission of SF galaxies revealing new insights into the observational signatures of CR transport both spectrally and spatially.
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.
Using time-resolved x-ray diffraction, we demonstrate the manipulation of the picosecond strain response of a metallic heterostructure consisting of a dysprosium (Dy) transducer and a niobium (Nb) detection layer by an external magnetic field. We utilize the first-order ferromagnetic–antiferromagnetic phase transition of the Dy layer, which provides an additional large contractive stress upon laser excitation compared to its zerofield response. This enhances the laser-induced contraction of the transducer and changes the shape of the picosecond strain pulses driven in Dy and detected within the buried Nb layer. Based on our experiment with rare-earth metals we discuss required properties for functional transducers, which may allow for novel field-control of the emitted picosecond strain pulses.
With the implementation of intense, short pulsed light sources throughout the last years, the powerful technique of resonant inelastic X-ray scattering (RIXS) became feasible for a wide range of experiments within femtosecond dynamics in correlated materials and molecules.
In this thesis I investigate the potential to bring RIXS into the fluence regime of nonlinear X-ray-matter interactions, especially focusing on the impact of stimulated scattering on RIXS in transition metal systems in a transmission spectroscopy geometry around transition metal L-edges.
After presenting the RIXS toolbox and the capabilities of free electron laser light sources for ultrafast intense X-ray experiments, the thesis explores an experiment designed to understand the impact of stimulated scattering on diffraction and direct beam transmission spectroscopy on a CoPd multilayer system. The experiments require short X-ray pulses that can only be generated at free electron lasers (FEL). Here the pulses are not only short, but also very intense, which opens the door to nonlinear X-ray-matter interactions. In the second part of this thesis, we investigate observations in the nonlinear interaction regime, look at potential difficulties for classic spectroscopy and investigate possibilities to enhance the RIXS through stimulated scattering. Here, a study on stimulated RIXS is presented, where we investigate the light field intensity dependent CoPd demagnetization in transmission as well as scattering geometry. Thereby we show the first direct observation of stimulated RIXS as well as light field induced nonlinear effects,
namely the breakdown of scattering intensity and the increase in sample transmittance. The topic is of ongoing interest and will just increase in relevance as more free electron lasers are planned and the number of experiments at such light sources will continue to increase in the near future.
Finally we present a discussion on the accessibility of small DOS shifts in the absorption-band of transition metal complexes through stimulated resonant X-ray scattering. As these shifts occur for example in surface states this finding could expand the experimental selectivity of NEXAFS and RIXS to the detectability of surface states. We show how stimulation can indeed enhance the visibility of DOS shifts through the detection of stimulated spectral shifts and enhancements in this theoretical study. We also forecast the observation of stimulated enhancements in resonant excitation experiments at FEL sources in systems with a high density of states just below the Fermi edge and in systems with an occupied to unoccupied DOS ratio in the valence band above 1.
In X-ray computed tomography (XCT), an X-ray beam of intensity I0 is transmitted through an object and its attenuated intensity I is measured when it exits the object. The attenuation of the beam depends on the attenuation coefficients along its path. The attenuation coefficients provide information about the structure and composition of the object and can be determined through mathematical operations that are referred to as reconstruction.
The standard reconstruction algorithms are based on the filtered backprojection (FBP) of the measured data. While these algorithms are fast and relatively simple, they do not always succeed in computing a precise reconstruction, especially from under-sampled data.
Alternatively, an image or volume can be reconstructed by solving a system of linear equations. Typically, the system of equations is too large to be solved but its solution can be approximated by iterative methods, such as the Simultaneous Iterative Reconstruction Technique (SIRT) and the Conjugate Gradient Least Squares (CGLS).
This dissertation focuses on the development of a novel iterative algorithm, the Direct Iterative Reconstruction of Computed Tomography Trajectories (DIRECTT). After its reconstruction principle is explained, its performance is assessed for real parallel- and cone-beam CT (including under-sampled) data and compared to that of other established algorithms. Finally, it is demonstrated how the shape of the measured object can be modelled into DIRECTT to achieve even better reconstruction results.
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.
Control over spin and electronic structure of MoS₂ monolayer via interactions with substrates
(2023)
The molybdenum disulfide (MoS2) monolayer is a semiconductor with a direct bandgap while it is a robust and affordable material.
It is a candidate for applications in optoelectronics and field-effect transistors.
MoS2 features a strong spin-orbit coupling which makes its spin structure promising for acquiring the Kane-Mele topological concept with corresponding applications in spintronics and valleytronics.
From the optical point of view, the MoS2 monolayer features two valleys in the regions of K and K' points. These valleys are differentiated by opposite spins and a related valley-selective circular dichroism.
In this study we aim to manipulate the MoS2 monolayer spin structure in the vicinity of the K and K' points to explore the possibility of getting control over the optical and electronic properties.
We focus on two different substrates to demonstrate two distinct routes: a gold substrate to introduce a Rashba effect and a graphene/cobalt substrate to introduce a magnetic proximity effect in MoS2.
The Rashba effect is proportional to the out-of-plane projection of the electric field gradient. Such a strong change of the electric field occurs at the surfaces of a high atomic number materials and effectively influence conduction electrons as an in-plane magnetic field. A molybdenum and a sulfur are relatively light atoms, thus, similar to many other 2D materials, intrinsic Rashba effect in MoS2 monolayer is vanishing small. However, proximity of a high atomic number substrate may enhance Rashba effect in a 2D material as it was demonstrated for graphene previously.
Another way to modify the spin structure is to apply an external magnetic field of high magnitude (several Tesla), and cause a Zeeman splitting, the conduction electrons.
However, a similar effect can be reached via magnetic proximity which allows us to reduce external magnetic fields significantly or even to zero. The graphene on cobalt interface is ferromagnetic and stable for MoS2 monolayer synthesis. Cobalt is not the strongest magnet; therefore, stronger magnets may lead to more significant results.
Nowadays most experimental studies on the dichalcogenides (MoS2 included) are performed on encapsulated heterostructures that are produced by mechanical exfoliation.
While mechanical exfoliation (or scotch-tape method) allows to produce a huge variety of structures, the shape and the size of the samples as well as distance between layers in heterostructures are impossible to control reproducibly.
In our study we used molecular beam epitaxy (MBE) methods to synthesise both MoS2/Au(111) and MoS2/graphene/Co systems.
We chose to use MBE, as it is a scalable and reproducible approach, so later industry may adapt it and take over.
We used graphene/cobalt instead of just a cobalt substrate because direct contact of MoS2\ monolayer and a metallic substrate may lead to photoluminescence (PL) quenching in the metallic substrate. Graphene and hexagonal boron nitride monolayer are considered building blocks of a new generation of electronics also commonly used as encapsulating materials for PL studies. Moreover graphene is proved to be a suitable substrate for the MBE growth of transitional metal dichalcogenides (TMDCs).
In chapter 1,
we start with an introduction to TMDCs. Then we focus on MoS2 monolayer state of the art research in the fields of application scenario; synthesis approaches; electronic, spin, and optical properties; and interactions with magnetic fields and magnetic materials.
We briefly touch the basics of magnetism in solids and move on to discuss various magnetic exchange interactions and magnetic proximity effect.
Then we describe MoS2 optical properties in more detail. We start from basic exciton physics and its manifestation in the MoS2 monolayer. We consider optical selection rules in the MoS2 monolayer and such properties as chirality, spin-valley locking, and coexistence of bright and dark excitons.
Chapter 2 contains an overview of the employed surface science methods: angle-integrated, angle-resolved, and spin-resolved photoemission; low energy electron diffraction and scanning tunneling microscopy.
In chapter 3, we describe MoS2 monolayer synthesis details for two substrates: gold monocrystal with (111) surface and graphene on cobalt thin film with Co(111) surface orientation.
The synthesis descriptions are followed by a detailed characterisation of the obtained structures: fingerprints of MoS2 monolayer formation; MoS2 monolayer symmetry and its relation to the substrate below; characterisation of MoS2 monolayer coverage, domain distribution, sizes and shapes, and moire structures.
In chapter~4, we start our discussion with MoS2/Au(111) electronic and spin structure. Combining density functional theory computations (DFT) and spin-resolved photoemission studies, we demonstrate that the MoS2 monolayer band structure features an in-plane Rashba spin splitting. This confirms the possibility of MoS2 monolayer spin structure manipulation via a substrate.
Then we investigate the influence of a magnetic proximity in the MoS2/graphene/Co system on the MoS2 monolayer spin structure.
We focus our investigation on MoS2 high symmetry points: G and K.
First, using spin-resolved measurements, we confirm that electronic states are spin-split at the G point via a magnetic proximity effect. Second, combining spin-resolved measurements and DFT computations for MoS2 monolayer in the K point region, we demonstrate the appearance of a small in-plane spin polarisation in the valence band top and predict a full in-plane spin polarisation for the conduction band bottom.
We move forward discussing how these findings are related to the MoS2 monolayer optical properties, in particular the possibility of dark exciton observation. Additionally, we speculate on the control of the MoS2 valley energy via magnetic proximity from cobalt.
As graphene is spatially buffering the MoS2 monolayer from the Co thin film, we speculate on the role of graphene in the magnetic proximity transfer by replacing graphene with vacuum and other 2D materials in our computations.
We finish our discussion by investigating the K-doped MoS2/graphene/Co system and the influence of this doping on the electronic and spin structure as well as on the magnetic proximity effect.
In summary, using a scalable MBE approach we synthesised
MoS2/Au(111) and MoS2/graphene/Co systems. We found a Rashba effect taking place in MoS2/Au(111) which proves that the MoS2 monolayer in-plane spin structure can be modified. In MoS2/graphene/Co the in-plane magnetic proximity effect indeed takes place which rises the possibility of fine tuning the MoS2 optical properties via manipulation of the the substrate magnetisation.
Planets outside our solar system, so-called "exoplanets", can be detected with different methods, and currently more than 5000 exoplanets have been confirmed, according to NASA Exoplanet Archive. One major highlight of the studies on exoplanets in the past twenty years is the characterization of their atmospheres usingtransmission spectroscopy as the exoplanet transits. However, this characterization is a challenging process and sometimes there are reported discrepancies in the literature regarding the atmosphere of the same exoplanet. One potential reason for the observed atmospheric inconsistencies is called impact parameter degeneracy, and it is highly driven by the limb darkening effect of the host star. A brief introductionto those topics in presented in chapter 1, while the motivation and objectives of thiswork are described in chapter 2.The first goal is to clarify the origin of the transmission spectrum, which is anindicator of an exoplanet’s atmosphere; whether it is real or influenced by the impactparameter degeneracy. A second goal is to determine whether photometry from space using the Transiting Exoplanet Survey Satellite (TESS), could improve on the major parameters, which are responsible for the aforementioned degeneracy, of known exoplanetary systems. Three individual projects were conducted in order toaddress those goals. The three manuscripts are presented, in short, in the manuscriptoverview in chapter 3.More specifically, in chapter 4, the first manuscript is presented, which is an ex-tended investigation on the impact parameter degeneracy and its application onsynthetic transmission spectra. Evidently, the limb darkening of the host star isan important driver for this effect. It keeps the degeneracy persisting through different groups of exoplanets, based on the uncertainty of their impact parameter and on the type of their host star. The second goal, was addressed in the second and third manuscripts (chapter 5 and chapter 6 respectively). Using observationsfrom the TESS mission, two samples of exoplanets were studied; 10 transiting inflated hot-Jupiters and 43 transiting grazing systems. Potentially, the refinement or confirmation of their major system parameters’ measurements can assist in solving current or future discrepancies regarding their atmospheric characterization.In chapter 7 the conclusions of this work are discussed, while in chapter 8 itis proposed how TESS’s measurements can be able to discern between erroneousinterpretations of transmission spectra, especially on systems where the impact parameter degeneracy is likely not applicable.
Recurrences in past climates
(2023)
Our ability to predict the state of a system relies on its tendency to recur to states it has visited before. Recurrence also pervades common intuitions about the systems we are most familiar with: daily routines, social rituals and the return of the seasons are just a few relatable examples. To this end, recurrence plots (RP) provide a systematic framework to quantify the recurrence of states. Despite their conceptual simplicity, they are a versatile tool in the study of observational data. The global climate is a complex system for which an understanding based on observational data is not only of academical relevance, but vital for the predurance of human societies within the planetary boundaries. Contextualizing current global climate change, however, requires observational data far beyond the instrumental period. The palaeoclimate record offers a valuable archive of proxy data but demands methodological approaches that adequately address its complexities. In this regard, the following dissertation aims at devising novel and further developing existing methods in the framework of recurrence analysis (RA). The proposed research questions focus on using RA to capture scale-dependent properties in nonlinear time series and tailoring recurrence quantification analysis (RQA) to characterize seasonal variability in palaeoclimate records (‘Palaeoseasonality’).
In the first part of this thesis, we focus on the methodological development of novel approaches in RA. The predictability of nonlinear (palaeo)climate time series is limited by abrupt transitions between regimes that exhibit entirely different dynamical complexity (e.g. crossing of ‘tipping points’). These possibly depend on characteristic time scales. RPs are well-established for detecting transitions and capture scale-dependencies, yet few approaches have combined both aspects. We apply existing concepts from the study of self-similar textures to RPs to detect abrupt transitions, considering the most relevant time scales. This combination of methods further results in the definition of a novel recurrence based nonlinear dependence measure. Quantifying lagged interactions between multiple variables is a common problem, especially in the characterization of high-dimensional complex systems. The proposed ‘recurrence flow’ measure of nonlinear dependence offers an elegant way to characterize such couplings. For spatially extended complex systems, the coupled dynamics of local variables result in the emergence of spatial patterns. These patterns tend to recur in time. Based on this observation, we propose a novel method that entails dynamically distinct regimes of atmospheric circulation based on their recurrent spatial patterns. Bridging the two parts of this dissertation, we next turn to methodological advances of RA for the study of Palaeoseasonality. Observational series of palaeoclimate ‘proxy’ records involve inherent limitations, such as irregular temporal sampling. We reveal biases in the RQA of time series with a non-stationary sampling rate and propose a correction scheme.
In the second part of this thesis, we proceed with applications in Palaeoseasonality. A review of common and promising time series analysis methods shows that numerous valuable tools exist, but their sound application requires adaptions to archive-specific limitations and consolidating transdisciplinary knowledge. Next, we study stalagmite proxy records from the Central Pacific as sensitive recorders of mid-Holocene El Niño-Southern Oscillation (ENSO) dynamics. The records’ remarkably high temporal resolution allows to draw links between ENSO and seasonal dynamics, quantified by RA. The final study presented here examines how seasonal predictability could play a role for the stability of agricultural societies. The Classic Maya underwent a period of sociopolitical disintegration that has been linked to drought events. Based on seasonally resolved stable isotope records from Yok Balum cave in Belize, we propose a measure of seasonal predictability. It unveils the potential role declining seasonal predictability could have played in destabilizing agricultural and sociopolitical systems of Classic Maya populations.
The methodological approaches and applications presented in this work reveal multiple exciting future research avenues, both for RA and the study of Palaeoseasonality.
The Lyman-𝛼 (Ly𝛼) line commonly assists in the detection of high-redshift galaxies, the so-called Lyman-alpha emitters (LAEs). LAEs are useful tools to study the baryonic matter distribution of the high-redshift universe. Exploring their spatial distribution not only reveals the large-scale structure of the universe at early epochs, but it also provides an insight into the early formation and evolution of the galaxies we observe today. Because dark matter halos (DMHs) serve as sites of galaxy formation, the LAE distribution also traces that of the underlying dark matter. However, the details of this relation and their co-evolution over time remain unclear. Moreover, theoretical studies predict that the spatial distribution of LAEs also impacts their own circumgalactic medium (CGM) by influencing their extended Ly𝛼 gaseous halos (LAHs), whose origin is still under investigation. In this thesis, I make several contributions to improve the knowledge on these fields using samples of LAEs observed with the Multi Unit Spectroscopic Explorer (MUSE) at redshifts of 3 < 𝑧 < 6.
Stars under influence: evidence of tidal interactions between stars and substellar companions
(2023)
Tidal interactions occur between gravitationally bound astrophysical bodies. If their spatial separation is sufficiently small, the bodies can induce tides on each other, leading to angular momentum transfer and altering of evolutionary path the bodies would have followed if they were single objects. The tidal processes are well established in the Solar planet-moon systems and close stellar binary systems. However, how do stars behave if they are orbited by a substellar companion (e.g. a planet or a brown dwarf) on a tight orbit?
Typically, a substellar companion inside the corotation radius of a star will migrate toward the star as it loses orbital angular momentum. On the other hand, the star will gain angular momentum which has the potential to increase its rotation rate. The effect should be more pronounced if the substellar companion is more massive. As the stellar rotation rate and the magnetic activity level are coupled, the star should appear more magnetically active under the tidal influence of the orbiting substellar companion. However, the difficulty in proving that a star has a higher magnetic activity level due to tidal interactions lies in the fact that (I) substellar companions around active stars are easier to detect if they are more massive, leading to a bias toward massive companions around active stars and mimicking the tidal interaction effect, and that (II) the age of a main-sequence star cannot be easily determined, leaving the possibility that a star is more active due to its young age.
In our work, we overcome these issues by employing wide stellar binary systems where one star hosts a substellar companion, and where the other star provides the magnetic activity baseline for the host star, assuming they have coevolved, and thereby provides the host's activity level if tidal interactions have no effect on it. Firstly, we find that extrasolar planets can noticeably increase the host star's X-ray luminosity and that the effect is more pronounced if the exoplanet is at least Jupiter-like in mass and close to the star. Further, we find that a brown dwarf will have an even stronger effect, as expected, and that the X-ray surface flux difference between the host star and the wide stellar companion is a significant outlier when compared to a large sample of similar wide binary systems without any known substellar companions. This result proves that substellar hosting wide binary systems can be good tools to reveal the tidal effect on host stars, and also show that the typical stellar age indicators as activity or rotation cannot be used for these stars. Finally, knowing that the activity difference is a good tracer of the substellar companion's tidal impact, we develop an analytical method to calculate the modified tidal quality factor Q' of individual host stars, which defines the tidal dissipation efficiency in the convective envelope of a given main-sequence star.
Properties of Arctic aerosol in the transition between Arctic haze to summer season derived by lidar
(2023)
During the Arctic haze period, the Arctic troposphere consists of larger, yet fewer, aerosol particles than during the summer (Tunved et al., 2013; Quinn et al., 2007). Interannual variability (Graßl and Ritter, 2019; Rinke et al., 2004), as well as unknown origins (Stock et al., 2014) and properties of aerosol complicate modeling these annual aerosol cycles. This thesis investigates the modification of the microphysical properties of Arctic aerosols in the transition from Arctic haze to the summer season. Therefore, lidar measurements of Ny-Ålesund from April 2021 to the end of July 2021 are evaluated based on the aerosols’ optical properties. An overview of those properties will be provided. Furthermore, parallel radiosonde data is considered for indication of hygroscopic growth.
The annual aerosol cycle in 2021 differs from expectations based on previous studies from Tunved et al. (2013) and Quinn et al. (2007). Developments of backscatter, extinction, aerosol depolarisation, lidar ratio and color ratio show a return of the Arctic haze in May. The haze had already reduced in April, but regrew afterwards.
The average Arctic aerosol displays hygroscopic behaviour, meaning growth due to water uptake. To determine such a behaviour is generally laborious because various meteorological circumstances need to be considered. Two case studies provide further information on these possible events. In particular, a day with a rare ice cloud and with highly variable water cloud layers is observed.
Late-type stars are by far the most frequent stars in the universe and of fundamental interest to various fields of astronomy – most notably to Galactic archaeology and exoplanet research. However, such stars barely change during their main sequence lifetime; their temperature, luminosity, or chemical composition evolve only very slowly over the course of billions of years. As such, it is difficult to obtain the age of such a star, especially when it is isolated and no other indications (like cluster association) can be used. Gyrochronology offers a way to overcome this problem.
Stars, just like all other objects in the universe, rotate and the rate at which stars rotate impacts many aspects of their appearance and evolution. Gyrochronology leverages the observed rotation rate of a late-type main sequence star and its systematic evolution to estimate their ages. Unlike the above-mentioned parameters, the rotation rate of a main sequence star changes drastically throughout its main sequence lifetime; stars spin down. The youngest stars rotate every few hours, whereas much older stars rotate only about once a month, or – in the case of some late M-stars – once in a hundred days. Given that this spindown is systematic (with an additional mass dependence), it gave rise to the idea of using the observed rotation rate of a star (and its mass or a suitable proxy thereof) to estimate a star’s age. This has been explored widely in young stellar open clusters but remains essentially unconstrained for stars older than the sun, and K and M stars older than 1 Gyr.
This thesis focuses on the continued exploration of the spindown behavior to assess, whether gyrochronology remains applicable for stars of old ages, whether it is universal for late-type main sequence stars (including field stars), and to provide calibration mileposts for spindown models. To accomplish this, I have analyzed data from Kepler space telescope for the open clusters Ruprecht 147 (2.7 Gyr old) and M 67 (4 Gyr). Time series photometry data (light curves)
were obtained for both clusters during Kepler’s K2 mission. However, due to technical limitations and telescope malfunctions, extracting usable data from the K2 mission to identify (especially long) rotation periods requires extensive data preparation.
For Ruprecht 147, I have compiled a list of about 300 cluster members from the literature and adopted preprocessed light curves from the Kepler archive where available. They have been cleaned of the gravest of data artifacts but still contained systematics. After correcting them for said artifacts, I was able to identify rotation periods in 31 of them.
For M 67 more effort was taken. My work on Ruprecht 147 has shown the limitations imposed by the preselection of Kepler targets. Therefore, I adopted the time series full frame image directly and performed photometry on a much higher spatial resolution to be able to obtain data for as many stars as possible. This also means that I had to deal with the ubiquitous artifacts in Kepler data. For that, I devised a method that correlates the artificial flux variations with the ongoing drift of the telescope pointing in order to remove it. This process was a large success and I was able to create light curves whose quality match and even exceede those that were created by the Kepler mission – all while operating on higher spatial resolution and processing fainter stars. Ultimately, I was able to identify signs of periodic variability in the (created) light curves for 31 and 47 stars in Ruprecht 147 and M 67, respectively. My data connect well to bluer stars of cluster of the same age and extend for the first time to stars redder than early-K and older than 1 Gyr. The cluster data show a clear flattening in the distribution of Ruprecht 147 and even a downturn for M 67, resulting in a somewhat sinusoidal shape. With that, I have shown that the systematic spindown of stars continues at least until 4 Gyr and stars continue to live on a single surface in age-rotation periods-mass space which allows gyrochronology to be used at least up to that age. However, the shape of the spindown – as exemplified by the newly discovered sinusoidal shape of the cluster sequence – deviates strongly from the expectations.
