Browsing by discipline "Teoretisk fysik"

Even after 50 years, there is still no standard, analytically tractable way to treat Quantum Chromodynamics (QCD) non-numerically besides perturbation theory. In the high-energy regime perturbation theory agrees with experimental results to a great accuracy. However, at low energies the theory becomes strongly coupled and therefore not computable by perturbative methods. Therefore, non-perturbative methods are needed, and one of the candidates is light-front holography. In this thesis, the basics of light-front quantisation and holography are discussed. Light-front quantisation takes light-cone coordinates and the Hamiltonian quantisation scheme as its basis and the resulting field theory has many beneficial properties like frame-independence. Still, to extract meaningful results from the light-front QCD, one needs to apply bottom-up holographic methods. Last part of this work focuses on the applicability of light-front holographic QCD in the area of dark matter. We find that one can build a secluded SU(3) sector consisting of a doublet of elementary particles, analogous to quarks and gluons. Due to a global symmetry, the lightest stable particle is analogous with ordinary neutron. It meets the basic requirements for being a WIMP candidate when its mass is higher than 5 TeV.

We review basics of quantum field theories (QFT) and lattice field theories (LFT). We present, evaluate, and compare possible solutions for creating portable high performance LFT simulation programs. We choose one of the possible solutions, creating our own programming language, discuss its features the our prototype of it. Last we present improvement ideas to the implemented solution.

This thesis discusses various topics related to the study of strongly coupled quantum field theories at finite density or, equivalently, finite chemical potential. In particular, the focus is on the theory of strong interactions, quantum chromodynamics (QCD). Finite-density QCD is important in the description of numerous physical systems such as neutron stars or heavy-ion collisions, a brief overview of which are given, alongside with the QCD phase diagram as motivational examples. After this, the general construction of a Lagrangian finite-density quantum field theory is described. In contrast with the zero-density setting, a finite-density field theory does not admit a simple description on the lattice, rendering this standard approach to strongly coupled theories impractical due to the so-called sign problem. Various attempts of addressing the sign problem are reviewed, and the so-called Lefschetz thimble approach and the complex Langevin method are discussed in detail. Some mathematical details related to these approaches are elaborated in the appendices. Due to the impracticality of lattice methods, a perturbative description becomes more important at finite density. Perturbative finite-density QCD and methods useful in practical calculations are discussed. Amongst them is a detailed proof of a set of so-called 'cutting rules' that apply to zero-temperature finite-density quantum field theory, an example computation using these rules as well as a discussion on various divergences and their relation to zero-density theory.

Magnetic resonance imaging (MRI) provides spatially accurate, three dimensional structural images of the human brain in a non-invasive way. This allows us to study the structure and function of the brain by analysing the shapes and sizes of different brain structures in an MRI image. Morphometric changes in different brain structures are associated with many neurological and psychiatric disorders, for example Alzheimer's disease. Tracking these changes automatically using automated segmentation methods would aid in diagnosing a particular brain disease and follow its progression. In this thesis we present a method for automatic segmentation of MRI brain scans using parametric generative models and Bayesian inference. Our method segments a given MRI scan to 41 different structures including for example hippocampus, thalamus and ventricles. In contrast to the current state-of-the-art methods in whole-brain segmentation, our method does not pose any constraints on the MRI scanning protocol used to acquire the images. Our model is based on two parts: the first part is a labeling model that models the anatomy of the brain and the second part is an imaging model that relates the label images to intensity images. Using these models and Bayesian inference we can find the most probable segmentation of a given MRI scan. We show how to train the labeling model using manual segmentations performed by experts and how to find optimal imaging model parameters using expectation-maximization (EM) optimizer. We compare our automated segmentations against expert segmentations by means of Dice scores and point out places for improvement. We then extend the labeling and imaging models and show, using a database consisting of MRI scans of 30 subjects, that the new models improve the segmentations compared to the original models. Finally we compare our method against the current state-of-the-art segmentation methods. The results show that the new models are an improvement over the old ones, and compare fairly well against other automated segmentation methods. This is encouraging, because there is still room for improvement in our models. The labeling model was trained using only nine expert segmentations, which is quite a small amount, and the automated segmentations should improve as the number of training samples grows. The upside of our method is that it is fast and generalizes straightforwardly to MRI images with varying contrast properties.

