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Arctic climate change is marked by intensified warming compared to global trends and a significant reduction in Arctic sea ice which can intricately influence mid-latitude atmospheric circulation through tropo- and stratospheric pathways. Achieving accurate simulations of current and future climate demands a realistic representation of Arctic climate processes in numerical climate models, which remains challenging.
Model deficiencies in replicating observed Arctic climate processes often arise due to inadequacies in representing turbulent boundary layer interactions that determine the interactions between the atmosphere, sea ice, and ocean. Many current climate models rely on parameterizations developed for mid-latitude conditions to handle Arctic turbulent boundary layer processes.
This thesis focuses on modified representation of the Arctic atmospheric processes and understanding their resulting impact on large-scale mid-latitude atmospheric circulation within climate models. The improved turbulence parameterizations, recently developed based on Arctic measurements, were implemented in the global atmospheric circulation model ECHAM6. This involved modifying the stability functions over sea ice and ocean for stable stratification and changing the roughness length over sea ice for all stratification conditions. Comprehensive analyses are conducted to assess the impacts of these modifications on ECHAM6's simulations of the Arctic boundary layer, overall atmospheric circulation, and the dynamical pathways between the Arctic and mid-latitudes.
Through a step-wise implementation of the mentioned parameterizations into ECHAM6, a series of sensitivity experiments revealed that the combined impacts of the reduced roughness length and the modified stability functions are non-linear. Nevertheless, it is evident that both modifications consistently lead to a general decrease in the heat transfer coefficient, being in close agreement with the observations.
Additionally, compared to the reference observations, the ECHAM6 model falls short in accurately representing unstable and strongly stable conditions.
The less frequent occurrence of strong stability restricts the influence of the modified stability functions by reducing the affected sample size. However, when focusing solely on the specific instances of a strongly stable atmosphere, the sensible heat flux approaches near-zero values, which is in line with the observations. Models employing commonly used surface turbulence parameterizations were shown to have difficulties replicating the near-zero sensible heat flux in strongly stable stratification.
I also found that these limited changes in surface layer turbulence parameterizations have a statistically significant impact on the temperature and wind patterns across multiple pressure levels, including the stratosphere, in both the Arctic and mid-latitudes. These significant signals vary in strength, extent, and direction depending on the specific month or year, indicating a strong reliance on the background state.
Furthermore, this research investigates how the modified surface turbulence parameterizations may influence the response of both stratospheric and tropospheric circulation to Arctic sea ice loss.
The most suitable parameterizations for accurately representing Arctic boundary layer turbulence were identified from the sensitivity experiments. Subsequently, the model's response to sea ice loss is evaluated through extended ECHAM6 simulations with different prescribed sea ice conditions.
The simulation with adjusted surface turbulence parameterizations better reproduced the observed Arctic tropospheric warming in vertical extent, demonstrating improved alignment with the reanalysis data. Additionally, unlike the control experiments, this simulation successfully reproduced specific circulation patterns linked to the stratospheric pathway for Arctic-mid-latitude linkages. Specifically, an increased occurrence of the Scandinavian-Ural blocking regime (negative phase of the North Atlantic Oscillation) in early (late) winter is observed. Overall, it can be inferred that improving turbulence parameterizations at the surface layer can improve the ECHAM6's response to sea ice loss.
Improving permafrost dynamics in land surface models: insights from dual sensitivity experiments
(2024)
The thawing of permafrost and the subsequent release of greenhouse gases constitute one of the most significant and uncertain positive feedback loops in the context of climate change, making predictions regarding changes in permafrost coverage of paramount importance. To address these critical questions, climate scientists have developed Land Surface Models (LSMs) that encompass a multitude of physical soil processes. This thesis is committed to advancing our understanding and refining precise representations of permafrost dynamics within LSMs, with a specific focus on the accurate modeling of heat fluxes, an essential component for simulating permafrost physics.
The first research question overviews fundamental model prerequisites for the representation of permafrost soils within land surface modeling. It includes a first-of-its-kind comparison between LSMs in CMIP6 to reveal their differences and shortcomings in key permafrost physics parameters. Overall, each of these LSMs represents a unique approach to simulating soil processes and their interactions with the climate system. Choosing the most appropriate model for a particular application depends on factors such as the spatial and temporal scale of the simulation, the specific research question, and available computational resources.
The second research question evaluates the performance of the state-of-the-art Community Land Model (CLM5) in simulating Arctic permafrost regions. Our approach overcomes traditional evaluation limitations by individually addressing depth, seasonality, and regional variations, providing a comprehensive assessment of permafrost and soil temperature dynamics. I compare CLM5's results with three extensive datasets: (1) soil temperatures from 295 borehole stations, (2) active layer thickness (ALT) data from the Circumpolar Active Layer Monitoring Network (CALM), and (3) soil temperatures, ALT, and permafrost extent from the ESA Climate Change Initiative (ESA-CCI). The results show that CLM5 aligns well with ESA-CCI and CALM for permafrost extent and ALT but reveals a significant global cold temperature bias, notably over Siberia. These results echo a persistent challenge identified in numerous studies: the existence of a systematic 'cold bias' in soil temperature over permafrost regions. To address this challenge, the following research questions propose dual sensitivity experiments.