I then compiled an extensive sample of rotation data in open clusters – very much including my own work – and used the resulting cluster skeleton (with each cluster forming a rip in color-rotation period-mass space) to investigate if field stars follow the same spindown as cluster stars. For the field stars, I used wide binaries, which – with their shared origin and coevality – are in a sense the smallest possible open clusters. I devised an empirical method to evaluate the consistency between the rotation rates of the wide binary components and found that the vast majority of them are in fact consistent with what is observed in open clusters. This leads me to conclude that gyrochronology – calibrated on open clusters – can be applied to determine the ages of field stars.
International migration has been an increasing phenomenon during the past decades and has involved all the regions of the globe. Together with fertility and mortality rates, net migration rates represent the components that fully define the demographic evolution of the population in a country. Therefore, being able to capture the patterns of international migration flows and to produce projections of how they might change in the future is of relevant importance for demographic studies and for designing policies informed on the potential scenarios. Existing forecasting methods do not account explicitly for the main drivers and processes shaping international migration flows: existing migrant communities at the destination country, termed diasporas, would reduce the costs of migration and facilitate the settling for new migrants, ultimately producing a positive feedback; accounting for the heterogeneity in the type of migration flows, e.g. return and transit Ćows, becomes critical in some specific bilateral migration channels; in low- to middle- income countries economic development could relax poverty constraint and result in an increase of emigration rates.
Economic conditions at both origin and destination are identified as major drivers of international migration. At the same time, climate change impacts have already appeared on natural and human-made systems such as the economic productivity. These economic impacts might have already produced a measurable effect on international migration flows. Studies that provide a quantification of the number of migration moves that might have been affected by climate change are usually specific to small regions, do not provide a mechanistic understanding of the pathway leading from climate change to migration and restrict their focus to the effective induced flows, disregarding the impact that climate change might have had in inhibiting other flows.
Global climate change is likely to produce impacts on the economic development of the countries during the next decades too. Understanding how these impacts might alter future global migration patterns is relevant for preparing future societies and understanding whether the response in migration flows would reduce or increase population's exposure to climate change impacts.
This doctoral research aims at investigating these questions and fill the research gaps outlined above. First, I have built a global bilateral international migration model which accounts explicitly for the diaspora feedback, distinguishes between transit and return flows, and accounts for the observed non-linear effects that link emigration rates to income levels in the country of origin. I have used this migration model within a population dynamic model where I account also for fertility and mortality rates, producing hindcasts and future projections of international migration flows, covering more than 170 countries. Results show that the model reproduces past patterns and trends well. Future projections highlight the fact that,depending on the assumptions regarding future evolution of income levels and between-country inequality, migration at the end of the century might approach net zero or be still high in many countries. The model, parsimonious in the explanatory variables that includes, represents a versatile tool for assessing the impacts of different socioeconomic scenarios on international migration.
I consider then a counterfactual past without climate change impacts on the economic productivity. By prescribing these counterfactual economic conditions to the migration model I produce counterfactual migration flows for the past 30 years. I compare the counterfactual migration flows to factual ones, where historical economic conditions are used to produce migration flows. This provides an estimation of the recent international migration flows attributed to climate change impacts. Results show that a counterfactual world without climate change would have seen less migration globally. This effect becomes larger if I consider separately the increase and decrease in migration moves: a Ągure of net change in the migration flows is not representative of the effective magnitude of the climate change impact on migration. Indeed, in my results climate change produces a divergent effect on richer and poorer countries: by slowing down the economic development, climate change might have reduced international mobility from and to countries of the Global South, and increased it from and to richer countries in the Global North.
I apply the same methodology to a scenario of future 3℃ global warming above pre-industrial conditions. I Ąnd that climate change impacts, acting by reorganizing the relative economic attractiveness of destination countries or by affecting the economic growth in the origin, might produce a substantial effect in international migration flows, inhibiting some moves and inducing others.
Overall my results suggest that climate change might have had and might have in the future a significant effect on global patterns of international migration. It also emerges clearly that, for a comprehensive understanding of the effects of climate change on international migration, we need to go beyond net effects and consider separately induced and inhibited flows.
The evolution of a galaxy is pivotally governed by its pattern of star formation over a given period of time. The star formation rate at any given time is strongly dependent on the amount of cold gas available in the galaxy. Accretion of pristine gas from the Intergalactic medium (IGM) is thought to be one of the primary sources for star-forming gas. This gas first passes through the virial regions of the galaxy before reaching the Interstellar medium (ISM), the hub of star formation. On the other hand, owing to the evolutionary course of young and massive stars, energetic winds are ejected from the ISM to the virial regions of the galaxy. A bunch of interlinked, complex astrophysical processes, arising from the concurrent presence of both infalling as well as outbound gas, play out over a range of timescales in the halo region or the Circumgalactic medium (CGM) of a galaxy. It would not be incorrect to say that the CGM has a stronghold over the gas reserves of a galaxy and thus, plays a backhand, yet, rather pivotal role in shaping many galactic properties, some of which are also readily observable. Observing the multi-phase CGM (via spectral-line ion measurements), however, remains a non-trivial effort even today. Low particle densities as well as the CGM’s vast spatial extent, coupled with likely deviations from a spherical distribution, marr the possibility of obtaining complete, unbiased, high-quality spectral information tracing the full extent of the gaseous halo. This often incomplete information leads to multiple inferences about the CGM properties that give rise to multiple contradicting models. In this regard, computer simulations offer a neat solution towards testing and, subsequently, falsifying many of these existing CGM models. Thanks to their controlled environments, simulations are able to not only effortlessly transcend several orders of magnitude in time and space, but also get around many of the observational limitations and provide some unique views on many CGM properties. In this thesis, I focus on effectively using different computer simulations to understand the role of CGM in various astrophysical contexts, namely, the effect of Local Group (LG) environment, major merger events and satellite galaxies. In Chapter 2, I discuss the approach used for modeling various phases of the simulated z = 0 LG CGM in Hestia constrained simulations. Each of the three realizations contain a Milky Way (MW)–Andromeda (M31) galaxy pair, along with their corresponding sets of satellite galaxies, all embedded within the larger cosmological context. For characterizing the different temperature–density phases within the CGM, I model five tracer ions with cloudy ionization modeling. The cold and cool–ionized CGM (H i and Si iii respectively) in Hestia is very clumpy and distributed close to the galactic centers, while the warm-hot and hot CGM (O vi, O vii and O viii) is tenuous and volume-filling. On comparing the H i and Si iii column densities for the simulated M31 with observational measurements from Project AMIGA survey and other low-z galaxies, I found that Hestia galaxies produced less gas in the outer CGM, unlike observations. My carefully designed observational bias model subsequently revealed the possibility that some MW gas clouds might be incorrectly associated with the M31 CGM in observations, and hence, may be partly responsible for giving rise to the detected mismatch between simulated data and observations. In Chapter 3, I present results from four zoom–in, major merger, gas–rich simulations and the subsequent role of the gas, originally situated in the CGM, in influencing some of the galactic observables. The progenitor parameters are selected such that the post–merger remnants are MW–mass galaxies. We generally see a very clear gas bridge joining the merging galaxies in case of multiple passage mergers while such a bridge is mostly absent when a direct collision occurs. On the basis of particle–to–galaxy distance computations and tracer particle analysis, I found that about 33–48 percent of the cold gas contributing to the merger–induced star formation in the bridge originated from the CGM regions. In Chapter 4, I used a sample of 234 MW-mass, L* galaxies from the TNG50 cosmological simulations, with an aim of characterizing the impact of their global satellite populations on the extended cold CGM properties of their host L* halos. On the basis of halo mass and number of satellite galaxies (N_sats ), I categorized the sample into low and high mass bins, and subsequently into bottom, inter and top quartiles respectively. After confirming that satellites indeed influence the extended cold halo gas density profiles of the host galaxies, I investigated the effects of different satellite population parameters on the host halo cold CGMs. My analysis showed that there is hardly any cold gas associated with the satellite population of the lowest mass halos. The stellar mass of the most massive satellite (M_*mms ) impacted the cold gas in low mass bin halos the most, while N_sats (followed by M_*mms ) was the most influential factor for the high mass halos. In any case, how easily cold gas was stripped off the most massive satellite did not play much role. The number of massive (Stellar mass, M* > 10^8 M_solar) satellites as well as the M_*mms associated with a galaxy are two of the most crucial parameters determining how much cold gas ultimately finds its way from the satellites to the host halo. Low mass galaxies are found rather lacking on both these fronts unlike their high mass counterparts. This work highlights some aspects of the complex gas physics that constitute the basic essence of a low-z CGM. My analysis proved the importance of a cosmological environment, local surroundings and merger history in defining some key observable properties of a galactic CGM. Furthermore, I found that different satellite properties were responsible for affecting the cold–dense CGM of the low and high-mass parent galaxies. Finally, the LG emerged as an exciting prospect for testing and pinning down several intricate details about the CGM.
Search for light primordial black holes with VERITAS using gamma γ-ray and optical observations
(2023)
The Very Energetic Radiation Imaging Telescope Array System (VERITAS) is an array of four imaging atmospheric Cherenkov telescopes (IACTs). VERITAS is sensitive to very-high-energy gamma-rays in the range of 100 GeV to >30 TeV. Hypothesized primordial black holes (PBHs) are attractive targets for IACTs. If they exist, their potential cosmological impact reaches beyond the candidacy for constituents of dark matter. The sublunar mass window is the largest unconstrained range of PBH masses. This thesis aims to develop novel concepts searching for light PBHs with VERITAS. PBHs below the sublunar window lose mass due to Hawking radiation. They would evaporate at the end of their lifetime, leading to a short burst of gamma-rays. If PBHs formed at about 10^15 g, the evaporation would occur nowadays. Detecting these signals might not only confirm the existence of PBHs but also prove the theory of Hawking radiation. This thesis probes archival VERITAS data recorded between 2012 and 2021 for possible PBH signals. This work presents a new automatic approach to assess the quality of the VERITAS data. The array-trigger rate and far infrared temperature are well suited to identify periods with poor data quality. These are masked by time cuts to obtain a consistent and clean dataset which contains about 4222 hours. The PBH evaporations could occur at any location in the field of view or time within this data. Only a blind search can be performed to identify these short signals. This thesis implements a data-driven deep learning based method to search for short transient signals with VERITAS. It does not depend on the modelling of the effective area and radial acceptance. This work presents the first application of this method to actual observational IACT data. This thesis develops new concepts dealing with the specifics of the data and the transient detection method. These are reflected in the developed data preparation pipeline and search strategies. After correction for trial factors, no candidate PBH evaporation is found in the data. Thus, new constraints of the local rate of PBH evaporations are derived. At the 99% confidence limit it is below <1.07 * 10^5 pc^-3 yr^-1. This constraint with the new, independent analysis approach is in the range of existing limits for the evaporation rate.
This thesis also investigates an alternative novel approach to searching for PBHs with IACTs. Above the sublunar window, the PBH abundance is constrained by optical microlensing studies. The sampling speed, which is of order of minutes to hours for traditional optical telescopes, is a limiting factor in expanding the limits to lower masses. IACTs are also powerful instruments for fast transient optical astronomy with up to O(ns) sampling. This thesis investigates whether IACTs might constrain the sublunar window with optical microlensing observations. This study confirms that, in principle, the fast sampling speed might allow extending microlensing searches into the sublunar mass window. However, the limiting factor for IACTs is the modest sensitivity to detect changes in optical fluxes. This thesis presents the expected rate of detectable events for VERITAS as well as prospects of possible future next-generation IACTs. For VERITAS, the rate of detectable microlensing events in the sublunar range is ~10^-6 per year of observation time. The future prospects for a 100 times more sensitive instrument are at ~0.05 events per year.
Supernova remnants are considered to be the primary sources of galactic cosmic rays. These cosmic rays are assumed to be accelerated by the diffusive shock acceleration mechanism, specifically at shocks in the remnants. Particularly in the core-collapse scenario, these supernova remnant shocks expand inside the wind-blown bubbles structured by massive progenitors during their lifetime. Therefore, the complex environment of wind bubbles can influence the particle acceleration and radiation from the remnants. Further, the evolution of massive stars depends on their Zero Age Main Sequence mass, rotation, and metallicity. Consequently, the structures of the wind bubbles generated during the lifetime of massive stars should be considerably different. Hence, the particle acceleration in the core-collapse supernova remnants should vary, not only from the remnants evolving in the uniform environment but also from one another, depending on their progenitor stars.
A core-collapse supernova remnant with a very massive 60 𝑀 ⊙ progenitor star has been considered to study the particle acceleration at the shock considering Bohm-like diffusion. This dissertation demonstrates the modification in particle acceleration and radiation while the remnant propagates through different regions of the wind bubble by impacts from the profiles of gas density, the temperature of the bubble and the magnetic field structure. Subsequently, in this thesis, I discuss the impacts of the non-identical ambient environment of core-collapse supernova remnants on particle spectra and the non-thermal emissions, considering 20 𝑀 ⊙ and 60 𝑀⊙ massive progenitors having different evolutionary tracks. Additionally, I also analyse the effect of cosmic ray streaming instabilities on particle spectra.
To model the particle acceleration in the remnants, I have performed simulations in one-dimensional spherical symmetry using RATPaC code. The transport equation for cosmic rays and magnetic turbulence in test-particle approximation, along with the induction equation for the evolution of the large-scale magnetic field, have been solved simultaneously with the hydrodynamic equations for the expansion of remnants inside the pre-supernova circumstellar medium.
The results from simulations describe that the spectra of accelerated particles in supernova remnants are regulated by density fluctuations, temperature variations, the large-scale magnetic field configuration and scattering turbulence. Although the diffusive shock acceleration mechanism at supernova remnant shock predicts the spectral index of 2 for the accelerated non-thermal particles, I have obtained the particle spectra that deviate from this prediction, in the core-collapse scenario. I have found that the particle spectral index reaches 2.5 for the supernova remnant with 60 𝑀 ⊙ progenitor when the remnant resides inside the shocked wind region of the wind bubble, and this softness persists at later evolutionary stages even with Bohm-like diffusion for accelerated particles. However, the supernova remnant with 20 𝑀 ⊙ progenitor does not demonstrate persistent softness in particle spectra from the influence of the hydrodynamics of the corresponding wind bubble. At later stages of evolution, the particle spectra illustrate softness at higher energies for both remnants as the consequence of the escape of high-energy particles from the remnants while considering the cosmic ray streaming instabilities. Finally, I have probed the emission morphology of remnants that varies depending on the progenitors, particularly in earlier evolutionary stages. This dissertation provides insight into different core-collapse remnants expanding inside wind bubbles, for instance, the calculated gamma-ray spectral index from the supernova remnant with 60 𝑀 ⊙ progenitor at later evolutionary stages is consistent with that of the observed supernova remnants expanding in dense molecular clouds.
In the last century, several astronomical measurements have supported that a significant percentage (about 22%) of the total mass of the Universe, on galactic and extragalactic scales, is composed of a mysterious ”dark” matter (DM). DM does not interact with the electromagnetic force; in other words it does not reflect, absorb or emit light. It is possible that DM particles are weakly interacting massive particles (WIMPs) that can annihilate (or decay) into Standard Model (SM) particles, and modern very- high-energy (VHE; > 100 GeV) instruments such as imaging atmospheric Cherenkov telescopes (IACTs) can play an important role in constraining the main properties of such DM particles, by detecting these products. One of the most privileged targets where to look for DM signal are dwarf spheroidal galaxies (dSphs), as they are expected to be high DM-dominated objects with a clean, gas-free environment. Some dSphs could be considered as extended sources, considering the angular resolution of IACTs; their angu- lar resolution is adequate to detect extended emission from dSphs. For this reason, we performed an extended-source analysis, by taking into account in the unbinned maximum likelihood estimation both the energy and the angular extension dependency of observed events. The goal was to set more constrained upper limits on the velocity-averaged cross-section annihilation of WIMPs with VERITAS data. VERITAS is an array of four IACTs, able to detect γ-ray photons ranging between 100 GeV and 30 TeV. The results of this extended analysis were compared against the traditional spectral analysis. We found that a 2D analysis may lead to more constrained results, depending on the DM mass, channel, and source. Moreover, in this thesis, the results of a multi-instrument project are presented too. Its goal was to combine already published 20 dSphs data from five different experiments, such as Fermi-LAT, MAGIC, H.E.S.S., VERITAS and HAWC, in order to set upper limits on the WIMP annihilation cross-section in the widest mass range ever reported.
The first part of the thesis studies the properties of fast mode in magneto hydro-dynamic (MHD) turbulence. 1D and 3D numerical simulations are carried out to generate decaying fast mode MHD turbulence. The injection of waves are carried out in a collinear and isotropic fashion to generate fast mode turbulence. The properties of fast mode turbulence are analyzed by studying their energy spectral density, 2D structure functions and energy decay/cascade time. The injection wave vector is varied to study the dependence of the above properties on the injection wave vectors. The 1D energy spectrum obtained for the velocity and magnetic fields has 𝐸 (𝑘) ∝ 𝑘−2. The 2D energy spectrum and 2D structure functions in parallel and perpendicular directions shows that fast mode turbulence generated is isotropic in nature. The cascade/decay rate of fast mode MHD turbulence is proportional to 𝑘−0.5 for different kinds of wave vector injection. Simulations are also carried out in 1D and 3D to compare balanced and imbalanced turbulence. The results obtained shows that while 1D imbalanced turbulence decays faster than 1D balanced turbulence, there is no difference in the decay of 3D balanced and imbalanced turbulence for the current resolution of 512 grid points.
"The second part of the thesis studies cosmic ray (CR) transport in driven MHD turbulence and is strongly dependent on it’s properties. Test particle simulations are carried out to study CR interaction with both total MHD turbulence and decomposed MHD modes. The spatial diffusion coefficients and the pitch angle scattering diffusion coefficients are calculated from the test particle trajectories in turbulence. The results confirms that the fast modes dominate the CR propagation, whereas Alfvén, slow modes are much less efficient with similar pitch angle scattering rates. The cross field transport on large and small scales are investigated next. On large/global scales, normal diffusion is observed and the diffusion coefficient is suppressed by 𝑀𝜁𝐴 compared to the parallel diffusion coefficients, with 𝜁 closer to 4 in Alfvén modes than that in total turbulence as theoretically expected. For the CR transport on scales smaller than the turbulence injection scale 𝐿, both the local and global magnetic reference frames are adopted. Super diffusion is observed on such small scales in all the cases. Particularly, CR transport in Alfvén modes show clear Richardson diffusion in the local reference frame. The diffusion transition smoothly from the Richardson’s one with index 1.5 to normal diffusion as particle’s mean free path decreases from 𝜆∥ ≫ 𝐿 to 𝜆∥ ≪ 𝐿. These results have broad applications to CRs in various astrophysical environments".
The near-Earth space environment is a highly complex system comprised of several regions and particle populations hazardous to satellite operations. The trapped particles in the radiation belts and ring current can cause significant damage to satellites during space weather events, due to deep dielectric and surface charging. Closer to Earth is another important region, the ionosphere, which delays the propagation of radio signals and can adversely affect navigation and positioning. In response to fluctuations in solar and geomagnetic activity, both the inner-magnetospheric and ionospheric populations can undergo drastic and sudden changes within minutes to hours, which creates a challenge for predicting their behavior. Given the increasing reliance of our society on satellite technology, improving our understanding and modeling of these populations is a matter of paramount importance.
In recent years, numerous spacecraft have been launched to study the dynamics of particle populations in the near-Earth space, transforming it into a data-rich environment. To extract valuable insights from the abundance of available observations, it is crucial to employ advanced modeling techniques, and machine learning methods are among the most powerful approaches available. This dissertation employs long-term satellite observations to analyze the processes that drive particle dynamics, and builds interdisciplinary links between space physics and machine learning by developing new state-of-the-art models of the inner-magnetospheric and ionospheric particle dynamics.
The first aim of this thesis is to investigate the behavior of electrons in Earth's radiation belts and ring current. Using ~18 years of electron flux observations from the Global Positioning System (GPS), we developed the first machine learning model of hundreds-of-keV electron flux at Medium Earth Orbit (MEO) that is driven solely by solar wind and geomagnetic indices and does not require auxiliary flux measurements as inputs. We then proceeded to analyze the directional distributions of electrons, and for the first time, used Fourier sine series to fit electron pitch angle distributions (PADs) in Earth's inner magnetosphere. We performed a superposed epoch analysis of 129 geomagnetic storms during the Van Allen Probes era and demonstrated that electron PADs have a strong energy-dependent response to geomagnetic activity. Additionally, we showed that the solar wind dynamic pressure could be used as a good predictor of the PAD dynamics. Using the observed dependencies, we created the first PAD model with a continuous dependence on L, magnetic local time (MLT) and activity, and developed two techniques to reconstruct near-equatorial electron flux observations from low-PA data using this model.
The second objective of this thesis is to develop a novel model of the topside ionosphere. To achieve this goal, we collected observations from five of the most widely used ionospheric missions and intercalibrated these data sets. This allowed us to use these data jointly for model development, validation, and comparison with other existing empirical models. We demonstrated, for the first time, that ion density observations by Swarm Langmuir Probes exhibit overestimation (up to ~40-50%) at low and mid-latitudes on the night side, and suggested that the influence of light ions could be a potential cause of this overestimation. To develop the topside model, we used 19 years of radio occultation (RO) electron density profiles, which were fitted with a Chapman function with a linear dependence of scale height on altitude. This approximation yields 4 parameters, namely the peak density and height of the F2-layer and the slope and intercept of the linear scale height trend, which were modeled using feedforward neural networks (NNs). The model was extensively validated against both RO and in-situ observations and was found to outperform the International Reference Ionosphere (IRI) model by up to an order of magnitude. Our analysis showed that the most substantial deviations of the IRI model from the data occur at altitudes of 100-200 km above the F2-layer peak. The developed NN-based ionospheric model reproduces the effects of various physical mechanisms observed in the topside ionosphere and provides highly accurate electron density predictions.
This dissertation provides an extensive study of geospace dynamics, and the main results of this work contribute to the improvement of models of plasma populations in the near-Earth space environment.
Flares are magnetically driven explosions that occur in the atmospheres of all main sequence stars that possess an outer convection zone. Flaring activity is rooted in the magnetic dynamo that operates deep in the stellar interior, propagates through all layers of the atmosphere from the corona to the photosphere, and emits electromagnetic radiation from radio bands to X-ray. Eventually, this radiation, and associated eruptions of energetic particles, are ejected out into interplanetary space, where they impact planetary atmospheres, and dominate the space weather environments of young star-planet systems.
Thanks to the Kepler and the Transit Exoplanet Survey Satellite (TESS) missions, flare observations have become accessible for millions of stars and star-planet systems. The goal of this thesis is to use these flares as multifaceted messengers to understand stellar magnetism across the main sequence, investigate planetary habitability, and explore how close-in planets can affect the host star.
Using space based observations obtained by the Kepler/K2 mission, I found that flaring activity declines with stellar age, but this decline crucially depends on stellar mass and rotation. I calibrated the age of the stars in my sample using their membership in open clusters from zero age main sequence to solar age. This allowed me to reveal the rapid transition from an active, saturated flaring state to a more quiescent, inactive flaring behavior in early M dwarfs at about 600-800 Myr. This result is an important observational constraint on stellar activity evolution that I was able to de-bias using open clusters as an activity-independent age indicator.
The TESS mission quickly superseded Kepler and K2 as the main source of flares in low mass M dwarfs. Using TESS 2-minute cadence light curves, I developed a new technique for flare localization and discovered, against the commonly held belief, that flares do not occur uniformly across their stellar surface: In fast rotating fully convective stars, giant flares are preferably located at high latitudes. This bears implications for both our understanding of magnetic field emergence in these stars, and the impact on the exoplanet atmospheres: A planet that orbits in the equatorial plane of its host may be spared from the destructive effects of these poleward emitting flares.
AU Mic is an early M dwarf, and the most actively flaring planet host detected to date. Its innermost companion, AU Mic b is one of the most promising targets for a first observation of flaring star-planet interactions. In these interactions, the planet influences the star, as opposed to space weather, where the planet is always on the receiving side. The effect reflects the properties of the magnetosphere shared by planet and star, as well as the so far inaccessible magnetic properties of planets. In the about 50 days of TESS monitoring data of AU Mic, I searched for statistically robust signs of flaring interactions with AU Mic b as flares that occur in surplus of the star's intrinsic activity. I found the strongest yet still marginal signal in recurring excess flaring in phase with the orbital period of AU Mic b. If it reflects true signal, I estimate that extending the observing time by a factor of 2-3 will yield a statistically significant detection. Well within the reach of future TESS observations, this additional data may bring us closer to robustly detecting this effect than we have ever been.
This thesis demonstrates the immense scientific value of space based, long baseline flare monitoring, and the versatility of flares as a carrier of information about the magnetism of star-planet systems. Many discoveries still lay in wait in the vast archives that Kepler and TESS have produced over the years. Flares are intense spotlights into the magnetic structures in star-planet systems that are otherwise far below our resolution limits. The ongoing TESS mission, and soon PLATO, will further open the door to in-depth understanding of small and dynamic scale magnetic fields on low mass stars, and the space weather environment they effect.
In the present thesis I investigate the lattice dynamics of thin film hetero structures of magnetically ordered materials upon femtosecond laser excitation as a probing and manipulation scheme for the spin system. The quantitative assessment of laser induced thermal dynamics as well as generated picosecond acoustic pulses and their respective impact on the magnetization dynamics of thin films is a challenging endeavor. All the more, the development and implementation of effective experimental tools and comprehensive models are paramount to propel future academic and technological progress.
In all experiments in the scope of this cumulative dissertation, I examine the crystal lattice of nanoscale thin films upon the excitation with femtosecond laser pulses. The relative change of the lattice constant due to thermal expansion or picosecond strain pulses is directly monitored by an ultrafast X-ray diffraction (UXRD) setup with a femtosecond laser-driven plasma X-ray source (PXS). Phonons and spins alike exert stress on the lattice, which responds according to the elastic properties of the material, rendering the lattice a versatile sensor for all sorts of ultrafast interactions. On the one hand, I investigate materials with strong magneto-elastic properties; The highly magnetostrictive rare-earth compound TbFe2, elemental Dysprosium or the technological relevant Invar material FePt. On the other hand I conduct a comprehensive study on the lattice dynamics of Bi1Y2Fe5O12 (Bi:YIG), which exhibits high-frequency coherent spin dynamics upon femtosecond laser excitation according to the literature. Higher order standing spinwaves (SSWs) are triggered by coherent and incoherent motion of atoms, in other words phonons, which I quantified with UXRD. We are able to unite the experimental observations of the lattice and magnetization dynamics qualitatively and quantitatively. This is done with a combination of multi-temperature, elastic, magneto-elastic, anisotropy and micro-magnetic modeling.
The collective data from UXRD, to probe the lattice, and time-resolved magneto-optical Kerr effect (tr-MOKE) measurements, to monitor the magnetization, were previously collected at different experimental setups. To improve the precision of the quantitative assessment of lattice and magnetization dynamics alike, our group implemented a combination of UXRD and tr-MOKE in a singular experimental setup, which is to my knowledge, the first of its kind. I helped with the conception and commissioning of this novel experimental station, which allows the simultaneous observation of lattice and magnetization dynamics on an ultrafast timescale under identical excitation conditions. Furthermore, I developed a new X-ray diffraction measurement routine which significantly reduces the measurement time of UXRD experiments by up to an order of magnitude. It is called reciprocal space slicing (RSS) and utilizes an area detector to monitor the angular motion of X-ray diffraction peaks, which is associated with lattice constant changes, without a time-consuming scan of the diffraction angles with the goniometer. RSS is particularly useful for ultrafast diffraction experiments, since measurement time at large scale facilities like synchrotrons and free electron lasers is a scarce and expensive resource. However, RSS is not limited to ultrafast experiments and can even be extended to other diffraction techniques with neutrons or electrons.
In this thesis, I present my contributions to the field of ultrafast molecular spectroscopy. Using the molecule 2-thiouracil as an example, I use ultrashort x-ray pulses from free- electron lasers to study the relaxation dynamics of gas-phase molecular samples. Taking advantage of the x-ray typical element- and site-selectivity, I investigate the charge flow and geometrical changes in the excited states of 2-thiouracil.
In order to understand the photoinduced dynamics of molecules, knowledge about the ground-state structure and the relaxation after photoexcitation is crucial. Therefore, a part of this thesis covers the electronic ground-state spectroscopy of mainly 2-thiouracil to provide the basis for the time-resolved experiments. Many of the previously published studies that focused on the gas-phase time-resolved dynamics of thionated uracils after UV excitation relied on information from solution phase spectroscopy to determine the excitation energies. This is not an optimal strategy as solvents alter the absorption spec- trum and, hence, there is no guarantee that liquid-phase spectra resemble the gas-phase spectra. Therefore, I measured the UV-absorption spectra of all three thionated uracils to provide a gas-phase reference and, in combination with calculations, we determined the excited states involved in the transitions.
In contrast to the UV absorption, the literature on the x-ray spectroscopy of thionated uracil is sparse. Thus, we measured static photoelectron, Auger-Meitner and x-ray absorption spectra on the sulfur L edge before or parallel to the time-resolved experiments we performed at FLASH (DESY, Hamburg). In addition, (so far unpublished) measurements were performed at the synchrotron SOLEIL (France) which have been included in this thesis and show the spin-orbit splitting of the S 2p photoline and its satellite which was not observed at the free-electron laser.
The relaxation of 2-thiouracil has been studied extensively in recent years with ultrafast visible and ultraviolet methods showing the ultrafast nature of the molecular process after photoexcitation. Ultrafast spectroscopy probing the core-level electrons provides a complementary approach to common optical ultrafast techniques. The method inherits its local sensitivity from the strongly localised core electrons. The core energies and core-valence transitions are strongly affected by local valence charge and geometry changes, and past studies have utilised this sensitivity to investigate the molecular process reflected by the ultrafast dynamics. We have built an apparatus that provides the requirements to perform time-resolved x-ray spectroscopy on molecules in the gas phase. With the apparatus, we performed UV-pump x-ray-probe electron spectroscopy on the S 2p edge of 2-thiouracil using the free-electron laser FLASH2. While the UV triggers the relaxation dynamics, the x-ray probes the single sulfur atom inside the molecule. I implemented photoline self-referencing for the photoelectron spectral analysis. This minimises the spectral jitter of the FEL, which is due to the underlying self-amplified spontaneous emission (SASE) process. With this approach, we were not only able to study dynamical changes in the binding energy of the electrons but also to detect an oscillatory behaviour in the shift of the observed photoline, which we associate with non-adiabatic dynamics involving several electronic states. Moreover, we were able to link the UV-induced shift in binding energy to the local charge flow at the sulfur which is directly connected to the electronic state. Furthermore, the analysis of the Auger-Meitner electrons shows that energy shifts observed at early stages of the photoinduced relaxation are related to the geometry change in the molecule. More specifically, the observed increase in kinetic energy of the Auger-Meitner electrons correlates with a previously predicted C=S bond stretch.
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.
Cosmic rays (CRs) are a ubiquitous and an important component of astrophysical environments such as the interstellar medium (ISM) and intracluster medium (ICM). Their plasma physical interactions with electromagnetic fields strongly influence their transport properties. Effective models which incorporate the microphysics of CR transport are needed to study the effects of CRs on their surrounding macrophysical media. Developing such models is challenging because of the conceptional, length-scale, and time-scale separation between the microscales of plasma physics and the macroscales of the environment. Hydrodynamical theories of CR transport achieve this by capturing the evolution of CR population in terms of statistical moments. In the well-established one-moment hydrodynamical model for CR transport, the dynamics of the entire CR population are described by a single statistical quantity such as the commonly used CR energy density. In this work, I develop a new hydrodynamical two-moment theory for CR transport that expands the well-established hydrodynamical model by including the CR energy flux as a second independent hydrodynamical quantity. I detail how this model accounts for the interaction between CRs and gyroresonant Alfvén waves. The small-scale magnetic fields associated with these Alfvén waves scatter CRs which fundamentally alters CR transport along large-scale magnetic field lines. This leads to the effects of CR streaming and diffusion which are both captured within the presented hydrodynamical theory. I use an Eddington-like approximation to close the hydrodynamical equations and investigate the accuracy of this closure-relation by comparing it to high-order approximations of CR transport. In addition, I develop a finite-volume scheme for the new hydrodynamical model and adapt it to the moving-mesh code Arepo. This scheme is applied using a simulation of a CR-driven galactic wind. I investigate how CRs launch the wind and perform a statistical analysis of CR transport properties inside the simulated circumgalactic medium (CGM). I show that the new hydrodynamical model can be used to explain the morphological appearance of a particular type of radio filamentary structures found inside the central molecular zone (CMZ). I argue that these harp-like features are synchrotron-radiating CRs which are injected into braided magnetic field lines by a point-like source such as a stellar wind of a massive star or a pulsar. Lastly, I present the finite-volume code Blinc that uses adaptive mesh refinement (AMR) techniques to perform simulations of radiation and magnetohydrodynamics (MHD). The mesh of Blinc is block-structured and represented in computer memory using a graph-based approach. I describe the implementation of the mesh graph and how a diffusion process is employed to achieve load balancing in parallel computing environments. Various test problems are used to verify the accuracy and robustness of the employed numerical algorithms.
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.
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.
The complex hierarchical structure of bone undergoes a lifelong remodeling process, where it adapts to mechanical needs. Hereby, bone resorption by osteoclasts and bone formation by osteoblasts have to be balanced to sustain a healthy and stable organ. Osteocytes orchestrate this interplay by sensing mechanical strains and translating them into biochemical signals. The osteocytes are located in lacunae and are connected to one another and other bone cells via cell processes through small channels, the canaliculi. Lacunae and canaliculi form a network (LCN) of extracellular spaces that is able to transport ions and enables cell-to-cell communication. Osteocytes might also contribute to mineral homeostasis by direct interactions with the surrounding matrix. If the LCN is acting as a transport system, this should be reflected in the mineralization pattern. The central hypothesis of this thesis is that osteocytes are actively changing their material environment. Characterization methods of material science are used to achieve the aim of detecting traces of this interaction between osteocytes and the extracellular matrix. First, healthy murine bones were characterized. The properties analyzed were then compared with three murine model systems: 1) a loading model, where a bone of the mouse was loaded during its life time; 2) a healing model, where a bone of the mouse was cut to induce a healing response; and 3) a disease model, where the Fbn1 gene is dysfunctional causing defects in the formation of the extracellular tissue.
The measurement strategy included routines that make it possible to analyze the organization of the LCN and the material components (i.e., the organic collagen matrix and the mineral particles) in the same bone volumes and compare the spatial distribution of different data sets. The three-dimensional network architecture of the LCN is visualized by confocal laser scanning microscopy (CLSM) after rhodamine staining and is then subsequently quantified. The calcium content is determined via quantitative backscattered electron imaging (qBEI), while small- and wide-angle X-ray scattering (SAXS and WAXS) are employed to determine the thickness and length of local mineral particles.
First, tibiae cortices of healthy mice were characterized to investigate how changes in LCN architecture can be attributed to interactions of osteocytes with the surrounding bone matrix. The tibial mid-shaft cross-sections showed two main regions, consisting of a band with unordered LCN surrounded by a region with ordered LCN. The unordered region is a remnant of early bone formation and exhibited short and thin mineral particles. The surrounding, more aligned bone showed ordered and dense LCN as well as thicker and longer mineral particles. The calcium content was unchanged between the two regions.
In the mouse loading model, the left tibia underwent two weeks of mechanical stimulation, which results in increased bone formation and decreased resorption in skeletally mature mice. Here the specific research question addressed was how do bone material characteristics change at (re)modeling sites? The new bone formed in response to mechanical stimulation showed similar properties in terms of the mineral particles, like the ordered calcium region but lower calcium content compared to the right, non-loaded control bone of the same mice. There was a clear, recognizable border between mature and newly formed bone. Nevertheless, some canaliculi went through this border connecting the LCN of mature and newly formed bone.
Additionally, the question should be answered whether the LCN topology and the bone matrix material properties adapt to loading. Although, mechanically stimulated bones did not show differences in calcium content compared to controls, different correlations were found between the local LCN density and the local Ca content depending on whether the bone was loaded or not. These results suggest that the LCN may serve as a mineral reservoir.
For the healing model, the femurs of mice underwent an osteotomy, stabilized with an external fixator and were allowed to heal for 21 days. Thus, the spatial variations in the LCN topology with mineral properties within different tissue types and their interfaces, namely calcified cartilage, bony callus and cortex, could be simultaneously visualized and compared in this model. All tissue types showed structural differences across multiple length scales. Calcium content increased and became more homogeneous from calcified cartilage to bony callus to lamellar cortical bone. The degree of LCN organization increased as well, while the lacunae became smaller, as did the lacunar density between these different tissue types that make up the callus. In the calcified cartilage, the mineral particles were short and thin. The newly formed callus exhibited thicker mineral particles, which still had a low degree of orientation. While most of the callus had a woven-like structure, it also served as a scaffold for more lamellar tissue at the edges. The lamelar bone callus showed thinner mineral particles, but a higher degree of alignment in both, mineral particles and the LCN. The cortex showed the highest values for mineral length, thickness and degree of orientation. At the same time, the lacunae number density was 34% lower and the lacunar volume 40% smaller compared to bony callus. The transition zone between cortical and callus regions showed a continuous convergence of bone mineral properties and lacunae shape. Although only a few canaliculi connected callus and the cortical region, this indicates that communication between osteocytes of both tissues should be possible. The presented correlations between LCN architecture and mineral properties across tissue types may suggest that osteocytes have an active role in mineralization processes of healing.
A mouse model for the disease marfan syndrome, which includes a genetic defect in the fibrillin-1 gene, was investigated. In humans, Marfan syndrome is characterized by a range of clinical symptoms such as long bone overgrowth, loose joints, reduced bone mineral density, compromised bone microarchitecture, and increased fracture rates. Thus, fibrillin-1 seems to play a role in the skeletal homeostasis. Therefore, the present work studied how marfan syndrome alters LCN architecture and the surrounding bone matrix. The mice with marfan syndrome showed longer tibiae than their healthy littermates from an age of seven weeks onwards. In contrast, the cortical development appeared retarded, which was observed across all measured characteristics, i. e. lower endocortical bone formation, looser and less organized lacuno-canalicular network, less collagen orientation, thinner and shorter mineral particles.
In each of the three model systems, this study found that changes in the LCN architecture spatially correlated with bone matrix material parameters. While not knowing the exact mechanism, these results provide indications that osteocytes can actively manipulate a mineral reservoir located around the canaliculi to make a quickly accessible contribution to mineral homeostasis. However, this interaction is most likely not one-sided, but could be understood as an interplay between osteocytes and extra-cellular matrix, since the bone matrix contains biochemical signaling molecules (e.g. non-collagenous proteins) that can change osteocyte behavior. Bone (re)modeling can therefore not only be understood as a method for removing defects or adapting to external mechanical stimuli, but also for increasing the efficiency of possible osteocyte-mineral interactions during bone homeostasis. With these findings, it seems reasonable to consider osteocytes as a target for drug development related to bone diseases that cause changes in bone composition and mechanical properties. It will most likely require the combined effort of materials scientists, cell biologists, and molecular biologists to gain a deeper understanding of how bone cells respond to their material environment.
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.
Isoflux tension propagation (IFTP) theory and Langevin dynamics (LD) simulations are employed to study the dynamics of channel-driven polymer translocation in which a polymer translocates into a narrow channel and the monomers in the channel experience a driving force fc. In the high driving force limit, regardless of the channel width, IFTP theory predicts τ ∝ f βc for the translocation time, where β = −1 is the force scaling exponent. Moreover, LD data show that for a very narrow channel fitting only a single file of monomers, the entropic force due to the subchain inside the channel does not play a significant role in the translocation dynamics and the force exponent β = −1 regardless of the force magnitude. As the channel width increases the number of possible spatial configurations of the subchain inside the channel becomes significant and the resulting entropic force causes the force exponent to drop below unity.
We consider a one-dimensional oscillatory medium with a coupling through a diffusive linear field. In the limit of fast diffusion this setup reduces to the classical Kuramoto–Battogtokh model. We demonstrate that for a finite diffusion stable chimera solitons, namely localized synchronous domain in an infinite asynchronous environment, are possible. The solitons are stable also for finite density of oscillators, but in this case they sway with a nearly constant speed. This finite-density-induced motility disappears in the continuum limit, as the velocity of the solitons is inverse proportional to the density. A long-wave instability of the homogeneous asynchronous state causes soliton turbulence, which appears as a sequence of soliton mergings and creations. As the instability of the asynchronous state becomes stronger, this turbulence develops into a spatio-temporal intermittency.
Anomalous diffusion or, more generally, anomalous transport, with nonlinear dependence of the mean-squared displacement on the measurement time, is ubiquitous in nature. It has been observed in processes ranging from microscopic movement of molecules to macroscopic, large-scale paths of migrating birds. Using data from multiple empirical systems, spanning 12 orders of magnitude in length and 8 orders of magnitude in time, we employ a method to detect the individual underlying origins of anomalous diffusion and transport in the data. This method decomposes anomalous transport into three primary effects: long-range correlations (“Joseph effect”), fat-tailed probability density of increments (“Noah effect”), and nonstationarity (“Moses effect”). We show that such a decomposition of real-life data allows us to infer nontrivial behavioral predictions and to resolve open questions in the fields of single-particle tracking in living cells and movement ecology.
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.
X-rays are integral to furthering our knowledge of exoplanetary systems. In this work we discuss the use of X-ray observations to understand star-planet interac- tions, mass-loss rates of an exoplanet’s atmosphere and the study of an exoplanet’s atmospheric components using future X-ray spectroscopy.
The low-mass star GJ 1151 was reported to display variable low-frequency radio emission, which is an indication of coronal star-planet interactions with an unseen exoplanet. In chapter 5 we report the first X-ray detection of GJ 1151’s corona based on XMM-Newton data. Averaged over the observation, we detect the star with a low coronal temperature of 1.6 MK and an X-ray luminosity of LX = 5.5 × 1026 erg/s. This is compatible with the coronal assumptions for a sub-Alfvénic star- planet interaction origin of the observed radio signals from this star.
In chapter 6, we aim to characterise the high-energy environment of known ex- oplanets and estimate their mass-loss rates. This work is based on the soft X-ray instrument on board the Spectrum Roentgen Gamma (SRG) mission, eROSITA, along with archival data from ROSAT, XMM-Newton, and Chandra. We use these four X-ray source catalogues to derive X-ray luminosities of exoplanet host stars in the 0.2-2 keV energy band. A catalogue of the mass-loss rates of 287 exoplan- ets is presented, with 96 of these planets characterised for the first time using new eROSITA detections. Of these first time detections, 14 are of transiting exoplanets that undergo irradiation from their host stars that is of a level known to cause ob- servable evaporation signals in other systems, making them suitable for follow-up observations.
In the next generation of space observatories, X-ray transmission spectroscopy of an exoplanet’s atmosphere will be possible, allowing for a detailed look into the atmospheric composition of these planets. In chapter 7, we model sample spectra using a toy model of an exoplanetary atmosphere to predict what exoplanet transit observations with future X-ray missions such as Athena will look like. We then estimate the observable X-ray transmission spectrum for a typical Hot Jupiter-type exoplanet, giving us insights into the advances in X-ray observations of exoplanets in the decades to come.
Elementary particle physics is a contemporary topic in science that is slowly being integrated into high-school education. These new implementations are challenging teachers’ professional knowledge worldwide. Therefore, physics education research is faced with two important questions, namely, how can particle physics be integrated in high-school physics curricula and how best to support teachers in enhancing their professional knowledge on particle physics. This doctoral research project set up to provide better guidelines for answering these two questions by conducting three studies on high-school particle physics education.
First, an expert concept mapping study was conducted to elicit experts’ expectations on what high-school students should learn about particle physics. Overall, 13 experts in particle physics, computing, and physics education participated in 9 concept mapping rounds. The broad knowledge base of the experts ensured that the final expert concept map covers all major particle physics aspects. Specifically, the final expert concept map includes 180 concepts and examples, connected with 266 links and crosslinks. Among them are also several links to students’ prior knowledge in topics such as mechanics and thermodynamics. The high interconnectedness of the concepts shows possible opportunities for including particle physics as a context for other curricular topics. As such, the resulting expert concept map is showcased as a well-suited tool for teachers to scaffold their instructional practice.
Second, a review of 27 high-school physics curricula was conducted. The review uncovered which concepts related to particle physics can be identified in most curricula. Each curriculum was reviewed by two reviewers that followed a codebook with 60 concepts related to particle physics. The analysis showed that most curricula mention cosmology, elementary particles, and charges, all of which are considered theoretical particle physics concepts. None of the experimental particle physics concepts appeared in more than half of the reviewed curricula. Additional analysis was done on two curricular subsets, namely curricula with and curricula without an explicit particle physics chapter. Curricula with an explicit particle physics chapter mention several additional explicit particle physics concepts, namely the Standard Model of particle physics, fundamental interactions, antimatter research, and particle accelerators. The latter is an example of experimental particle physics concepts. Additionally, the analysis revealed that, overall, most curricula include Nature of Science and history of physics, albeit both are typically used as context or as a tool for teaching, respectively.