The third research question represents the first study to apply a Plant Functional Type (PFT)-based approach to derive soil texture and soil organic matter (SOM), departing from the conventional use of coarse-resolution global data in LSMs. This novel method results in a more uniform distribution of soil organic matter density (OMD) across the domain, characterized by reduced OMD values in most regions. However, changes in soil texture exhibit a more intricate spatial pattern. Comparing the results to observations reveals a significant reduction in the cold bias observed in the control run. This method shows noticeable improvements in permafrost extent, but at the cost of an overestimation in ALT. These findings emphasize the model's high sensitivity to variations in soil texture and SOM content, highlighting the crucial role of soil composition in governing heat transfer processes and shaping the seasonal variation of soil temperatures in permafrost regions.
Expanding upon a site experiment conducted in Trail Valley Creek by \citet{dutch_impact_2022}, the fourth research question extends the application of the snow scheme proposed by \citet{sturm_thermal_1997} to cover the entire Arctic domain. By employing a snow scheme better suited to the snow density profile observed over permafrost regions, this thesis seeks to assess its influence on simulated soil temperatures. Comparing this method to observational datasets reveals a significant reduction in the cold bias that was present in the control run. In most regions, the Sturm run exhibits a substantial decrease in the cold bias. However, there is a distinctive overshoot with a warm bias observed in mountainous areas. The Sturm experiment effectively addressed the overestimation of permafrost extent in the control run, albeit resulting in a substantial reduction in permafrost extent over mountainous areas. ALT results remain relatively consistent compared to the control run. These outcomes align with our initial hypothesis, which anticipated that the reduced snow insulation in the Sturm run would lead to higher winter soil temperatures and a more accurate representation of permafrost physics.
In summary, this thesis demonstrates significant advancements in understanding permafrost dynamics and its integration into LSMs. It has meticulously unraveled the intricacies involved in the interplay between heat transfer, soil properties, and snow dynamics in permafrost regions. These insights offer novel perspectives on model representation and performance.
The mobile-immobile model (MIM) has been established in geoscience in the context of contaminant transport in groundwater. Here the tracer particles effectively immobilise, e.g., due to diffusion into dead-end pores or sorption. The main idea of the MIM is to split the total particle density into a mobile and an immobile density. Individual tracers switch between the mobile and immobile state following a two-state telegraph process, i.e., the residence times in each state are distributed exponentially. In geoscience the focus lies on the breakthrough curve (BTC), which is the concentration at a fixed location over time. We apply the MIM to biological experiments with a special focus on anomalous scaling regimes of the mean squared displacement (MSD) and non-Gaussian displacement distributions. As an exemplary system, we have analysed the motion of tau proteins, that diffuse freely inside axons of neurons. Their free diffusion thereby corresponds to the mobile state of the MIM. Tau proteins stochastically bind to microtubules, which effectively immobilises the tau proteins until they unbind and continue diffusing. Long immobilisation durations compared to the mobile durations give rise to distinct non-Gaussian Laplace shaped distributions. It is accompanied by a plateau in the MSD for initially mobile tracer particles at relevant intermediate timescales. An equilibrium fraction of initially mobile tracers gives rise to non-Gaussian displacements at intermediate timescales, while the MSD remains linear at all times. In another setting bio molecules diffuse in a biosensor and transiently bind to specific receptors, where advection becomes relevant in the mobile state. The plateau in the MSD observed for the advection-free setting and long immobilisation durations persists also for the case with advection. We find a new clear regime of anomalous diffusion with non-Gaussian distributions and a cubic scaling of the MSD. This regime emerges for initially mobile and for initially immobile tracers. For an equilibrium fraction of initially mobile tracers we observe an intermittent ballistic scaling of the MSD. The long-time effective diffusion coefficient is enhanced by advection, which we physically explain with the variance of mobile durations. Finally, we generalize the MIM to incorporate arbitrary immobilisation time distributions and focus on a Mittag-Leffler immobilisation time distribution with power-law tail ~ t^(-1-mu) with 0<mu<1 and diverging mean immobilisation durations. A fit of our model to the BTC of experimental data from tracer particles in aquifers matches the BTC including the power-law tail. We use the fit parameters for plotting the displacement distributions and the MSD. We find Gaussian normal diffusion at short times and long-time power-law decay of mobile mass accompanied by anomalous diffusion at long times. The long-time diffusion is subdiffusive in the advection-free setting, while it is either subdiffusive for 0<mu<1/2 or superdiffusive for 1/2<mu<1 when advection is present. In the long-time limit we show equivalence of our model to a bi-fractional diffusion equation.
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 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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".
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.