Third, a Delphi study was conducted to investigate stakeholders’ expectations regarding what teachers should learn in particle physics professional development programmes. Over 100 stakeholders from 41 countries represented four stakeholder groups, namely physics education researchers, research scientists, government representatives, and high-school teachers. The study resulted in a ranked list of the 13 most important topics to be included in particle physics professional development programmes. The highest-ranked topics are cosmology, the Standard Model, and real-life applications of particle physics. All stakeholder groups agreed on the overall ranking of the topics. While the highest-ranked topics are again more theoretical, stakeholders also expect teachers to learn about experimental particle physics topics, which are ranked as medium importance topics.
The three studies addressed two research aims of this doctoral project. The first research aim was to explore to what extent particle physics is featured in high-school physics curricula. The comparison of the outcomes of the curricular review and the expert concept map showed that curricula cover significantly less than what experts expect high-school students to learn about particle physics. For example, most curricula do not include concepts that could be classified as experimental particle physics. However, the strong connections between the different concept show that experimental particle physics can be used as context for theoretical particle physics concepts, Nature of Science, and other curricular topics. In doing so, particle physics can be introduced in classrooms even though it is not (yet) explicitly mentioned in the respective curriculum.
The second research aim was to identify which aspects of content knowledge teachers are expected to learn about particle physics. The comparison of the Delphi study results to the outcomes of the curricular review and the expert concept map showed that stakeholders generally expect teachers to enhance their school knowledge as defined by the curricula. Furthermore, teachers are also expected to enhance their deeper school knowledge by learning how to connect concepts from their school knowledge to other concepts in particle physics and beyond. As such, professional development programmes that focus on enhancing teachers’ school knowledge and deeper school knowledge best support teachers in building relevant context in their instruction.
Overall, this doctoral research project reviewed the current state of high-school particle physics education and provided guidelines for future enhancements of the particle physics content in high-school student and teacher education. The outcomes of the project support further implementations of particle physics in high-school education both as explicit content and as context for other curricular topics. Furthermore, the mixed-methods approach and the outcomes of this research project lead to several implications for professional development programmes and science education research, that are discussed in the final chapters of this dissertation.
Extending synchrotron X-ray refraction techniques to the quantitative analysis of metallic materials
(2022)
In this work, two X-ray refraction based imaging methods, namely, synchrotron X-ray refraction radiography (SXRR) and synchrotron X-ray refraction computed tomography (SXRCT), are applied to analyze quantitatively cracks and porosity in metallic materials. SXRR and SXRCT make use of the refraction of X-rays at inner surfaces of the material, e.g., the surfaces of cracks and pores, for image contrast. Both methods are, therefore, sensitive to smaller defects than their absorption based counterparts X-ray radiography and computed tomography. They can detect defects of nanometric size. So far the methods have been applied to the analysis of ceramic materials and fiber reinforced plastics. The analysis of metallic materials requires higher photon energies to achieve sufficient X-ray transmission due to their higher density. This causes smaller refraction angles and, thus, lower image contrast because the refraction index depends on the photon energy. Here, for the first time, a conclusive study is presented exploring the possibility to apply SXRR and SXRCT to metallic materials. It is shown that both methods can be optimized to overcome the reduced contrast due to smaller refraction angles. Hence, the only remaining limitation is the achievable X-ray transmission which is common to all X-ray imaging methods. Further, a model for the quantitative analysis of the inner surfaces is presented and verified.
For this purpose four case studies are conducted each posing a specific challenge to the imaging task. Case study A investigates cracks in a coupon taken from an aluminum weld seam. This case study primarily serves to verify the model for quantitative analysis and prove the sensitivity to sub-resolution features. In case study B, the damage evolution in an aluminum-based particle reinforced metal-matrix composite is analyzed. Here, the accuracy and repeatability of subsequent SXRR measurements is investigated showing that measurement errors of less than 3 % can be achieved. Further, case study B marks the fist application of SXRR in combination with in-situ tensile loading. Case study C is out of the highly topical field of additive manufacturing. Here, porosity in additively manufactured Ti-Al6-V4 is analyzed with a special interest in the pore morphology. A classification scheme based on SXRR measurements is devised which allows to distinguish binding defects from keyhole pores even if the defects cannot be spatially resolved. In case study D, SXRCT is applied to the analysis of hydrogen assisted cracking in steel. Due to the high X-ray attenuation of steel a comparatively high photonenergy of 50 keV is required here. This causes increased noise and lower contrast in the data compared to the other case studies. However, despite the lower data quality a quantitative analysis of the occurance of cracks in dependence of hydrogen content and applied mechanical load is possible.
Organic solar cells (OSCs), in recent years, have shown high efficiencies through the development of novel non-fullerene acceptors (NFAs). Fullerene derivatives have been the centerpiece of the accepting materials used throughout organic photovoltaic (OPV) research. However, since 2015 novel NFAs have been a game-changer and have overtaken fullerenes. However, the current understanding of the properties of NFAs for OPV is still relatively limited and critical mechanisms defining the performance of OPVs are still topics of debate.
In this thesis, attention is paid to understanding reduced-Langevin recombination with respect to the device physics properties of fullerene and non-fullerene systems. The work is comprised of four closely linked studies. The first is a detailed exploration of the fill factor (FF) expressed in terms of transport and recombination properties in a comparison of fullerene and non-fullerene acceptors. We investigated the key reason behind the reduced FF in the NFA (ITIC-based) devices which is faster non-geminate recombination relative to the fullerene (PCBM[70]-based) devices. This is then followed by a consideration of a newly synthesized NFA Y-series derivative which exhibits the highest power conversion efficiency for OSC at the time. Such that in the second study, we illustrated the role of disorder on the non-geminate recombination and charge extraction of thick NFA (Y6-based) devices. As a result, we enhanced the FF of thick PM6:Y6 by reducing the disorder which leads to suppressing the non-geminate recombination toward non-Langevin system. In the third work, we revealed the reason behind thickness independence of the short circuit current of PM6:Y6 devices, caused by the extraordinarily long diffusion length of Y6. The fourth study entails a broad comparison of a selection of fullerene and non-fullerene blends with respect to charge generation efficiency and recombination to unveil the importance of efficient charge generation for achieving reduced recombination.
I employed transient measurements such as Time Delayed Collection Field (TDCF), Resistance dependent Photovoltage (RPV), and steady-state techniques such as Bias Assisted Charge Extraction (BACE), Temperature-Dependent Space Charge Limited Current (T-SCLC), Capacitance-Voltage (CV), and Photo-Induce Absorption (PIA), to analyze the OSCs.
The outcomes in this thesis together draw a complex picture of multiple factors that affect reduced-Langevin recombination and thereby the FF and overall performance. This provides a suitable platform for identifying important parameters when designing new blend systems. As a result, we succeeded to improve the overall performance through enhancing the FF of thick NFA device by adjustment of the amount of the solvent additive in the active blend solution. It also highlights potentially critical gaps in the current experimental understanding of fundamental charge interaction and recombination dynamics.
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.
Sprache
Englisch
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed systems. We here augment recently proposed machine-learning techniques for decoding anomalous-diffusion data to include an uncertainty estimate in addition to the predicted output. To avoid the Black-Box-Problem a Bayesian-Deep-Learning technique named Stochastic-Weight-Averaging-Gaussian is used to train models for both the classification of the diffusionmodel and the regression of the anomalous diffusion exponent of single-particle-trajectories. Evaluating their performance, we find that these models can achieve a wellcalibrated error estimate while maintaining high prediction accuracies. In the analysis of the output uncertainty predictions we relate these to properties of the underlying diffusion models, thus providing insights into the learning process of the machine and the relevance of the output.
Anomalous-diffusion, the departure of the spreading dynamics of diffusing particles from the traditional law of Brownian-motion, is a signature feature of a large number of complex soft-matter and biological systems. Anomalous-diffusion emerges due to a variety of physical mechanisms, e.g., trapping interactions or the viscoelasticity of the environment. However, sometimes systems dynamics are erroneously claimed to be anomalous, despite the fact that the true motion is Brownian—or vice versa. This ambiguity in establishing whether the dynamics as normal or anomalous can have far-reaching consequences, e.g., in predictions for reaction- or relaxation-laws. Demonstrating that a system exhibits normal- or anomalous-diffusion is highly desirable for a vast host of applications. Here, we present a criterion for anomalous-diffusion based on the method of power-spectral analysis of single trajectories. The robustness of this criterion is studied for trajectories of fractional-Brownian-motion, a ubiquitous stochastic process for the description of anomalous-diffusion, in the presence of two types of measurement errors. In particular, we find that our criterion is very robust for subdiffusion. Various tests on surrogate data in absence or presence of additional positional noise demonstrate the efficacy of this method in practical contexts. Finally, we provide a proof-of-concept based on diverse experiments exhibiting both normal and anomalous-diffusion.
How do different reset protocols affect ergodicity of a diffusion process in single-particle-tracking experiments? We here address the problem of resetting of an arbitrary stochastic anomalous-diffusion process (ADP) from the general mathematical points of view and assess ergodicity of such reset ADPs for an arbitrary resetting protocol. The process of stochastic resetting describes the events of the instantaneous restart of a particle’s motion via randomly distributed returns to a preset initial position (or a set of those). The waiting times of such resetting events obey the Poissonian, Gamma, or more generic distributions with specified conditions regarding the existence of moments. Within these general approaches, we derive general analytical results and support them by computer simulations for the behavior of the reset mean-squared displacement (MSD), the new reset increment-MSD (iMSD), and the mean reset time-averaged MSD (TAMSD). For parental nonreset ADPs with the MSD(t)∝ tμ we find a generic behavior and a switch of the short-time growth of the reset iMSD and mean reset TAMSDs from ∝ _μ for subdiffusive to ∝ _1 for superdiffusive reset ADPs. The critical condition for a reset ADP that recovers its ergodicity is found to be more general than that for the nonequilibrium stationary state, where obviously the iMSD and the mean TAMSD are equal. The consideration of the new statistical quantifier, the iMSD—as compared to the standard MSD—restores the ergodicity of an arbitrary reset ADP in all situations when the μth moment of the waiting-time distribution of resetting events is finite. Potential applications of these new resetting results are, inter alia, in the area of biophysical and soft-matter systems.
Science education researchers have developed a refined understanding of the structure of science teachers’ pedagogical content knowledge (PCK), but how to develop applicable and situation-adequate PCK remains largely unclear. A potential problem lies in the diverse conceptualisations of the PCK used in PCK research. This study sought to systematize existing science education research on PCK through the lens of the recently proposed refined consensus model (RCM) of PCK. In this review, the studies’ approaches to investigating PCK and selected findings were characterised and synthesised as an overview comparing research before and after the publication of the RCM. We found that the studies largely employed a qualitative case-study methodology that included specific PCK models and tools. However, in recent years, the studies focused increasingly on quantitative aspects. Furthermore, results of the reviewed studies can mostly be integrated into the RCM. We argue that the RCM can function as a meaningful theoretical lens for conceptualizing links between teaching practice and PCK development by proposing pedagogical reasoning as a mechanism and/or explanation for PCK development in the context of teaching practice.
Following excited-state chemical shifts in molecular ultrafast x-ray photoelectron spectroscopy
(2022)
The conversion of photon energy into other energetic forms in molecules is accompanied by charge moving on ultrafast timescales. We directly observe the charge motion at a specific site in an electronically excited molecule using time-resolved x-ray photoelectron spectroscopy (TR-XPS). We extend the concept of static chemical shift from conventional XPS by the excited-state chemical shift (ESCS), which is connected to the charge in the framework of a potential model. This allows us to invert TR-XPS spectra to the dynamic charge at a specific atom. We demonstrate the power of TR-XPS by using sulphur 2p-core-electron-emission probing to study the UV-excited dynamics of 2-thiouracil. The method allows us to discover that a major part of the population relaxes to the molecular ground state within 220–250 fs. In addition, a 250-fs oscillation, visible in the kinetic energy of the TR-XPS, reveals a coherent exchange of population among electronic states.
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.
Poly(vinylidene fluoride) (PVDF)-based homo-, co- and ter-polymers are well-known for their ferroelectric and relaxor-ferroelectric properties. Their semi-crystalline morphology consists of crystalline and amorphous phases, plus interface regions in between, and governs the relevant electro-active properties. In this work, the influence of chemical, thermal and mechanical treatments on the structure and morphology of PVDF-based polymers and on the related ferroelectric/relaxor-ferroelectric properties is investigated. Polymer films were prepared in different ways and subjected to various treatments such as annealing, quenching and stretching. The resulting changes in the transitions and relaxations of the polymer samples were studied by means of dielectric, thermal, mechanical and optical techniques. In particular, the origin(s) behind the mysterious mid-temperature transition (T_{mid}) that is observed in all PVDF-based polymers was assessed. A new hypothesis is proposed to describe the T_{mid} transition as a result of multiple processes taking place within the temperature range of the transition. The contribution of the individual processes to the observed overall transition depends on both the chemical structure of the monomer units and the processing conditions which also affect the melting transition. Quenching results in a decrease of the overall crystallinity and in smaller crystallites. On samples quenched after annealing, notable differences in the fractions of different crystalline phases have been observed when compared to samples that had been slowly cooled. Stretching of poly(vinylidene fluoride-tetrafluoroethylene) (P(VDF-TFE)) films causes an increase in the fraction of the ferroelectric β-phase with simultaneous increments in the melting point (T_m) and the crystallinity (\chi_c) of the copolymer. While an increase in the stretching temperature does not have a profound effect on the amount of the ferroelectric phase, its stability appears to improve.
Measurements of the non-linear dielectric permittivity \varepsilon_2^\prime in a poly(vinylidenefluoride-trifluoroethylene-chlorofluoroethylene) (P(VDF-TrFE- CFE)) relaxor-ferroelectric (R-F) terpolymer reveal peaks at 30 and 80 °C that cannot be identified in conventional dielectric spectroscopy. The former peak is associated with T_{mid}\ and may help to understand the non-zero \varepsilon_2^\prime values that are found for the paraelectric terpolymer phase. The latter peak can also be observed during cooling of P(VDF-TrFE) copolymer samples at 100 °C and is due to conduction processes and space-charge polarization as a result of the accumulation of real charges at the electrode-sample interface. Annealing lowers the Curie-transition temperature of the terpolymer as a consequence of its smaller ferroelectric-phase fraction, which by default exists even in terpolymers with relatively high CFE content. Changes in the transition temperatures are in turn related to the behavior of the hysteresis curves observed on differently heat-treated samples. Upon heating, the hysteresis curves evolve from those known for a ferroelectric to those of a typical relaxor-ferroelectric material. Comparing dielectric-hysteresis loops obtained at various temperatures, we find that annealed terpolymer films show higher electric-displacement values and lower coercive fields than the non-annealed samples − irrespective of the measurement temperature − and also exhibit ideal relaxor-ferroelectric behavior at ambient temperatures, which makes them excellent candidates for related applications at or near room temperature. However, non-annealed films − by virtue of their higher ferroelectric activity − show a larger and more stable remanent polarization at room temperature, while annealed samples need to be poled below 0 °C to induce a well-defined polarization. Overall, by modifying the three phases in PVDF-based polymers, it has been demonstrated how the preparation steps and processing conditions can be tailored to achieve the desired properties that are optimal for specific applications.
Inverted perovskite solar cells still suffer from significant non-radiative recombination losses at the perovskite surface and across the perovskite/C₆₀ interface, limiting the future development of perovskite-based single- and multi-junction photovoltaics. Therefore, more effective inter- or transport layers are urgently required. To tackle these recombination losses, we introduce ortho-carborane as an interlayer material that has a spherical molecular structure and a three-dimensional aromaticity. Based on a variety of experimental techniques, we show that ortho-carborane decorated with phenylamino groups effectively passivates the perovskite surface and essentially eliminates the non-radiative recombination loss across the perovskite/C₆₀ interface with high thermal stability. We further demonstrate the potential of carborane as an electron transport material, facilitating electron extraction while blocking holes from the interface. The resulting inverted perovskite solar cells deliver a power conversion efficiency of over 23% with a low non-radiative voltage loss of 110 mV, and retain >97% of the initial efficiency after 400 h of maximum power point tracking. Overall, the designed carborane based interlayer simultaneously enables passivation, electron-transport and hole-blocking and paves the way toward more efficient and stable perovskite solar cells.
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.
The Antarctic ice sheet is the largest freshwater reservoir worldwide. If it were to melt completely, global sea levels would rise by about 58 m. Calculation of projections of the Antarctic contribution to sea level rise under global warming conditions is an ongoing effort which
yields large ranges in predictions. Among the reasons for this are uncertainties related to the physics of ice sheet modeling. These
uncertainties include two processes that could lead to runaway ice retreat: the Marine Ice Sheet Instability (MISI), which causes rapid grounding line retreat on retrograde bedrock, and the Marine Ice Cliff Instability (MICI), in which tall ice cliffs become unstable and calve off, exposing even taller ice cliffs.
In my thesis, I investigated both marine instabilities (MISI and MICI) using the Parallel Ice Sheet Model (PISM), with a focus on MICI.
The current generation of ground-based instruments has rapidly extended the limits of the range accessible to us with very-high-energy (VHE) gamma-rays, and more than a hundred sources have now been detected in the Milky Way. These sources represent only the tip of the iceberg, but their number has reached a level that allows population studies. In this work, a model of the global population of VHE gamma-ray sources based on the most comprehensive census of Galactic sources in this energy regime, the H.E.S.S. Galactic plane survey (HGPS), will be presented. A population synthesis approach was followed in the construction of the model. Particular attention was paid to correcting for the strong observational bias inherent in the sample of detected sources. The methods developed for estimating the model parameters have been validated with extensive Monte Carlo simulations and will be shown to provide unbiased estimates of the model parameters. With these methods, five models for different spatial distributions of sources have been constructed. To test the validity of these models, their predictions for the composition of sources within the sensitivity range of the HGPS are compared with the observed sample. With one exception, similar results are obtained for all spatial distributions, showing that the observed longitude profile and the source distribution over photon flux are in fair agreement with observation. Regarding the latitude profile and the source distribution over angular extent, it becomes apparent that the model needs to be further adjusted to bring its predictions in agreement with observation. Based on the model, predictions of the global properties of the Galactic population of VHE gamma-ray sources and the prospects of the Cherenkov Telescope Array (CTA) will be presented.
CTA will significantly increase our knowledge of VHE gamma-ray sources by lowering the threshold for source detection, primarily through a larger detection area compared to current-generation instruments. In ground-based gamma-ray astronomy, the sensitivity of an instrument depends strongly, in addition to the detection area, on the ability to distinguish images of air showers produced by gamma-rays from those produced by cosmic rays, which are a strong background. This means that the number of detectable sources depends on the background rejection algorithm used and therefore may also be increased by improving the performance of such algorithms. In this context, in addition to the population model, this work presents a study on the application of deep-learning techniques to the task of gamma-hadron separation in the analysis of data from ground-based gamma-ray instruments. Based on a systematic survey of different neural-network architectures, it is shown that robust classifiers can be constructed with competitive performance compared to the best existing algorithms. Despite the broad coverage of neural-network architectures discussed, only part of the potential offered by the
application of deep-learning techniques to the analysis of gamma-ray data is exploited in the context of this study. Nevertheless, it provides an important basis for further research on this topic.
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.
Halide perovskites are a class of novel photovoltaic materials that have recently attracted much attention in the photovoltaics research community due to their highly promising optoelectronic properties, including large absorption coefficients and long carrier lifetimes. The charge carrier mobility of halide perovskites is investigated in this thesis by THz spectroscopy, which is a contact-free technique that yields the intra-grain sum mobility of electrons and holes
in a thin film.
The polycrystalline halide perovskite thin films, provided from Potsdam University, show moderate mobilities in the range from 21.5 to 33.5 cm2V-1s-1. It is shown in this work that the room temperature mobility is limited by charge carrier scattering at polar optical phonons. The mobility at low temperature is likely to be limited by scattering at charged and neutral impurities at impurity concentration N=1017-1018 cm-3. Furthermore, it is shown that exciton formation
may decrease the mobility at low temperatures. Scattering at acoustic phonons can be neglected at both low and room temperatures. The analysis of mobility spectra over a broad range of temperatures for perovskites with various cation compounds shows that cations have a minor impact on charge carrier mobility.
The low-dimensional thin films of quasi-2D perovskite with different numbers of [PbI6]4−sheets (n=2-4) alternating with long organic spacer molecules were provided by S. Zhang from Potsdam University. They exhibit mobilities in the range from 3.7 to 8 cm2V-1s-1. A clear
decrease of mobility is observed with decrease in number of metal-halide sheets n, which likely arises from charge carrier confinement within metal-halide layers. Modelling the measured THz mobility with the modified Drude-Smith model yields localization length from 0.9 to 3.7 nm, which agrees well on the thicknesses of the metal-halide layers. Additionally, the mobilities are found to be dependent on the orientation of the layers. The charge carrier dynamics is also
dependent on the number of metal-halide sheets n. For the thin films with n =3-4 the dynamics is similar to the 3D MHPs. However, the thin film with n = 2 shows clearly different dynamics, where the signs of exciton formation are observed within 390 fs timeframe after
photoexcitation.
Also, the charge carrier dynamics of CsPbI3 perovskite nanocrystals was investigated, in particular the effect of post treatments on the charge carrier transport.
We use ultrafast x-ray diffraction to investigate the effect of expansive phononic and contractive magnetic stress driving the picosecond strain response of a metallic perovskite SrRuO3 thin film upon femtosecond laser excitation. We exemplify how the anisotropic bulk equilibrium thermal expansion can be used to predict the response of the thin film to ultrafast deposition of energy. It is key to consider that the laterally homogeneous laser excitation changes the strain response compared to the near-equilibrium thermal expansion because the balanced in-plane stresses suppress the Poisson stress on the picosecond timescale. We find a very large negative Grüneisen constant describing the large contractive stress imposed by a small amount of energy in the spin system. The temperature and fluence dependence of the strain response for a double-pulse excitation scheme demonstrates the saturation of the magnetic stress in the high-fluence regime.
The High Energy Stereoscopic System (H.E.S.S.) is an array of five imaging atmospheric Cherenkov telescopes located in the Khomas Highland of Namibia. H.E.S.S. operates in a wide energy range from several tens of GeV to several tens of TeV, reaching the best sensitivity around 1 TeV or at lower energies. However, there are many important topics – such as the search for Galactic PeVatrons, the study of gamma-ray production scenarios for sources (hadronic vs. leptonic), EBL absorption studies – which require good sensitivity at energies above 10 TeV. This work aims at improving the sensitivity of H.E.S.S. and increasing the gamma-ray statistics at high energies. The study investigates an enlargement of the H.E.S.S. effective field of view using events with larger offset angles in the analysis. The greatest challenges in the analysis of large-offset events are a degradation of the reconstruction accuracy and a rise of the background rate as the offset angle increases. The more sophisticated direction reconstruction method (DISP) and improvements to the standard background rejection technique, which by themselves are effective ways to increase the gamma-ray statistics and improve the sensitivity of the analysis, are implemented to overcome the above-mentioned issues. As a result, the angular resolution at the preselection level is improved by 5 - 10% for events at 0.5◦ offset angle and by 20 - 30% for events at 2◦ offset angle. The background rate at large offset angles is decreased nearly to a level typical for offset angles below 2.5◦. Thereby, sensitivity improvements of 10 - 20% are achieved for the proposed analysis compared to the standard analysis at small offset angles. Developed analysis also allows for the usage of events at large offset angles up to approximately 4◦, which was not possible before. This analysis method is applied to the analysis of the Galactic plane data above 10 TeV. As a result, 40 sources out of the 78 presented in the H.E.S.S. Galactic plane survey (HGPS) are detected above 10 TeV. Among them are representatives of all source classes that are present in the HGPS catalogue; namely, binary systems, supernova remnants, pulsar wind nebulae and composite objects. The potential of the improved analysis method is demonstrated by investigating the more than 10 TeV emission for two objects: the region associated with the shell-type SNR HESS J1731−347 and the PWN candidate associated with PSR J0855−4644 that is coincident with Vela Junior (HESS J0852−463).
Filaments are omnipresent features in the solar chromosphere, one of the atmospheric layers of the Sun, which is located above the photosphere, the visible surface of the Sun. They are clouds of plasma reaching from the photosphere to the chromosphere, and even to the outer-most atmospheric layer, the corona. They are stabalized by the magnetic field. If the magnetic field is disturbed, filaments can erupt as coronal mass ejections (CME), releasing plasma into space, which can also hit the Earth. A special type of filaments are polar crown filaments, which form at the interface of the unipolar field of the poles and flux of opposite magnetic polarity, which was transported towards the poles. This flux transport is related to the global dynamo of the Sun and can therefore be analyzed indirectly with polar crown filaments. The main objective of this thesis is to better understand the physical properties and environment of high-latitude and polar crown filaments, which can be approached from two perspectives: (1) analyzing the large-scale properties of high-latitude and polar crown filaments with full-disk Hα observations from the Chromospheric Telescope (ChroTel) and (2) determining the relation of polar crown and high-latitude filaments from the chromosphere to the lower-lying photosphere with high-spatial resolution observations of the Vacuum Tower Telescope (VTT), which reveal the smallest details.
The Chromospheric Telescope (ChroTel) is a small 10-cm robotic telescope at Observatorio del Teide on Tenerife (Spain), which observes the entire Sun in Hα, Ca IIK, and He I 10830 Å. We present a new calibration method that includes limb-darkening correction, removal of non-uniform filter transmission, and determination of He I Doppler velocities. Chromospheric full-disk filtergrams are often obtained with Lyot filters, which may display non-uniform transmission causing large-scale intensity variations across the solar disk. Removal of a 2D symmetric limb-darkening function from full-disk images results in a flat background. However, transmission artifacts remain and are even more distinct in these contrast-enhanced images. Zernike polynomials are uniquely appropriate to fit these large-scale intensity variations of the background. The Zernike coefficients show a distinct temporal evolution for ChroTel data, which is likely related to the telescope’s alt-azimuth mount that introduces image rotation. In addition, applying this calibration to sets of seven filtergrams that cover the He I triplet facilitates determining chromospheric Doppler velocities. To validate the method, we use three datasets with varying levels of solar activity. The Doppler velocities are benchmarked with respect to co-temporal high-resolution spectroscopic data of the GREGOR Infrared Spectrograph (GRIS). Furthermore, this technique can be applied to ChroTel Hα and Ca IIK data. The calibration method for ChroTel filtergrams can be easily adapted to other full-disk data exhibiting unwanted large-scale variations. The spectral region of the He I triplet is a primary choice for high-resolution near-infrared spectropolarimetry. Here, the improved calibration of ChroTel data will provide valuable context data.
Polar crown filaments form above the polarity inversion line between the old magnetic flux of the previous cycle and the new magnetic flux of the current cycle. Studying their appearance and their properties can lead to a better understanding of the solar cycle. We use full-disk data of the ChroTel at Observatorio del Teide, Tenerife, Spain, which were taken in three different chromospheric absorption lines (Hα 6563 Å, Ca IIK 3933 Å, and He I 10830 Å), and we create synoptic maps. In addition, the spectroscopic He I data allow us to compute Doppler velocities and to create synoptic Doppler maps. ChroTel data cover the rising and decaying phase of Solar Cycle 24 on about 1000 days between 2012 and 2018. Based on these data, we automatically extract polar crown filaments with image-processing tools and study their properties. We compare contrast maps of polar crown filaments with those of quiet-Sun filaments. Furthermore, we present a super-synoptic map summarizing the entire ChroTel database. In summary, we provide statistical properties, i.e. number and location of filaments, area, and tilt angle for both the maximum and declining phase of Solar Cycle 24. This demonstrates that ChroTel provides a
promising dataset to study the solar cycle.
The cyclic behavior of polar crown filaments can be monitored by regular full-disk Hα observations. ChroTel provides such regular observations of the Sun in three chromospheric wavelengths. To analyze the cyclic behavior and the statistical properties of polar crown filaments, we have to extract the filaments from the images. Manual extraction is tedious, and extraction with morphological image processing tools produces a large number of false positive detections and the manual extraction of these takes too much time. Automatic object detection and extraction in a reliable manner allows us to process more data in a shorter time. We will present an overview of the ChroTel database and a proof of concept of a machine learning application, which allows us a unified extraction of, for example, filaments from ChroTel data.
The chromospheric Hα spectral line dominates the spectrum of the Sun and other stars. In the stellar regime, this spectral line is already used as a powerful tracer of magnetic activity. For the Sun, other tracers are typically used to monitor solar activity. Nonetheless, the Sun is observed constantly in Hα with globally distributed ground-based full-disk imagers. The aim of this study is to introduce Hα as a tracer of solar activity and compare it to other established indicators. We discuss the newly created imaging Hα excess in the perspective of possible application for modelling of stellar atmospheres. In particular, we try to determine how constant is the mean intensity of the Hα excess and number density of low-activity regions between solar maximum and minimum. Furthermore, we investigate whether the active region coverage fraction or the changing emission strength in the active regions dominates time variability in solar Hα observations. We use ChroTel observations of full-disk Hα filtergrams and morphological image processing techniques to extract the positive and negative imaging Hα excess, for bright features (plage regions) and dark absorption features (filaments and sunspots), respectively. We describe the evolution of the Hα excess during Solar Cycle 24 and compare it to other well established tracers: the relative sunspot number, the F10.7 cm radio flux, and the Mg II index. Moreover, we discuss possible applications of the Hα excess for stellar activity diagnostics and the contamination of exoplanet transmission spectra. The positive and negative Hα excess follow the behavior of the solar activity over the course of the cycle. Thereby, positive Hα excess is closely correlated to the chromospheric Mg II index. On the other hand, the negative Hα excess, created from dark features like filaments and sunspots, is introduced as a tracer of solar activity for the first time. We investigated the mean intensity distribution for active regions for solar minimum and maximum and found that the shape of both distributions is very similar but with different amplitudes. This might be related with the relatively stable coronal temperature component during the solar cycle. Furthermore, we found that the coverage fraction of Hα excess and the Hα excess of bright features are strongly correlated, which will influence modelling of stellar and exoplanet atmospheres.
High-resolution observations of polar crown and high-latitude filaments are scarce. We present a unique sample of such filaments observed in high-resolution Hα narrow-band filtergrams and broad-band images, which were obtained with a new fast camera system at the VTT. ChroTel provided full-disk context observations in Hα, Ca IIK, and He I 10830 Å. The Helioseismic and Magnetic Imager (HMI) and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) provided line-of-sight magnetograms and ultraviolet (UV) 1700 Å filtergrams, respectively. We study filigree in the vicinity of polar crown and high-latitude filaments and relate their locations to magnetic concentrations at the filaments’ footpoints. Bright points are a well studied phenomenon in the photosphere at low latitudes, but they were not yet studied in the quiet network close to the poles. We examine size, area, and eccentricity of bright points and find that their morphology is very similar to their counterparts at lower latitudes, but their sizes and areas are larger. Bright points at the footpoints of polar crown filaments are preferentially located at stronger magnetic flux concentrations, which are related to bright regions at the border of supergranules as observed in UV filtergrams. Examining the evolution of bright points on three consecutive days reveals that their amount increases while the filament decays, which indicates they impact the equilibrium of the cool plasma contained in filaments.
Active Galactic Nuclei (AGN) are considered to be the main powering source of active galaxies, where central Super Massive Black Holes (SMBHs), with masses between 106 and 109 M⊙ gravitationally pull the surrounding material via accre- tion. AGN phenomenon expands over a very wide range of luminosities, from the most luminous high-redshift quasars (QSOs), to the local Low-Luminosity AGN (LLAGN), with significantly weaker luminosities. While "typical" luminous AGNs distinguish themselves by their characteristical blue featureless continuum, the Broad Emission Lines (BELs) with Full Widths at Half Maximum (FWHM) in order of few thousands km s1, arising from the so-called Broad Line Region (BLR), and strong radio and/or X-ray emission, detection of LLAGNs on the other hand is quite chal- lenging due to their extremely weak emission lines, and absence of the power-law continuum. In order to fully understand AGN evolution and their duty-cycles across cosmic history, we need a proper knowledge of AGN phenomenon at all luminosi- ties and redshifts, as well as perspectives from different wavelength bands.
In this thesis I present a search for AGN signatures in central spectra of 542 local (0.005 < z < 0.03) galaxies from the Calar Alto Legacy Integral Field Area (CALIFA) survey. The adopted aperture of 3′′ × 3′′ corresponds to central ∼ 100 − 500 pc for the redshift range of CALIFA. Using the standard emission-line ratio diagnostic diagrams, we initially classified all CALIFA emission-line galaxies (526) into star- forming, LINER-like, Seyfert 2 and intermediates. We further detected signatures of the broad Hα component in 89 spectra from the sample, of which more than 60% are present in the central spectra of LINER-like galaxies. These BELs are very weak, with luminosities in range 1038 − 1041 erg s−1, but with FWHMs between 1000 km s−1 and 6000 km s−1, comparable to those of luminous high-z AGN. This result implies that type 1 AGN are in fact quite frequent in the local Universe. We also identified additional 29 Seyfert 2 galaxies using the emission-line ratio diagnostic diagrams.
Using the MBH − σ∗ correlation, we estimated black hole masses of 55 type 1 AGN from CALIFA, a sample for which we had estimates of bulge stellar velocity dispersions σ∗. We compared these masses to the ones that we estimated from the virial method and found large discrepancies. We analyzed the validity of both meth- ods for black hole mass estimation of local LLAGN, and concluded that most likely virial scaling relations can no longer be applied as a valid MBH estimator in such low-luminosity regime. These black holes accrete at very low rate, having Edding- ton ratios in range 4.1 × 10−5 − 2.4 × 10−3. Detection of BELs with such low lumi- nosities and at such low Eddington rates implies that these LLAGN are still able to form the BLR, although with probably modified structure of the central engine.
In order to obtain full picture of black hole growth across cosmic time, it is es- sential that we study them in different stages of their activity. For that purpose, we estimated the broad AGN Luminosity Function (AGNLF) of our entire type 1 AGN sample using the 1/Vmax method. The shape of AGNLF indicates an apparent flattening below luminosities LHα ∼ 1039 erg s−1. Correspondingly we estimated ac- tive Black Hole Mass Function (BHMF) and Eddington Ration Distribution Function (ERDF) for a sub-sample of type 1 AGN for which we have MBH and λ estimates. The flattening is also present in both BHMF and ERDF, around log(MBH) ∼ 7.7 and log(λ) < 3, respectively. We estimated the fraction of active SMBHs in CALIFA by comparing our active BHMF to the one of the local quiescent SMBHs. The shape of
the active fraction which decreases with increasing MBH, as well as the flattening of AGNLF, BHMF and ERDF is consistent with scenario of AGN cosmic downsizing.
To complete AGN census in the CALIFA galaxy sample, it is necessary to search for them in various wavelength bands. For the purpose of completing the census we performed cross-correlations between all 542 CALIFA galaxies and multiwavelength surveys, Swift – BAT 105 month catalogue (in hard 15 - 195 keV X-ray band), and NRAO VLA Sky Survey (NVSS, in 1.4 GHz radio domain). This added 1 new AGN candidate in X-ray, and 7 in radio wavelength band to our local LLAGN count.
It is possible to detect AGN emission signatures within 10 – 20 kpc outside of the central galactic regions. This may happen when the central AGN has recently switched off and the photoionized material is spread across the galaxy within the light-travel-time, or the photoionized material is blown away from the nucleus by outflows. In order to detect these extended AGN regions we constructed spatially resolved emission-line ratio diagnostic diagrams of all emission-line galaxies from the CALIFA, and found 1 new object that was previously not identified as AGN.
Obtaining the complete AGN census in CALIFA, with five different AGN types, showed that LLAGN contribute a significant fraction of 24% of the emission-line galaxies in the CALIFA sample. This result implies that AGN are quite common in the local Universe, and although being in very low activity stage, they contribute to large fraction of all local SMBHs. Within this thesis we approached the upper limit of AGN fraction in the local Universe and gained some deeper understanding of the LLAGN phenomenon.
Reciprocal space slicing
(2021)
An experimental technique that allows faster assessment of out-of-plane strain dynamics of thin film heterostructures via x-ray diffraction is presented. In contrast to conventional high-speed reciprocal space-mapping setups, our approach reduces the measurement time drastically due to a fixed measurement geometry with a position-sensitive detector. This means that neither the incident (ω) nor the exit (2θ) diffraction angle is scanned during the strain assessment via x-ray diffraction. Shifts of diffraction peaks on the fixed x-ray area detector originate from an out-of-plane strain within the sample. Quantitative strain assessment requires the determination of a factor relating the observed shift to the change in the reciprocal lattice vector. The factor depends only on the widths of the peak along certain directions in reciprocal space, the diffraction angle of the studied reflection, and the resolution of the instrumental setup. We provide a full theoretical explanation and exemplify the concept with picosecond strain dynamics of a thin layer of NbO2.
As society paves its way towards device miniaturization and precision medicine, micro-scale actuation and guided transport become increasingly prominent research fields, with high potential impact in both technological and clinical contexts. In order to accomplish directed motion of micron-sized objects, as biosensors and drug-releasing microparticles, towards specific target sites, a promising strategy is the use of living cells as smart biochemically-powered carriers, building the so-called bio-hybrid systems. Inspired by leukocytes, native cells of living organisms efficiently migrating to critical targets as tumor tissue, an emerging concept is to exploit the amoeboid crawling motility of such cells as mean of transport for drug delivery applications.
In the research work described in this thesis, I synergistically applied experimental, computational and theoretical modeling approaches to investigate the behaviour and transport mechanism of a novel kind of bio-hybrid system for active transport at the micro-scale, referred to as cellular truck. This system consists of an amoeboid crawling cell, the carrier, attached to a microparticle, the cargo, which may ideally be drug-loaded for specific therapeutic treatments.
For the purposes of experimental investigation, I employed the amoeba Dictyostelium discoideum as crawling cellular carrier, being a renowned model organism for leukocyte migration and, in general, for eukaryotic cell motility. The performed experiments revealed a complex recurrent cell-cargo relative motion, together with an intermittent motility of the cellular truck as a whole. The evidence suggests the presence of cargoes on amoeboid cells to act as mechanical stimulus leading cell polarization, thus promoting cell motility and giving rise to the observed intermittent dynamics of the truck. Particularly, bursts in cytoskeletal polarity along the cell-cargo axis have been
found to occur in time with a rate dependent on cargo geometrical features, as particle diameter. Overall, the collected experimental evidence pointed out a pivotal role of cell-cargo interactions in the emergent cellular truck motion dynamics. Especially, they can determine the transport capabilities of amoeboid cells, as the cargo size significantly impacts the cytoskeletal activity and repolarization dynamics along the cell-cargo axis, the latter responsible for truck displacement and reorientation.
Furthermore, I developed a modeling framework, built upon the experimental evidence on cellular truck behaviour, that connects the relative dynamics and interactions arising at the truck scale with the actual particle transport dynamics. In fact, numerical simulations of the proposed model successfully reproduced the phenomenology of the cell-cargo system, while enabling the prediction of the transport properties of cellular trucks over larger spatial and temporal scales. The theoretical analysis provided a deeper understanding of the role of cell-cargo interaction on mass transport, unveiling in particular how the long-time transport efficiency is governed by the interplay between the persistence time of cell polarity and time scales of the relative dynamics stemming from cell-cargo interaction. Interestingly, the model predicts the existence of an optimal cargo size, enhancing the diffusivity of cellular trucks; this is in line with previous independent experimental data, which appeared rather counterintuitive and had no explanation prior to this study.
In conclusion, my research work shed light on the importance of cargo-carrier interactions in the context of crawling cell-mediated particle transport, and provides a prototypical, multifaceted framework for the analysis and modelling of such complex bio-hybrid systems and their perspective optimization.
Leveraging large-deviation statistics to decipher the stochastic properties of measured trajectories
(2021)
Extensive time-series encoding the position of particles such as viruses, vesicles, or individualproteins are routinely garnered insingle-particle tracking experiments or supercomputing studies.They contain vital clues on how viruses spread or drugs may be delivered in biological cells.Similar time-series are being recorded of stock values in financial markets and of climate data.Such time-series are most typically evaluated in terms of time-averaged mean-squareddisplacements (TAMSDs), which remain random variables for finite measurement times. Theirstatistical properties are different for differentphysical stochastic processes, thus allowing us toextract valuable information on the stochastic process itself. To exploit the full potential of thestatistical information encoded in measured time-series we here propose an easy-to-implementand computationally inexpensive new methodology, based on deviations of the TAMSD from itsensemble average counterpart. Specifically, we use the upper bound of these deviations forBrownian motion (BM) to check the applicability of this approach to simulated and real data sets.By comparing the probability of deviations fordifferent data sets, we demonstrate how thetheoretical bound for BM reveals additional information about observed stochastic processes. Weapply the large-deviation method to data sets of tracer beads tracked in aqueous solution, tracerbeads measured in mucin hydrogels, and of geographic surface temperature anomalies. Ouranalysis shows how the large-deviation properties can be efficiently used as a simple yet effectiveroutine test to reject the BM hypothesis and unveil relevant information on statistical propertiessuch as ergodicity breaking and short-time correlations.
Polymeric semiconductors are strong contenders for replacing traditional inorganic semiconductors in electronic applications requiring low power, low cost and flexibility, such as biosensors, flexible solar cells and electronic displays. Molecular doping has the potential to enable this revolution by improving the conductivity and charge transport properties of this class of materials. Despite decades of research in this field, gaps in our understanding of the nature of dopant–polymer interactions has resulted in limited commercialization of this technology. This work aims at providing a deeper insight into the underlying mechanisms of molecular p-doping of semiconducting polymers in the solution and solid-state, and thereby bring the scientific community closer to realizing the dream of making organic semiconductors commonplace in the electronics industry. The role of 1) dopant size/shape, 2) polymer chain aggregation and 3) charge delocalization on the doping mechanism and efficiency is addressed using optical (UV-Vis-NIR) and electron paramagnetic resonance (EPR) spectroscopies. By conducting a comprehensive study of the nature and concentration of the doping-induced species in solutions of the polymer poly(3-hexylthiophene) (P3HT) with 3 different dopants, we identify the unique optical signatures of the delocalized polaron, localized polaron and charge-transfer complex, and report their extinction coefficient values. Furthermore, with X-ray diffraction, atomic force microscopy and electrical conductivity measurements, we study the impact of processing technique and doping mechanism on the morphology and thereby, charge transport through the doped films.
This work demonstrates that the doping mechanism and type of doping-induced species formed are strongly influenced by the polymer backbone arrangement rather than dopant shape/size. The ability of the polymer chain to aggregate is found to be crucial for efficient charge transfer (ionization) and polaron delocalization. At the same time, our results suggest that the high ionization efficiency of a dopant–polymer system in solution may subsequently hinder efficient charge transport in the solid-state due to the reduction in the fraction of tie chains, which enable charges to move efficiently between aggregated domains in the films. This study demonstrates the complex multifaceted nature of polymer doping while providing important hints for the future design of dopant-host systems and film fabrication techniques.
Angular momentum is a particularly sensitive probe into stellar evolution because it changes significantly over the main sequence life of a star. In this thesis, I focus on young main sequence stars of which some feature a rapid evolution in their rotation rates. This transition from fast to slow rotation is inadequately explored observationally and this work aims to provide insights into the properties and time scales but also investigates stellar rotation in young open clusters in general.
I focus on the two open clusters NGC 2516 and NGC 3532 which are ~150 Myr (zero-age main sequence age) and ~300 Myr old, respectively. From 42 d-long time series photometry obtained at the Cerro Tololo Inter-American Observatory, I determine stellar rotation periods in both clusters. With accompanying low resolution spectroscopy, I measure radial velocities and chromospheric emission for NGC 3532, the former to establish a clean membership and the latter to probe the rotation-activity connection.
The rotation period distribution derived for NGC 2516 is identical to that of four other coeval open clusters, including the Pleiades, which shows the universality of stellar rotation at the zero-age main sequence. Among the similarities (with the Pleiades) the "extended slow rotator sequence" is a new, universal, yet sparse, feature in the colour-period diagrams of open clusters. From a membership study, I find NGC 3532 to be one of the richest nearby open clusters with 660 confirmed radial velocity members and to be slightly sub-solar in metallicity. The stellar rotation periods for NGC 3532 are the first published for a 300 Myr-old open cluster, a key age to understand the transition from fast to slow rotation. The fast rotators at this age have significantly evolved beyond what is observed in NGC 2516 which allows to estimate the spin-down timescale and to explore the issues that angular momentum models have in describing this transition. The transitional sequence is also clearly identified in a colour-activity diagram of stars in NGC 3532. The synergies of the chromospheric activity and the rotation periods allow to understand the colour-activity-rotation connection for NGC 3532 in unprecedented detail and to estimate additional rotation periods for members of NGC 3532, including stars on the "extended slow rotator sequence".
In conclusion, this thesis probes the transition from fast to slow rotation but has also more general implications for the angular momentum evolution of young open clusters.
The majority of baryons in the Universe is believed to reside in the intergalactic medium (IGM). This makes the IGM an important component in understanding cosmological structure formation. It is expected to trace the same dark matter distribution as galaxies, forming structures like filaments and clusters. However, whereas galaxies can be observed to be arranged along these large-scale structures, the spatial distribution of the diffuse IGM is not as easily unveiled. Absorption line studies of quasar (QSO) spectra can help with mapping the IGM, as well as the boundary layer between IGM and galaxies: the circumgalactic medium (CGM). By studying gas in the Local Group, as well as in the IGM, this study aims to get a better understanding of how the gas is linked to the large-scale structure of the local Universe and the galaxies residing in that structure.
Chapter 1 gives an introduction to the CGM and IGM, while the methods used in this study are explained in Chapter 2. Chapter 3 starts on a relatively small cosmological scale, namely that of our Local Group, which includes i.a. the Milky Way (MW) and the M31. Within the CGM of the MW, there exist denser clouds, some of which are infalling while others are moving away from the Galactic disc. To study these clouds, 29 QSO spectra obtained with the Cosmic Origins Spectrograph (COS) aboard the Hubble Space Telescope (HST) were analysed. Abundances of Si II, Si III, Si IV, C II, and C IV were measured for 69 HVCs belonging to two samples: one in the direction of the LG’s barycentre and the other in the anti-barycentre direction. Their velocities range from -100 ≥ vLSR ≥ -400 km/s for the barycentre sample and between +100 ≤ vLSR ≤ +300 km/s for the anti-barycentre sample. By using Cloudy models, these data could then be used to derive gas volume densities for the HVCs. Because of the relationship between density and pressure of the ambient medium, which is in turn determined by the Galactic radiation field, the distances of the HVCs could be estimated. From this, a subsample of absorbers located in the direction of M31 was found to exist outside of the MW’s virial radius, their low densities (log nH ≤ -3.54) making it likely for them to be part of the gas in between the MW and M31. No such low-density absorbers were found in the anti-barycentre sample. Our results thus hint at gas following the dark matter potential, which would be deeper between the MW and M31 as they are by far the most massive members of the LG.
From this bridge of gas in the LG, this study zooms out to the large-scale structure of the local Universe (z ~ 0) in Chapter 4. Galaxy data from the V8k catalogue and QSO spectra from COS were used to study the relation between the galaxies tracing large-scale filaments and the gas existing outside of those galaxies. This study used the filaments defined in Courtois et al. (2013). A total of 587 Lyman α (Lyα) absorbers were found in the 302 QSO spectra in the velocity range 1070 - 6700 km/s. After selecting sightlines passing through or close to these filaments, model spectra were made for 91 sightlines and 215 (227) Lyα absorbers (components) were measured in this sample. The velocity gradient along each filament was calculated and 74 absorbers were found within 1000 km/s of the nearest filament segment.
In order to find whether the absorbers are more tied to galaxies or to the large-scale structure, equivalent widths of the Lyα absorbers were plotted against both galaxy and filament impact parameters. While stronger absorbers do tend to be closer to either galaxies or filaments, there is a large scatter in this relation. Despite this large scatter, this study found that the absorbers do not follow a random distribution either. They cluster less strongly around filaments than galaxies, but stronger than random distributions, as confirmed by a Kolmogorov-Smirnov test.
Furthermore, the column density distribution function found in this study has a slope of -β = 1.63±0.12 for the total sample and -β =1.47±0.24 for the absorbers within 1000 km/s of a filament. The shallower slope for the latter subsample could indicate an excess of denser absorbers within the filament, but they are consistent within errors. These values are in agreement with values found in e.g. Lehner et al. (2007); Danforth et al. (2016).
The picture that emerges from this study regarding the relation between the IGM and the large-scale structure in the local Universe fits with what is found in other studies: while at least part of the gas traces the same filamentary structure as galaxies, the relation is complex. This study has shown that by taking a large sample of sightlines and comparing the data gathered from those with galaxy data, it is possible to study the gaseous large-scale structure. This approach can be used in the future together with simulations to get a better understanding of structure formation and evolution in the Universe.
The evolution of life on Earth has been driven by disturbances of different types and magnitudes over the 4.6 million years of Earth’s history (Raup, 1994, Alroy, 2008). One example for such disturbances are mass extinctions which are characterized by an exceptional increase in the extinction rate affecting a great number of taxa in a short interval of geologic time (Sepkoski, 1986). During the 541 million years of the Phanerozoic, life on Earth suffered five exceptionally severe mass extinctions named the “Big Five Extinctions”. Many mass extinctions are linked to changes in climate
(Feulner, 2009). Hence, the study of past mass extinctions is not only intriguing, but can also provide insights into the complex nature of the Earth system. This thesis aims at deepening our understanding of the triggers of mass extinctions and how they affected life. To accomplish this, I investigate changes in climate during two of the Big Five extinctions using a coupled climate model.
During the Devonian (419.2–358.9 million years ago) the first vascular plants and vertebrates evolved on land while extinction events occurred in the ocean (Algeo et al., 1995). The causes of these formative changes, their interactions and their links to changes in climate are still poorly understood. Therefore, we explore the sensitivity of the Devonian climate to various boundary conditions using an intermediate-complexity climate model (Brugger et al., 2019). In contrast to Le Hir et al. (2011), we find only a minor biogeophysical effect of changes in vegetation cover due to unrealistically high soil albedo values used in the earlier study. In addition, our results cannot support the strong influence of orbital parameters on the Devonian climate, as simulated with a climate model with a strongly simplified ocean model (De Vleeschouwer et al., 2013, 2014, 2017). We can only reproduce the changes in Devonian climate suggested by proxy data by decreasing atmospheric CO2. Still, finding agreement between the evolution of sea surface temperatures reconstructed from proxy data (Joachimski et al., 2009) and our simulations remains challenging and suggests a lower δ18O ratio of Devonian seawater. Furthermore, our study of the sensitivity of the Devonian climate reveals a prevailing mode of climate variability on a timescale of decades to centuries. The quasi-periodic ocean temperature fluctuations are linked to a physical mechanism of changing sea-ice cover, ocean convection and overturning in high northern latitudes.
In the second study of this thesis (Dahl et al., under review) a new reconstruction of atmospheric CO2 for the Devonian, which is based on CO2-sensitive carbon isotope fractionation in the earliest vascular plant fossils, suggests a much earlier drop of atmo- spheric CO2 concentration than previously reconstructed, followed by nearly constant CO2 concentrations during the Middle and Late Devonian. Our simulations for the Early Devonian with identical boundary conditions as in our Devonian sensitivity study (Brugger et al., 2019), but with a low atmospheric CO2 concentration of 500 ppm, show no direct conflict with available proxy and paleobotanical data and confirm that under the simulated climatic conditions carbon isotope fractionation represents a robust proxy for atmospheric CO2. To explain the earlier CO2 drop we suggest that early forms of vascular land plants have already strongly influenced weathering. This new perspective on the Devonian questions previous ideas about the climatic conditions and earlier explanations for the Devonian mass extinctions.
The second mass extinction investigated in this thesis is the end-Cretaceous mass extinction (66 million years ago) which differs from the Devonian mass extinctions in terms of the processes involved and the timescale on which the extinctions occurred. In the two studies presented here (Brugger et al., 2017, 2021), we model the climatic effects of the Chicxulub impact, one of the proposed causes of the end-Cretaceous extinction, for the first millennium after the impact. The light-dimming effect of stratospheric sulfate aerosols causes severe cooling, with a decrease of global annual mean surface air temperature of at least 26◦C and a recovery to pre-impact temperatures after more than 30 years. The sudden surface cooling of the ocean induces deep convection which brings nutrients from the deep ocean via upwelling to the surface ocean. Using an ocean biogeochemistry model we explore the combined effect of ocean mixing and iron-rich dust originating from the impactor on the marine biosphere. As soon as light levels have recovered, we find a short, but prominent peak in marine net primary productivity. This newly discovered mechanism could result in toxic effects for marine near-surface ecosystems. Comparison of our model results to proxy data (Vellekoop et al., 2014, 2016, Hull et al., 2020) suggests that carbon release from the terrestrial biosphere is required in addition to the carbon dioxide which can be attributed to the target material. Surface ocean acidification caused by the addition of carbon dioxide and sulfur is only moderate. Taken together, the results indicate a significant contribution of the Chicxulub impact to the end-Cretaceous mass extinction by triggering multiple stressors for the Earth system.
Although the sixth extinction we face today is characterized by human intervention in nature, this thesis shows that we can gain many insights into future extinctions from studying past mass extinctions, such as the importance of the rate of change (Rothman, 2017), the interplay of multiple stressors (Gunderson et al., 2016), and changes in the carbon cycle (Rothman, 2017, Tierney et al., 2020).
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.
Magnetic strain contributions in laser-excited metals studied by time-resolved X-ray diffraction
(2021)
In this work I explore the impact of magnetic order on the laser-induced ultrafast strain response of metals. Few experiments with femto- or picosecond time-resolution have so far investigated magnetic stresses. This is contrasted by the industrial usage of magnetic invar materials or magnetostrictive transducers for ultrasound generation, which already utilize magnetostrictive stresses in the low frequency regime.
In the reported experiments I investigate how the energy deposition by the absorption of femtosecond laser pulses in thin metal films leads to an ultrafast stress generation. I utilize that this stress drives an expansion that emits nanoscopic strain pulses, so called hypersound, into adjacent layers. Both the expansion and the strain pulses change the average inter-atomic distance in the sample, which can be tracked with sub-picosecond time resolution using an X-ray diffraction setup at a laser-driven Plasma X-ray source. Ultrafast X-ray diffraction can also be applied to buried layers within heterostructures that cannot be accessed by optical methods, which exhibit a limited penetration into metals. The reconstruction of the initial energy transfer processes from the shape of the strain pulse in buried detection layers represents a contribution of this work to the field of picosecond ultrasonics.
A central point for the analysis of the experiments is the direct link between the deposited energy density in the nano-structures and the resulting stress on the crystal lattice. The underlying thermodynamical concept of a Grüneisen parameter provides the theoretical framework for my work. I demonstrate how the Grüneisen principle can be used for the interpretation of the strain response on ultrafast timescales in various materials and that it can be extended to describe magnetic stresses. The class of heavy rare-earth elements exhibits especially large magnetostriction effects, which can even lead to an unconventional contraction of the laser-excited transducer material. Such a dominant contribution of the magnetic stress to the motion of atoms has not been demonstrated previously. The observed rise time of the magnetic stress contribution in Dysprosium is identical to the decrease in the helical spin-order, that has been found previously using time-resolved resonant X-ray diffraction. This indicates that the strength of the magnetic stress can be used as a proxy of the underlying magnetic order. Such magnetostriction measurements are applicable even in case of antiparallel or non-collinear alignment of the magnetic moments and a vanishing magnetization.
The strain response of metal films is usually determined by the pressure of electrons and lattice vibrations. I have developed a versatile two-pulse excitation routine that can be used to extract the magnetic contribution to the strain response even if systematic measurements above and below the magnetic ordering temperature are not feasible. A first laser pulse leads to a partial ultrafast demagnetization so that the amplitude and shape of the strain response triggered by the second pulse depends on the remaining magnetic order. With this method I could identify a strongly anisotropic magnetic stress contribution in the magnetic data storage material iron-platinum and identify the recovery of the magnetic order by the variation of the pulse-to-pulse delay. The stark contrast of the expansion of iron-platinum nanograins and thin films shows that the different constraints for the in-plane expansion have a strong influence on the out-of-plane expansion, due to the Poisson effect. I show how such transverse strain contributions need to be accounted for when interpreting the ultrafast out-of-plane strain response using thermal expansion coefficients obtained in near equilibrium conditions.
This work contributes an investigation of magnetostriction on ultrafast timescales to the literature of magnetic effects in materials. It develops a method to extract spatial and temporal varying stress contributions based on a model for the amplitude and shape of the emitted strain pulses. Energy transfer processes result in a change of the stress profile with respect to the initial absorption of the laser pulses. One interesting example occurs in nanoscopic gold-nickel heterostructures, where excited electrons rapidly transport energy into a distant nickel layer, that takes up much more energy and expands faster and stronger than the laser-excited gold capping layer. Magnetic excitations in rare earth materials represent a large energy reservoir that delays the energy transfer into adjacent layers. Such magneto-caloric effects are known in thermodynamics but not extensively covered on ultrafast timescales. The combination of ultrafast X-ray diffraction and time-resolved techniques with direct access to the magnetization has a large potential to uncover and quantify such energy transfer processes.
In our daily life, recurrence plays an important role on many spatial and temporal scales and in different contexts. It is the foundation of learning, be it in an evolutionary or in a neural context. It therefore seems natural that recurrence is also a fundamental concept in theoretical dynamical systems science. The way in which states of a system recur or develop in a similar way from similar initial states makes it possible to infer information about the underlying dynamics of the system. The mathematical space in which we define the state of a system (state space) is often high dimensional, especially in complex systems that can also exhibit chaotic dynamics. The recurrence plot (RP) enables us to visualize the recurrences of any high-dimensional systems in a two-dimensional, binary representation. Certain patterns in RPs can be related to physical properties of the underlying system, making the qualitative and quantitative analysis of RPs an integral part of nonlinear systems science. The presented work has a methodological focus and further develops recurrence analysis (RA) by addressing current research questions related to an increasing amount of available data and advances in machine learning techniques. By automatizing a central step in RA, namely the reconstruction of the state space from measured experimental time series, and by investigating the impact of important free parameters this thesis aims to make RA more accessible to researchers outside of physics.
The first part of this dissertation is concerned with the reconstruction of the state space from time series. To this end, a novel idea is proposed which automates the reconstruction problem in the sense that there is no need to preprocesse the data or estimate parameters a priori. The key idea is that the goodness of a reconstruction can be evaluated by a suitable objective function and that this function is minimized in the embedding process. In addition, the new method can process multivariate time series input data. This is particularly important because multi-channel sensor-based observations are ubiquitous in many research areas and continue to increase. Building on this, the described minimization problem of the objective function is then processed using a machine learning approach.
In the second part technical and methodological aspects of RA are discussed. First, we mathematically justify the idea of setting the most influential free parameter in RA, the recurrence threshold ε, in relation to the distribution of all pairwise distances in the data. This is especially important when comparing different RPs and their quantification statistics and is fundamental to any comparative study. Second, some aspects of recurrence quantification analysis (RQA) are examined. As correction schemes for biased RQA statistics, which are based on diagonal lines, we propose a simple method for dealing with border effects of an RP in RQA and a skeletonization algorithm for RPs. This results in less biased (diagonal line based) RQA statistics for flow-like data. Third, a novel type of RQA characteristic is developed, which can be viewed as a generalized non-linear powerspectrum of high dimensional systems. The spike powerspectrum transforms a spike-train like signal into its frequency domain. When transforming the diagonal line-dependent recurrence rate (τ-RR) of a RP in this way, characteristic periods, which can be seen in the state space representation of the system can be unraveled. This is not the case, when Fourier transforming τ-RR.
Finally, RA and RQA are applied to climate science in the third part and neuroscience in the fourth part. To the best of our knowledge, this is the first time RPs and RQA have been used to analyze lake sediment data in a paleoclimate context. Therefore, we first elaborate on the basic formalism and the interpretation of visually visible patterns in RPs in relation to the underlying proxy data. We show that these patterns can be used to classify certain types of variability and transitions in the Potassium record from six short (< 17m) sediment cores collected during the Chew Bahir Drilling Project. Building on this, the long core (∼ m composite) from the same site is analyzed and two types of variability and transitions are
identified and compared with ODP Site wetness index from the eastern Mediterranean. Type variability likely reflects the influence of precessional forcing in the lower latitudes at times of maximum values of the long eccentricity cycle ( kyr) of the earth’s orbit around the sun, with a tendency towards extreme events. Type variability appears to be related to the minimum values of this cycle and corresponds to fairly rapid transitions between relatively dry and relatively wet conditions.
In contrast, RQA has been applied in the neuroscientific context for almost two decades. In the final part, RQA statistics are used to quantify the complexity in a specific frequency band of multivariate EEG (electroencephalography) data. By analyzing experimental data, it can be shown that the complexity of the signal measured in this way across the sensorimotor cortex decreases as motor tasks are performed. The results are consistent with and comple- ment the well known concepts of motor-related brain processes. We assume that the thus discovered features of neuronal dynamics in the sensorimotor cortex together with the robust RQA methods for identifying and classifying these contribute to the non-invasive EEG-based development of brain-computer interfaces (BCI) for motor control and rehabilitation.
The present work is an important step towards a robust analysis of complex systems based on recurrence.
Ground-based astronomy is set to employ next-generation telescopes with apertures larger than 25 m in diameter before this decade is out. Such giant telescopes observe their targets through a larger patch of turbulent atmosphere, demanding that most of the instruments behind them must also grow larger to make full use of the collected stellar flux. This linear scaling in size greatly complicates the design of astronomical instrumentation, inflating their cost quadratically. Adaptive optics (AO) is one approach to circumvent this scaling law, but it can only be done to an extent before the cost of the corrective system itself overwhelms that of the instrument or even that of the telescope. One promising technique for miniaturizing the instruments and thus driving down their cost is to replace some, or all, of the free space bulk optics in the optical train with integrated photonic components.
Photonic devices, however, do their work primarily in single-mode waveguides, and the atmospherically-distorted starlight must first be efficiently coupled into them if they are to outperform their bulk optic counterparts. This is doable by two means: AO systems can again help control the angular size and motion of seeing disks to the point where they will couple efficiently into astrophotonic components, but this is only feasible for the brightest of objects and over limited fields of view. Alternatively, tapered fiber devices known as photonic lanterns — with their ability to convert multimode into single-mode optical fields — can be used to feed speckle patterns into single-mode integrated optics. They, nonetheless, must conserve the degrees of freedom, and the number of output waveguides will quickly grow out of control for uncorrected large telescopes. An AO-assisted photonic lantern fed by a partially corrected wavefront presents a compromise that can have a manageable size if the trade-off between the two methods is chosen carefully. This requires end-to-end simulations that take into account all the subsystems upstream of the astrophotonic instrument, i.e., the atmospheric layers, the telescope, the AO system, and the photonic lantern, before a decision can be made on sizing the multiplexed integrated instrument.
The numerical models that simulate atmospheric turbulence and AO correction are presented in this work. The physics and models for optical fibers, arrays of waveguides, and photonic lanterns are also provided. The models are on their own useful in understanding the behavior of the individual subsystems involved and are also used together to compute the optimum sizing of photonic lanterns for feeding astrophotonic instruments. Additionally, since photonic lanterns are a relatively new concept, two novel applications are discussed for them later in this thesis: the use of mode-selective photonic lanterns (MSPLs) to reduce the multiplicity of multiplexed integrated instruments and the combination of photonic lanterns with discrete beam combiners (DBCs) to retrieve the modal content in an optical waveguide.
In the frame of a world fighting a dramatic global warming caused by human-related activities, research towards the development of renewable energies plays a crucial role. Solar energy is one of the most important clean energy sources and its role in the satisfaction of the global energy demand is set to increase. In this context, a particular class of materials captured the attention of the scientific community for its attractive properties: halide perovskites. Devices with perovskite as light-absorber saw an impressive development within the last decade, reaching nowadays efficiencies comparable to mature photovoltaic technologies like silicon solar cells. Yet, there are still several roadblocks to overcome before a wide-spread commercialization of this kind of devices is enabled. One of the critical points lies at the interfaces: perovskite solar cells (PSCs) are made of several layers with different chemical and physical features. In order for the device to function properly, these properties have to be well-matched.
This dissertation deals with some of the challenges related to interfaces in PSCs, with a focus on the interface between the perovskite material itself and the subsequent charge transport layer. In particular, molecular assemblies with specific properties are deposited on the perovskite surface to functionalize it. The functionalization results in energy level alignment adjustment, interfacial losses reduction, and stability improvement.
First, a strategy to tune the perovskite’s energy levels is introduced: self-assembled monolayers of dipolar molecules are used to functionalize the surface, obtaining simultaneously a shift in the vacuum level position and a saturation of the dangling bonds at the surface. A shift in the vacuum level corresponds to an equal change in work function, ionization energy, and electron affinity. The direction of the shift depends on the direction of the collective interfacial dipole. The magnitude of the shift can be tailored by controlling the deposition parameters, such as the concentration of the solution used for the deposition. The shift for different molecules is characterized by several non-invasive techniques, including in particular Kelvin probe. Overall, it is shown that it is possible to shift the perovskite energy levels in both directions by several hundreds of meV. Moreover, interesting insights on the molecules deposition dynamics are revealed.
Secondly, the application of this strategy in perovskite solar cells is explored. Devices with different perovskite compositions (“triple cation perovskite” and MAPbBr3) are prepared. The two resulting model systems present different energetic offsets at the perovskite/hole-transport layer interface. Upon tailored perovskite surface functionalization, the devices show a stabilized open circuit voltage (Voc) enhancement of approximately 60 meV on average for devices with MAPbBr3, while the impact is limited on triple-cation solar cells. This suggests that the proposed energy level tuning method is valid, but its effectiveness depends on factors such as the significance of the energetic offset compared to the other losses in the devices.
Finally, the above presented method is further developed by incorporating the ability to interact with the perovskite surface directly into a novel hole-transport material (HTM), named PFI. The HTM can anchor to the perovskite halide ions via halogen bonding (XB). Its behaviour is compared to that of another HTM (PF) with same chemical structure and properties, except for the ability of forming XB. The interaction of perovskite with PFI and PF is characterized through UV-Vis, atomic force microscopy and Kelvin probe measurements combined with simulations. Compared to PF, PFI exhibits enhanced resilience against solvent exposure and improved energy level alignment with the perovskite layer. As a consequence, devices comprising PFI show enhanced Voc and operational stability during maximum-power-point tracking, in addition to hysteresis reduction. XB promotes the formation of a high-quality interface by anchoring to the halide ions and forming a stable and ordered interfacial layer, showing to be a particularly interesting candidate for the development of tailored charge transport materials in PSCs.
Overall, the results exposed in this dissertation introduce and discuss a versatile tool to functionalize the perovskite surface and tune its energy levels. The application of this method in devices is explored and insights on its challenges and advantages are given. Within this frame, the results shed light on XB as ideal interaction for enhancing stability and efficiency in perovskite-based devices.
Proteins of halophilic organisms that accumulate molar concentrations of KCl in their cytoplasm have much higher content in acidic amino acids than proteins of mesophilic organisms. It has been proposed that this excess is necessary to maintain proteins hydrated in an environment with low water activity: either via direct interactions between water and the carboxylate groups of acidic amino acids or via cooperative interactions between acidic amino acids and hydrated cations, which would stabilize the folded protein. In the course of this Ph.D. study, we investigated these possibilities using atomistic molecular dynamics simulations and classical force fields. High quality parameters describing the interaction between K+ and carboxylate groups present in acidic amino acids are indispensable for this study. We first evaluated the quality of the default parameters for these ions within the widely used AMBER ff14SB force field for proteins and found that they perform poorly. We propose new parameters, which reproduce solution activity derivatives of potassium acetate solutions up to 2 mol/kg and the distances between potassium ions and carboxylate groups observed in x-ray structures of proteins. To understand the role of acidic amino acids in protein hydration, we investigated this aspect for 5 halophilic proteins in comparison with 5 mesophilic ones. Our results do not support the necessity of acidic amino acids to keep folded proteins hydrated. Proteins with a larger fraction of acidic amino acids indeed have higher hydration levels. However, the hydration level of each protein is identical at low (b_KCl = 0.15 mol/kg) and high (b_KCl = 2 mol/kg) KCl concentration. It has also been proposed that cooperative interactions between acidic amino acids with nearby hydrated cations stabilize the folded protein and slow down its solvation shell; according to this theory, the cations would be preferentially excluded from the unfolded structure. We investigate this possibility through extensive free energy calculation simulations. We find that cooperative interactions between neighboring acidic amino acids exist and are mediated by the ions in solution but are present in both folded and unfolded structures of halophilic proteins. The translational dynamics of the solvation shell is barely distinguishable between halophilic and mesophilic proteins; therefore, such a cooperative effect does not result in unusually slow solvent dynamics as has been suggested.
Partial synchronous states exist in systems of coupled oscillators between full synchrony and asynchrony. They are an important research topic because of their variety of different dynamical states. Frequently, they are studied using phase dynamics. This is a caveat, as phase dynamics are generally obtained in the weak coupling limit of a first-order approximation in the coupling strength. The generalization to higher orders in the coupling strength is an open problem. Of particular interest in the research of partial synchrony are systems containing both attractive and repulsive coupling between the units. Such a mix of coupling yields very specific dynamical states that may help understand the transition between full synchrony and asynchrony. This thesis investigates partial synchronous states in mixed-coupling systems. First, a method for higher-order phase reduction is introduced to observe interactions beyond the pairwise one in the first-order phase description, hoping that these may apply to mixed-coupling systems. This new method for coupled systems with known phase dynamics of the units gives correct results but, like most comparable methods, is computationally expensive. It is applied to three Stuart-Landau oscillators coupled in a line with a uniform coupling strength. A numerical method is derived to verify the analytical results. These results are interesting but give importance to simpler phase models that still exhibit exotic states. Such simple models that are rarely considered are Kuramoto oscillators with attractive and repulsive interactions. Depending on how the units are coupled and the frequency difference between the units, it is possible to achieve many different states. Rich synchronization dynamics, such as a Bellerophon state, are observed when considering a Kuramoto model with attractive interaction in two subpopulations (groups) and repulsive interactions between groups. In two groups, one attractive and one repulsive, of identical oscillators with a frequency difference, an interesting solitary state appears directly between full and partial synchrony. This system can be described very well analytically.
In the last five years, gravitational-wave astronomy has gone from a purerly theoretical field into a thriving experimental science. Several gravitational- wave signals, emitted by stellar-mass binary black holes and binary neutron stars, have been detected, and many more are expected in the future as consequence of the planned upgrades in the gravitational-wave detectors. The observation of the gravitational-wave signals from these systems, and the characterization of their sources, heavily relies on the precise models for the emitted gravitational waveforms. To take full advantage of the increased detector sensitivity, it is then necessary to also improve the accuracy of the gravitational-waveform models.
In this work, I present an updated version of the waveform models for spinning binary black holes within the effective-one-body formalism. This formalism is based on the notion that the solution to the relativistic two- body problem varies smoothly with the mass ratio of the binary system, from the equal-mass regime to the test-particle limit. For this reason, it provides an elegant method to combine, under a unique framework, the solution to the relativistic two-body problem in different regimes. The main two regimes that are combined under the effective-one-body formalism are the slow-motion, weak field limit (accessible through the post-Newtonian theory), and the extreme mass-ratio regime (described using the black-hole- perturbation theory). This formalism is nevertheless flexible enough to integrate information about the solution to the relativistic two-body problem obtained using other techniques, such as numerical relativity.
The novelty of the waveform models presented in this work is the inclusion of beyond-quadupolar terms in the waveforms emitted by spinning binary black holes. In fact, while the time variation of the source quadupole moment is the leading contribution to the waveforms emitted by binary black holes observable by LIGO and Virgo detectors, beyond-quadupolar terms can be important for binary systems with asymmetric masses, large total mass, or observed with large inclination angle with respect to the orbital angular momentum of the binary. For this purpose, I combine the approximate analytic expressions of these beyond-quadupolar terms, with their calculations from numerical relativity, to develop an accurate waveform model including inspiral, merger and ringdown for spinning binary black holes. I first construct this model in the simplified case of black holes with spins aligned with the orbital angular momentum of the binary, then I extend it to the case of generic spin orientations. Finally, I test the accuracy of both these models against a large number of waveforms obtained from numerical relativity. The waveform models I present in this work are the state of the art for spinning binary black holes, without restrictions in the allowed values for the masses and the spins of the system.
The measurement of the source properties of a binary system emitting gravitational waves requires to compute O(107 − 109) different waveforms. Since the waveform models mentioned before can require O(1 − 10)s to generate a single waveform, they can be difficult to use in data-analysis studies given the increasing number of sources observed by the LIGO and Virgo detectors. To overcome this obstacle, I use the reduced-order-modeling technique to develop a faster version of the waveform model for black holes with spins aligned to the orbital angular momentum of the binary. This version of the model is as accurate as the original and reduces the time for evaluating a waveform by two orders of magnitude.
The waveform models developed in this thesis have been used by the LIGO and Virgo collaborations in the inference of the source parameters of the gravitational-wave signals detected during the second observing run (O2), and first half of the third observing run (O3a) of LIGO and Virgo detectors. Here, I present a study on the source properties of the signals GW170729 and GW190412, for which I have been directly involved in the analysis. In addition, these models have been used by the LIGO and Virgo collaborations to perform tests on General Relativity employing the gravitational-wave signals detected during O3a, and to analyze the population of the observed binary black holes.
In this paper, we report X-ray absorption and core-level electron spectra of the nucleobase derivative 2-thiouracil at the sulfur L1- and L2,3-edges. We used soft X-rays from the free-electron laser FLASH2 for the excitation of isolated molecules and dispersed the outgoing electrons with a magnetic bottle spectrometer. We identified photoelectrons from the 2p core orbital, accompanied by an electron correlation satellite, as well as resonant and non-resonant Coster–Kronig and Auger–Meitner emission at the L1- and L2,3-edges, respectively. We used the electron yield to construct X-ray absorption spectra at the two edges. The experimental data obtained are put in the context of the literature currently available on sulfur core-level and 2-thiouracil spectroscopy.
Computation of the instantaneous phase and amplitude via the Hilbert Transform is a powerful tool of data analysis. This approach finds many applications in various science and engineering branches but is not proper for causal estimation because it requires knowledge of the signal’s past and future. However, several problems require real-time estimation of phase and amplitude; an illustrative example is phase-locked or amplitude-dependent stimulation in neuroscience. In this paper, we discuss and compare three causal algorithms that do not rely on the Hilbert Transform but exploit well-known physical phenomena, the synchronization and the resonance. After testing the algorithms on a synthetic data set, we illustrate their performance computing phase and amplitude for the accelerometer tremor measurements and a Parkinsonian patient’s beta-band brain activity.
Synchronization of coupled oscillators manifests itself in many natural and man-made systems, including cyrcadian clocks, central pattern generators, laser arrays, power grids, chemical and electrochemical oscillators, only to name a few. The mathematical description of this phenomenon is often based on the paradigmatic Kuramoto model, which represents each oscillator by one scalar variable, its phase. When coupled, phase oscillators constitute a high-dimensional dynamical system, which exhibits complex behaviour, ranging from synchronized uniform oscillation to quasiperiodicity and chaos. The corresponding collective rhythms can be useful or harmful to the normal operation of various systems, therefore they have been the subject of much research.
Initially, synchronization phenomena have been studied in systems with all-to-all (global) and nearest-neighbour (local) coupling, or on random networks. However, in recent decades there has been a lot of interest in more complicated coupling structures, which take into account the spatially distributed nature of real-world oscillator systems and the distance-dependent nature of the interaction between their components. Examples of such systems are abound in biology and neuroscience. They include spatially distributed cell populations, cilia carpets and neural networks relevant to working memory. In many cases, these systems support a rich variety of patterns of synchrony and disorder with remarkable properties that have not been observed in other continuous media. Such patterns are usually referred to as the coherence-incoherence patterns, but in symmetrically coupled oscillator systems they are also known by the name chimera states.
The main goal of this work is to give an overview of different types of collective behaviour in large networks of spatially distributed phase oscillators and to develop mathematical methods for their analysis. We focus on the Kuramoto models for one-, two- and three-dimensional oscillator arrays with nonlocal coupling, where the coupling extends over a range wider than nearest neighbour coupling and depends on separation. We use the fact that, for a special (but still quite general) phase interaction function, the long-term coarse-grained dynamics of the above systems can be described by a certain integro-differential equation that follows from the mathematical approach called the Ott-Antonsen theory. We show that this equation adequately represents all relevant patterns of synchrony and disorder, including stationary, periodically breathing and moving coherence-incoherence patterns. Moreover, we show that this equation can be used to completely solve the existence and stability problem for each of these patterns and to reliably predict their main properties in many application relevant situations.
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.
Selfsustained oscillations are some of the most commonly observed phenomena in biological systems. They emanate from non-linear systems in a heterogeneous environment and can be described by the theory of dynamical systems. Part of this theory considers reduced models of the oscillator dynamics by means of amplitudes and a phase variable. Such variables are highly attractive for theoretical and experimental studies. Theoretically these variables correspond to an integrable linearization of the generally non-linear system. Experimentally, there exist well established approaches to extract phases from oscillator signals. Notably, one can define phase models also for networks of oscillators. One highly active field examines effects of non-local coupling among oscillators, which is thought to play a key role in networks with strong coupling. The dissertation introduces and expands the knowledge about high-order phase coupling in networks of oscillators. Mathematical calculations consider the Stuart-Landau oscillator. A novel phase estimation scheme for direct observations of an oscillator dynamics is introduced based on numerics. A numerical study of high-order phase coupling applies a Fourier fit for the Stuart-Landau and for the van-der-Pol oscillator. The numerical approach is finally tested on observation-based phase estimates of the Morris-Lecar neuron. A popular approach for the construction of phases from signals is based on phase demodulation by means of the Hilbert transform. Generally, observations of oscillations contain a small and generic variation of their amplitude. The work presents a way to quantify how much the variations of signal amplitude spoil a phase demodulation procedure. For the ideal case of phase modulated signals, amplitude modulations vanish. However, the Hilbert transform produces artificial variations of the reconstructed amplitude even in this case. The work proposes a novel procedure called Iterative Hilbert Transform Embedding to obtain an optimal demodulation of signals. The text presents numerous examples and tests of application for the method, covering multicomponent signals, observables of highly stable limit cycle oscillations and noisy phase dynamics. The numerical results are supported by a spectral theory of convergence for weak phase modulations.
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.
We consider a sequential cascade of molecular first-reaction events towards a terminal reaction centre in which each reaction step is controlled by diffusive motion of the particles. The model studied here represents a typical reaction setting encountered in diverse molecular biology systems, in which, e.g. a signal transduction proceeds via a series of consecutive 'messengers': the first messenger has to find its respective immobile target site triggering a launch of the second messenger, the second messenger seeks its own target site and provokes a launch of the third messenger and so on, resembling a relay race in human competitions. For such a molecular relay race taking place in infinite one-, two- and three-dimensional systems, we find exact expressions for the probability density function of the time instant of the terminal reaction event, conditioned on preceding successful reaction events on an ordered array of target sites. The obtained expressions pertain to the most general conditions: number of intermediate stages and the corresponding diffusion coefficients, the sizes of the target sites, the distances between them, as well as their reactivities are arbitrary.
With ongoing anthropogenic global warming, some of the most vulnerable components of the Earth system might become unstable and undergo a critical transition. These subsystems are the so-called tipping elements. They are believed to exhibit threshold behaviour and would, if triggered, result in severe consequences for the biosphere and human societies. Furthermore, it has been shown that climate tipping elements are not isolated entities, but interact across the entire Earth system. Therefore, this thesis aims at mapping out the potential for tipping events and feedbacks in the Earth system mainly by the use of complex dynamical systems and network science approaches, but partially also by more detailed process-based models of the Earth system.
In the first part of this thesis, the theoretical foundations are laid by the investigation of networks of interacting tipping elements. For this purpose, the conditions for the emergence of global cascades are analysed against the structure of paradigmatic network types such as Erdös-Rényi, Barabási-Albert, Watts-Strogatz and explicitly spatially embedded networks. Furthermore, micro-scale structures are detected that are decisive for the transition of local to global cascades. These so-called motifs link the micro- to the macro-scale in the network of tipping elements. Alongside a model description paper, all these results are entered into the Python software package PyCascades, which is publicly available on github.
In the second part of this dissertation, the tipping element framework is first applied to components of the Earth system such as the cryosphere and to parts of the biosphere. Afterwards it is applied to a set of interacting climate tipping elements on a global scale. Using the Earth system Model of Intermediate Complexity (EMIC) CLIMBER-2, the temperature feedbacks are quantified, which would arise if some of the large cryosphere elements disintegrate over a long span of time. The cryosphere components that are investigated are the Arctic summer sea ice, the mountain glaciers, the Greenland and the West Antarctic Ice Sheets. The committed temperature increase, in case the ice masses disintegrate, is on the order of an additional half a degree on a global average (0.39-0.46 °C), while local to regional additional temperature increases can exceed 5 °C. This means that, once tipping has begun, additional reinforcing feedbacks are able to increase global warming and with that the risk of further tipping events.
This is also the case in the Amazon rainforest, whose parts are dependent on each other via the so-called moisture-recycling feedback. In this thesis, the importance of drought-induced tipping events in the Amazon rainforest is investigated in detail. Despite the Amazon rainforest is assumed to be adapted to past environmental conditions, it is found that tipping events sharply increase if the drought conditions become too intense in a too short amount of time, outpacing the adaptive capacity of the Amazon rainforest. In these cases, the frequency of tipping cascades also increases to 50% (or above) of all tipping events. In the model that was developed in this study, the southeastern region of the Amazon basin is hit hardest by the simulated drought patterns. This is also the region that already nowadays suffers a lot from extensive human-induced changes due to large-scale deforestation, cattle ranching or infrastructure projects.
Moreover, on the larger Earth system wide scale, a network of conceptualised climate tipping elements is constructed in this dissertation making use of a large literature review, expert knowledge and topological properties of the tipping elements. In global warming scenarios, tipping cascades are detected even under modest scenarios of climate change, limiting global warming to 2 °C above pre-industrial levels. In addition, the structural roles of the climate tipping elements in the network are revealed. While the large ice sheets on Greenland and Antarctica are the initiators of tipping cascades, the Atlantic Meridional Overturning Circulation (AMOC) acts as the transmitter of cascades. Furthermore, in our conceptual climate tipping element model, it is found that the ice sheets are of particular importance for the stability of the entire system of investigated climate tipping elements.
In the last part of this thesis, the results from the temperature feedback study with the EMIC CLIMBER-2 are combined with the conceptual model of climate tipping elements. There, it is observed that the likelihood of further tipping events slightly increases due to the temperature feedbacks even if no further CO$_2$ would be added to the atmosphere.
Although the developed network model is of conceptual nature, it is possible with this work for the first time to quantify the risk of tipping events between interacting components of the Earth system under global warming scenarios, by allowing for dynamic temperature feedbacks at the same time.
The Earth's electron radiation belts exhibit a two-zone structure, with the outer belt being highly dynamic due to the constant competition between a number of physical processes, including acceleration, loss, and transport. The flux of electrons in the outer belt can vary over several orders of magnitude, reaching levels that may disrupt satellite operations. Therefore, understanding the mechanisms that drive these variations is of high interest to the scientific community.
In particular, the important role played by loss mechanisms in controlling relativistic electron dynamics has become increasingly clear in recent years. It is now widely accepted that radiation belt electrons can be lost either by precipitation into the atmosphere or by transport across the magnetopause, called magnetopause shadowing. Precipitation of electrons occurs due to pitch-angle scattering by resonant interaction with various types of waves, including whistler mode chorus, plasmaspheric hiss, and electromagnetic ion cyclotron waves. In addition, the compression of the magnetopause due to increases in solar wind dynamic pressure can substantially deplete electrons at high L shells where they find themselves in open drift paths, whereas electrons at low L shells can be lost through outward radial diffusion. Nevertheless, the role played by each physical process during electron flux dropouts still remains a fundamental puzzle.
Differentiation between these processes and quantification of their relative contributions to the evolution of radiation belt electrons requires high-resolution profiles of phase space density (PSD). However, such profiles of PSD are difficult to obtain due to restrictions of spacecraft observations to a single measurement in space and time, which is also compounded by the inaccuracy of instruments. Data assimilation techniques aim to blend incomplete and inaccurate spaceborne data with physics-based models in an optimal way. In the Earth's radiation belts, it is used to reconstruct the entire radial profile of electron PSD, and it has become an increasingly important tool in validating our current understanding of radiation belt dynamics, identifying new physical processes, and predicting the near-Earth hazardous radiation environment.
In this study, sparse measurements from Van Allen Probes A and B and Geostationary Operational Environmental Satellites (GOES) 13 and 15 are assimilated into the three-dimensional Versatile Electron Radiation Belt (VERB-3D) diffusion model, by means of a split-operator Kalman filter over a four-year period from 01 October 2012 to 01 October 2016. In comparison to previous works, the 3D model accounts for more physical processes, namely mixed pitch angle-energy diffusion, scattering by EMIC waves, and magnetopause shadowing. It is shown how data assimilation, by means of the innovation vector (the residual between observations and model forecast), can be used to account for missing physics in the model. This method is used to identify the radial distances from the Earth and the geomagnetic conditions where the model is inconsistent with the measured PSD for different values of the adiabatic invariants mu and K. As a result, the Kalman filter adjusts the predictions in order to match the observations, and this is interpreted as evidence of where and when additional source or loss processes are active.
Furthermore, two distinct loss mechanisms responsible for the rapid dropouts of radiation belt electrons are investigated: EMIC wave-induced scattering and magnetopause shadowing. The innovation vector is inspected for values of the invariant mu ranging from 300 to 3000 MeV/G, and a statistical analysis is performed to quantitatively assess the effect of both processes as a function of various geomagnetic indices, solar wind parameters, and radial distance from the Earth. The results of this work are in agreement with previous studies that demonstrated the energy dependence of these two mechanisms. EMIC wave scattering dominates loss at lower L shells and it may amount to between 10%/hr to 30%/hr of the maximum value of PSD over all L shells for fixed first and second adiabatic invariants. On the other hand, magnetopause shadowing is found to deplete electrons across all energies, mostly at higher L shells, resulting in loss from 50%/hr to 70%/hr of the maximum PSD. Nevertheless, during times of enhanced geomagnetic activity, both processes can operate beyond such location and encompass the entire outer radiation belt.
The results of this study are two-fold. Firstly, it demonstrates that the 3D data assimilative code provides a comprehensive picture of the radiation belts and is an important step toward performing reanalysis using observations from current and future missions. Secondly, it achieves a better understanding and provides critical clues of the dominant loss mechanisms responsible for the rapid dropouts of electrons at different locations over the outer radiation belt.
Supernova remnants (SNRs) are discussed as the most promising sources of galactic cosmic rays (CR). The diffusive shock acceleration (DSA) theory predicts particle spectra in a rough agreement with observations. Upon closer inspection, however, the photon spectra of observed SNRs indicate that the particle spectra produced at SNRs shocks deviate from the standard expectation. This work suggests a viable explanation for a softening of the particle spectra in SNRs. The basic idea is the re-acceleration of particles in the turbulent region immediately downstream of the shock. This thesis shows that at the re-acceleration of particles by the fast-mode waves in the downstream region can be efficient enough to impact particle spectra over several decades in energy. To demonstrate this, a generic SNR model is presented, where the evolution of particles is described by the reduced transport equation for CR. It is shown that the resulting particle and the corresponding synchrotron spectra are significantly softer compared to the standard case. Next, this work outlines RATPaC, a code developed to model particle acceleration and corresponding photon emissions in SNRs. RATPaC solves the particle transport equation in test-particle mode using hydrodynamic simulations of the SNR plasma flow. The background magnetic field can be either computed from the induction equation or follows analytic profiles. This work presents an extended version of RATPaC that accounts for stochastic re-acceleration by fast-mode waves that provide diffusion of particles in momentum space. This version is then applied to model the young historical SNR Tycho. According to radio observations, Tycho’s SNR features the radio spectral index of approximately −0.65. In previous modeling approaches, this fact has been attributed to the strongly distinctive Alfvénic drift, which is assumed to operate in the shock vicinity. In this work, the problems and inconsistencies of this scenario are discussed. Instead, stochastic re-acceleration of electrons in the immediate downstream region of Tycho’s SNR is suggested as a cause for the soft radio spectrum. Furthermore, this work investigates two different scenarios for magnetic-field distributions inside Tycho’s SNR. It is concluded that magnetic-field damping is needed to account for the observed filaments in the radio range. Two models are presented for Tycho’s SNR, both of them feature strong hadronic contribution. Thus, a purely leptonic model is considered as very unlikely. Additionally, to the detailed modeling of Tycho’s SNR, this dissertation presents a relatively simple one-zone model for the young SNR Cassiopeia A and an interpretation for the recently analyzed VERITAS and Fermi-LAT data. It shows that the γ-ray emission of Cassiopeia A cannot be explained without a hadronic contribution and that the remnant accelerates protons up to TeV energies. Thus, Cassiopeia A is found to be unlikely a PeVatron.
Over the last decades, the rate of near-surface warming in the Arctic is at least double than elsewhere on our planet (Arctic amplification). However, the relative contribution of different feedback processes to Arctic amplification is a topic of ongoing research, including the role of aerosol and clouds. Lidar systems are well-suited for the investigation of aerosol and optically-thin clouds as they provide vertically-resolved information on fine temporal scales. Global aerosol models fail to converge on the sign of the Arctic aerosol radiative effect (ARE). In the first part of this work, the optical and microphysical properties of Arctic aerosol were characterized at case study level in order to assess the short-wave (SW) ARE. A long-range transport episode was first investigated. Geometrically similar aerosol layers were captured over three locations. Although the aerosol size distribution was different between Fram Strait(bi-modal) and Ny-Ålesund (fine mono-modal), the atmospheric column ARE was similar. The latter was related to the domination of accumulation mode aerosol. Over both locations top of the atmosphere (TOA) warming was accompanied by surface cooling.
Subsequently, the sensitivity of ARE was investigated with respect to different aerosol and spring-time ambient conditions. A 10% change in the single-scattering albedo (SSA) induced higher ARE perturbations compared to a 30% change in the aerosol extinction coefficient. With respect to ambient conditions, the ARETOA was more sensitive to solar elevation changes compared to AREsur f ace. Over dark surfaces the ARE profile was exclusively negative, while over bright surfaces a negative to positive shift occurred above the aerosol layers. Consequently, the sign of ARE can be highly sensitive in spring since this season is characterized by transitional surface albedo conditions.
As the inversion of the aerosol microphysics is an ill-posed problem, the inferred aerosol size distribution of a low-tropospheric event was compared to the in-situ measured distribution. Both techniques revealed a bi-modal distribution, with good agreement in the total volume concentration. However, in terms of SSA a disagreement was found, with the lidar inversion indicating highly scattering particles and the in-situ measurements pointing to absorbing particles. The discrepancies could stem from assumptions in the inversion (e.g. wavelength-independent refractive index) and errors in the conversion of the in-situ measured light attenuation into absorption. Another source of discrepancy might be related to an incomplete capture of fine particles in the in-situ sensors. The disagreement in the most critical parameter for the Arctic ARE necessitates further exploration in the frame of aerosol closure experiments. Care must be taken in ARE modelling studies, which may use either the in-situ or lidar-derived SSA as input.
Reliable characterization of cirrus geometrical and optical properties is necessary for improving their radiative estimates. In this respect, the detection of sub-visible cirrus is of special importance. The total cloud radiative effect (CRE) can be negatively biased, should only the optically-thin and opaque cirrus contributions are considered. To this end, a cirrus retrieval scheme was developed aiming at increased sensitivity to thin clouds. The cirrus detection was based on the wavelet covariance transform (WCT) method, extended by dynamic thresholds. The dynamic WCT exhibited high sensitivity to faint and thin cirrus layers (less than 200 m) that were partly or completely undetected by the existing static method. The optical characterization scheme extended the Klett–Fernald retrieval by an iterative lidar ratio (LR) determination (constrained Klett). The iterative process was constrained by a reference value, which indicated the aerosol concentration beneath the cirrus cloud. Contrary to existing approaches, the aerosol-free assumption was not adopted, but the aerosol conditions were approximated by an initial guess. The inherent uncertainties of the constrained Klett were higher for optically-thinner cirrus, but an overall good agreement was found with two established retrievals. Additionally, existing approaches, which rely on aerosol-free assumptions, presented increased accuracy when the proposed reference value was adopted. The constrained Klett retrieved reliably the optical properties in all cirrus regimes, including upper sub-visible cirrus with COD down to 0.02.
Cirrus is the only cloud type capable of inducing TOA cooling or heating at daytime. Over the Arctic, however, the properties and CRE of cirrus are under-explored. In the final part of this work, long-term cirrus geometrical and optical properties were investigated for the first time over an Arctic site (Ny-Ålesund). To this end, the newly developed retrieval scheme was employed. Cirrus layers over Ny-Ålesund seemed to be more absorbing in the visible spectral region compared to lower latitudes and comprise relatively more spherical ice particles. Such meridional differences could be related to discrepancies in absolute humidity and ice nucleation mechanisms. The COD tended to decline for less spherical and smaller ice particles probably due to reduced water vapor deposition on the particle surface. The cirrus optical properties presented weak dependence on ambient temperature and wind conditions.
Over the 10 years of the analysis, no clear temporal trend was found and the seasonal cycle was not pronounced. However, winter cirrus appeared under colder conditions and stronger winds. Moreover, they were optically-thicker, less absorbing and consisted of relatively more spherical ice particles. A positive CREnet was primarily revealed for a broad range of representative cloud properties and ambient conditions. Only for high COD (above 10) and over tundra a negative CREnet was estimated, which did not hold true over snow/ice surfaces. Consequently, the COD in combination with the surface albedo seem to play the most critical role in determining the CRE sign over the high European Arctic.
During the last decade, intracellular actin waves have attracted much attention due to their essential role in various cellular functions, ranging from motility to cytokinesis. Experimental methods have advanced significantly and can capture the dynamics of actin waves over a large range of spatio-temporal scales. However, the corresponding coarse-grained theory mostly avoids the full complexity of this multi-scale phenomenon. In this perspective, we focus on a minimal continuum model of activator–inhibitor type and highlight the qualitative role of mass conservation, which is typically overlooked. Specifically, our interest is to connect between the mathematical mechanisms of pattern formation in the presence of a large-scale mode, due to mass conservation, and distinct behaviors of actin waves.
The Ornstein–Uhlenbeck process is a stationary and ergodic Gaussian process, that is fully determined by its covariance function and mean. We show here that the generic definitions of the ensemble- and time-averaged mean squared displacements fail to capture these properties consistently, leading to a spurious ergodicity breaking. We propose to remedy this failure by redefining the mean squared displacements such that they reflect unambiguously the statistical properties of any stochastic process. In particular we study the effect of the initial condition in the Ornstein–Uhlenbeck process and its fractional extension. For the fractional Ornstein–Uhlenbeck process representing typical experimental situations in crowded environments such as living biological cells, we show that the stationarity of the process delicately depends on the initial condition.
Over the last decades, the Arctic regions of the earth have warmed at a rate 2–3 times faster than the global average– a phenomenon called Arctic Amplification. A complex, non-linear interplay of physical processes and unique pecularities in the Arctic climate system is responsible for this, but the relative role of individual processes remains to be debated. This thesis focuses on the climate change and related processes on Svalbard, an archipelago in the North Atlantic sector of the Arctic, which is shown to be a "hotspot" for the amplified recent warming during winter. In this highly dynamical region, both oceanic and atmospheric large-scale transports of heat and moisture interfere with spatially inhomogenous surface conditions, and the corresponding energy exchange strongly shapes the atmospheric boundary layer. In the first part, Pan-Svalbard gradients in the surface air temperature (SAT) and sea ice extent (SIE) in the fjords are quantified and characterized. This analysis is based on observational data from meteorological stations, operational sea ice charts, and hydrographic observations from the adjacent ocean, which cover the 1980–2016 period. It is revealed that typical estimates of SIE during late winter range from 40–50% (80–90%) in the western (eastern) parts of Svalbard. However, strong SAT warming during winter of the order of 2–3K per decade dictates excessive ice loss, leaving fjords in the western parts essentially ice-free in recent winters. It is further demostrated that warm water currents on the west coast of Svalbard, as well as meridional winds contribute to regional differences in the SIE evolution. In particular, the proximity to warm water masses of the West Spitsbergen Current can explain 20–37% of SIE variability in fjords on west Svalbard, while meridional winds and associated ice drift may regionally explain 20–50% of SIE variability in the north and northeast. Strong SAT warming has overruled these impacts in recent years, though.
In the next part of the analysis, the contribution of large-scale atmospheric circulation changes to the Svalbard temperature development over the last 20 years is investigated. A study employing kinematic air-back trajectories for Ny-Ålesund reveals a shift in the source regions of lower-troposheric air over time for both the winter and the summer season. In winter, air in the recent decade is more often of lower-latitude Atlantic origin, and less frequent of Arctic origin. This affects heat- and moisture advection towards Svalbard, potentially manipulating clouds and longwave downward radiation in that region. A closer investigation indicates that this shift during winter is associated with a strengthened Ural blocking high and Icelandic low, and contributes about 25% to the observed winter warming on Svalbard over the last 20 years. Conversely, circulation changes during summer include a strengthened Greenland blocking high which leads to more frequent cold air advection from the central Arctic towards Svalbard, and less frequent air mass origins in the lower latitudes of the North Atlantic. Hence, circulation changes during winter are shown to have an amplifying effect on the recent warming on Svalbard, while summer circulation changes tend to mask warming.
An observational case study using upper air soundings from the AWIPEV research station in Ny-Ålesund during May–June 2017 underlines that such circulation changes during summer are associated with tropospheric anomalies in temperature, humidity and boundary layer height.
In the last part of the analysis, the regional representativeness of the above described changes around Svalbard for the broader Arctic is investigated. Therefore, the terms in the diagnostic temperature equation in the Arctic-wide lower troposphere are examined for the Era-Interim atmospheric reanalysis product. Significant positive trends in diabatic heating rates, consistent with latent heat transfer to the atmosphere over regions of increasing ice melt, are found for all seasons over the Barents/Kara Seas, and in individual months in the vicinity of Svalbard. The above introduced warm (cold) advection trends during winter (summer) on Svalbard are successfully reproduced. Regarding winter, they are regionally confined to the Barents Sea and Fram Strait, between 70°–80°N, resembling a unique feature in the whole Arctic. Summer cold advection trends are confined to the area between eastern Greenland and Franz Josef Land, enclosing Svalbard.
The goal of this thesis was to thoroughly investigate the behavior of multimode fibres to aid the development of modern and forthcoming fibre-fed spectrograph systems. Based on the Eigenmode Expansion Method, a field propagation model was created that can emulate effects in fibres relevant for astronomical spectroscopy, such as modal noise, scrambling, and focal ratio degradation. These effects are of major concern for any fibre-coupled spectrograph used in astronomical research. Changes in the focal ratio, modal distribution of light or non-perfect scrambling limit the accuracy of measurements, e.g. the flux determination of the astronomical object, the sky-background subtraction and detection limit for faint galaxies, or the spectral line position accuracy used for the detection of extra-solar planets.
Usually, fibres used for astronomical instrumentation are characterized empirically through tests. The results of this work allow to predict the fibre behaviour under various conditions using sophisticated software tools to simulate the waveguide behaviour and mode transport of fibres.
The simulation environment works with two software interfaces. The first is the mode solver module FemSIM from Rsoft. It is used to calculate all the propagation modes and effective refractive indexes of a given system. The second interface consists of Python scripts which enable the simulation of the near- and far-field outputs of a given fibre. The characteristics of the input field can be manipulated to emulate real conditions. Focus variations, spatial translation, angular fluctuations, and disturbances through the mode coupling factor can also be simulated.
To date, complete coherent propagation or complete incoherent propagation can be simulated. Partial coherence was not addressed in this work. Another limitation of the simulations is that they work exclusively for the monochromatic case and that the loss coefficient of the fibres is not considered. Nevertheless, the simulations were able to match the results of realistic measurements.
To test the validity of the simulations, real fibre measurements were used for comparison. Two fibres with different cross-sections were characterized. The first fibre had a circular cross-section, and the second one had an octagonal cross-section. The utilized test-bench was originally developed for the prototype fibres of the 4MOST fibre feed characterization. It allowed for parallel laser beam measurements, light cone measurements, and scrambling measurements. Through the appropriate configuration, the acquisition of the near- and/or far-field was feasible.
By means of modal noise analysis, it was possible to compare the near-field speckle patterns of simulations and measurements as a function of the input angle. The spatial frequencies that originate from the modal interference could be analyzed by using the power spectral density analysis. Measurements and simulations yielded similar results. Measurements with induced modal scrambling were compared to simulations using incoherent propagation and once again similar results were achieved. Through both measurements and simulations, the enlargement of the near-field distribution could be observed and analyzed. The simulations made it possible to explain incoherent intensity fluctuations that appear in real measurements due to the field distribution of the active propagation modes.
By using the Voigt analysis in the far-field distribution, it was possible to separate the modal diffusion component in order to compare it with the simulations. Through an appropriate assessment, the modal diffusion component as a function of the input angle could be translated into angular divergence. The simulations gave the minimal angular divergence of the system. Through the mean of the difference between simulations and measurements, a figure of merit is given which can be used to characterize the angular divergence of real fibres using the simulations. Furthermore, it was possible to simulate light cone measurements. Due to the overall consistent results, it can be stated that the simulations represent a good tool to assist the fibre characterization process for fibre-fed spectrograph systems.
This work was possible through the BMBF Grant 05A14BA1 which was part of the phase A study of the fibre system for MOSAIC, a multi-object spectrograph for the Extremely Large Telescope (ELT-MOS).
We consider the emerging dynamics of a separable continuous time random walk (CTRW) in the case when the random walker is biased by a velocity field in a uniformly growing domain. Concrete examples for such domains include growing biological cells or lipid vesicles, biofilms and tissues, but also macroscopic systems such as expanding aquifers during rainy periods, or the expanding Universe. The CTRW in this study can be subdiffusive, normal diffusive or superdiffusive, including the particular case of a Lévy flight. We first consider the case when the velocity field is absent. In the subdiffusive case, we reveal an interesting time dependence of the kurtosis of the particle probability density function. In particular, for a suitable parameter choice, we find that the propagator, which is fat tailed at short times, may cross over to a Gaussian-like propagator. We subsequently incorporate the effect of the velocity field and derive a bi-fractional diffusion-advection equation encoding the time evolution of the particle distribution. We apply this equation to study the mixing kinetics of two diffusing pulses, whose peaks move towards each other under the action of velocity fields acting in opposite directions. This deterministic motion of the peaks, together with the diffusive spreading of each pulse, tends to increase particle mixing, thereby counteracting the peak separation induced by the domain growth. As a result of this competition, different regimes of mixing arise. In the case of Lévy flights, apart from the non-mixing regime, one has two different mixing regimes in the long-time limit, depending on the exact parameter choice: in one of these regimes, mixing is mainly driven by diffusive spreading, while in the other mixing is controlled by the velocity fields acting on each pulse. Possible implications for encounter–controlled reactions in real systems are discussed.
Towards seasonal prediction: stratosphere-troposphere coupling in the atmospheric model ICON-NWP
(2020)
Stratospheric variability is one of the main potential sources for sub-seasonal to seasonal predictability in mid-latitudes in winter. Stratospheric pathways play an important role for long-range teleconnections between tropical phenomena, such as the quasi-biennial oscillation (QBO) and El Niño-Southern Oscillation (ENSO), and the mid-latitudes on the one hand, and linkages between Arctic climate change and the mid-latitudes on the other hand. In order to move forward in the field of extratropical seasonal predictions, it is essential that an atmospheric model is able to realistically simulate the stratospheric circulation and variability. The numerical weather prediction (NWP) configuration of the ICOsahedral Non-hydrostatic atmosphere model ICON is currently being used by the German Meteorological Service for the regular weather forecast, and is intended to produce seasonal predictions in future. This thesis represents the first extensive evaluation of Northern Hemisphere stratospheric winter circulation in ICON-NWP by analysing a large set of seasonal ensemble experiments.
An ICON control climatology simulated with a default setup is able to reproduce the basic behaviour of the stratospheric polar vortex. However, stratospheric westerlies are significantly too weak and major stratospheric warmings too frequent, especially in January. The weak stratospheric polar vortex in ICON is furthermore connected to a mean sea level pressure (MSLP) bias pattern resembling the negative phase of the Arctic Oscillation (AO). Since a good representation of the drag exerted by gravity waves is crucial for a realistic simulation of the stratosphere, three sensitivity experiments with reduced gravity wave drag are performed. Both a reduction of the non-orographic and orographic gravity wave drag respectively, lead to a strengthening of the stratospheric vortex and thus a bias reduction in winter, in particular in January. However, the effect of the non-orographic gravity wave drag on the stratosphere is stronger. A third experiment, combining a reduced orographic and non-orographic drag, exhibits the largest stratospheric bias reductions. The analysis of stratosphere-troposphere coupling based on an index of the Northern Annular Mode demonstrates that ICON realistically represents downward coupling. This coupling is intensified and more realistic in experiments with a reduced gravity wave drag, in particular with reduced non-orographic drag. Tropospheric circulation is also affected by the reduced gravity wave drag, especially in January, when the strongly improved stratospheric circulation reduces biases in the MSLP patterns. Moreover, a retuning of the subgrid-scale orography parameterisations leads to a significant error reduction in the MSLP in all months. In conclusion, the combination of these adjusted parameterisations is recommended as a current optimal setup for seasonal simulations with ICON.
Additionally, this thesis discusses further possible influences on the stratospheric polar vortex, including the influence of tropical phenomena, such as QBO and ENSO, as well as the influence of a rapidly warming Arctic. ICON does not simulate the quasi-oscillatory behaviour of the QBO and favours weak easterlies in the tropical stratosphere. A comparison with a reanalysis composite of the easterly QBO phase reveals, that the shift towards the easterly QBO in ICON further weakens the stratospheric polar vortex. On the other hand, the stratospheric reaction to ENSO events in ICON is realistic. ICON and the reanalysis exhibit a weakened stratospheric vortex in warm ENSO years. Furthermore, in particular in winter, warm ENSO events favour the negative phase of the Arctic Oscillation, whereas cold events favour the positive phase. The ICON simulations also suggest a significant effect of ENSO on the Atlantic-European sector in late winter. To investigate the influence of Arctic climate change on mid-latitude circulation changes, two differing approaches with transient and fixed sea ice conditions are chosen. Neither ICON approach exhibits the mid-latitude tropospheric negative Arctic Oscillation circulation response to amplified Arctic warming, as it is discussed on the basis of observational evidence. Nevertheless, adding a new model to the current and active discussion on Arctic-midlatitude linkages, further contributes to the understanding of divergent conclusions between model and observational studies.
We study the experimentally measured ciprofloxacin antibiotic diffusion through a gel-like artificial sputum medium (ASM) mimicking physiological conditions typical for a cystic fibrosis layer, in which regions occupied by Pseudomonas aeruginosa bacteria are present. To quantify the antibiotic diffusion dynamics we employ a phenomenological model using a subdiffusion-absorption equation with a fractional time derivative. This effective equation describes molecular diffusion in a medium structured akin Thompson’s plumpudding model; here the ‘pudding’ background represents the ASM and the ‘plums’ represent the bacterial biofilm. The pudding is a subdiffusion barrier for antibiotic molecules that can affect bacteria found in plums. For the experimental study we use an interferometric method to determine the time evolution of the amount of antibiotic that has diffused through the biofilm. The theoretical model shows that this function is qualitatively different depending on whether or not absorption of the antibiotic in the biofilm occurs. We show that the process can be divided into three successive stages: (1) only antibiotic subdiffusion with constant biofilm parameters, (2) subdiffusion and absorption of antibiotic molecules with variable biofilm transport parameters, (3) subdiffusion and absorption in the medium but the biofilm parameters are constant again. Stage 2 is interpreted as the appearance of an intensive defence build–up of bacteria against the action of the antibiotic, and in the stage 3 it is likely that the bacteria have been inactivated. Times at which stages change are determined from the experimentally obtained temporal evolution of the amount of antibiotic that has diffused through the ASM with bacteria. Our analysis shows good agreement between experimental and theoretical results and is consistent with the biologically expected biofilm response. We show that an experimental method to study the temporal evolution of the amount of a substance that has diffused through a biofilm is useful in studying the processes occurring in a biofilm. We also show that the complicated biological process of antibiotic diffusion in a biofilm can be described by a fractional subdiffusion-absorption equation with subdiffusion and absorption parameters that change over time.
Gold at the nanoscale
(2020)
In this cumulative dissertation, I want to present my contributions to the field of plasmonic nanoparticle science. Plasmonic nanoparticles are characterised by resonances of the free electron gas around the spectral range of visible light. In recent years, they have evolved as promising components for light based nanocircuits, light harvesting, nanosensors, cancer therapies, and many more.
This work exhibits the articles I authored or co-authored in my time as PhD student at the University of Potsdam. The main focus lies on the coupling between localised plasmons and excitons in organic dyes. Plasmon–exciton coupling brings light–matter coupling to the nanoscale. This size reduction is accompanied by strong enhancements of the light field which can, among others, be utilised to enhance the spectroscopic footprint of molecules down to single molecule detection, improve the efficiency of solar cells, or establish lasing on the nanoscale. When the coupling exceeds all decay channels, the system enters the strong coupling regime. In this case, hybrid light–matter modes emerge utilisable as optical switches, in quantum networks, or as thresholdless lasers. The present work investigates plasmon–exciton coupling in gold–dye core–shell geometries and contains both fundamental insights and technical novelties. It presents a technique which reveals the anticrossing in coupled systems without manipulating the particles themselves. The method is used to investigate the relation between coupling strength and particle size. Additionally, the work demonstrates that pure extinction measurements can be insufficient when trying to assess the coupling regime. Moreover, the fundamental quantum electrodynamic effect of vacuum induced saturation is introduced. This effect causes the vacuum fluctuations to diminish the polarisability of molecules and has not yet been considered in the plasmonic context.
The work additionally discusses the reaction of gold nanoparticles to optical heating. Such knowledge is of great importance for all potential optical applications utilising plasmonic nanoparticles since optical excitation always generates heat. This heat can induce a change in the optical properties, but also mechanical changes up to melting can occur. Here, the change of spectra in coupled plasmon–exciton particles is discussed and explained with a precise model. Moreover, the work discusses the behaviour of gold nanotriangles exposed to optical heating. In a pump–probe measurement, X-ray probe pulses directly monitored the particles’ breathing modes. In another experiment, the triangles were exposed to cw laser radiation with varying intensities and illumination areas. X-ray diffraction directly measured the particles’ temperature. Particle melting was investigated with surface enhanced Raman spectroscopy and SEM imaging demonstrating that larger illumination areas can cause melting at lower intensities. An elaborate methodological and theoretical introduction precedes the articles. This way, also readers without specialist’s knowledge get a concise and detailed overview of the theory and methods used in the articles. I introduce localised plasmons in metal nanoparticles of different shapes. For this work, the plasmons were mostly coupled to excitons in J-aggregates. Therefore, I discuss these aggregates of organic dyes with sharp and intense resonances and establish an understanding of the coupling between the two systems. For ab initio simulations of the coupled systems, models for the systems’ permittivites are presented, too. Moreover, the route to the sample fabrication – the dye coating of gold nanoparticles, their subsequent deposition on substrates, and the covering with polyelectrolytes – is presented together with the measurement methods that were used for the articles.