Flavour violating processes have never been observed for charged leptons, electron, muon and tau. The existence of charged lepton flavour violating (CLFV) processes is however expected, since flavour is violated by all the other fermions of the standard model (SM). In the standard model the neutrinos are massless, which forbids the mixing of neutrino flavour and also the violation of lepton flavour. The zero mass of the neutrinos in the SM is in conflict with the experimentally observed neutrino oscillations. The standard model has to be extended to include massive neutrinos. The easiest way to explain the neutrino mass is to assume that they acquire masses in the same way as the rest of the SM fermions: in the Higgs mechanism. This way however leads to problems with the naturality of the neutrino Yukawa coupling. One of the most popular methods of generating the neutrino mass is the so called seesaw mechanism (type-I). The standard model, extended with the neutrino masses, allows the charged lepton flavour to be violated. This leads to unobservably small transition rates however. Therefore an observation of charged lepton flavour violating process would be a clear evidence of the existence of new physics beyond the standard model and it's trivial extensions. To have hope of ever observing charged lepton flavour violating processes, there must be an extension of the standard model which produces observable, though small, rates for CLFV processes. One of the most popular extensions of the standard model is the so called minimal supersymmetric standard model (MSSM). The neutrinos are massless in the MSSM, as they are in SM, and therefore CLFV processes are forbidden in the MSSM. Luckily the neutrino masses can be generated via seesaw mechanism in the MSSM as well as in the SM. The MSSM contains more potential sources for CLFV processes than the SM. The extra sources are the soft mass parameters of the sleptons. In supersymmetric models the sleptons couple to the leptons through the slepton-lepton-gaugino-vertices. These generate the CLFV processes at the loop-level. Often the off-diagonal soft terms are assumed zero in the MSSM at the input scale, where the supersymmetry breaks. Experiments are done at much lower electroweak scale. The soft SUSY-breaking terms acquire large radiative corrections as they are run from the input scale down to the electroweak scale. Here the seesaw mechanism kicks in. The seesaw mechanism brings with it the off-diagonal neutrino Yukawa coupling matrices. This allows the off-diagonal slepton mass terms to evolve non-zero at the electroweak scale. In this thesis the charged lepton flavour violation is discussed first in the context of the standard model. Then the CLFV processes, l_i → (l_j γ), l_i → (l_j l_k l_l) and l_i ↔ l_j, are studied in the most general way: in the effective theories. Finally the charged lepton flavour violation is studied in the supersymmetric theories in general and more specifically in the minimal supersymmetric standard model extended with the seesaw mechanism (type-I).

Hybrid organic-inorganic perovskites (HPs) are a novel materials class in photovoltaic (PV) power generation. The PV performance of HPs is impressive, although the microscopic origin of it is not well known due to the complex atomic structure of HPs. Specifically, the disordered mobile organic cations aggravate the use of conventional computational models. I have addressed this structural complexity by developing a multi-scale model that applies quantum mechanical (QM) calculations of small HP supercell models in large coarse-grained structures. With a mixed QM-classical hopping model, I have studied the effects of cation disorder on charge mobility in HPs, which is a key feature to optimize their PV performance. My multi-scale model parametrizes the interaction between neighboring methylammonium cations (MA) in the prototypical HP material, methylammonium lead triiodide (CH3NH3PbI3, or MAPbI3). For the charge mobility analysis with my hopping model, I solved the QM site-to-site hopping probabilities analytically and computed the nearest-neighbor electronic coupling energies from the band structure of MAPbI3 with density-functional theory. I investigated the charge mobility in various MAPbI3 supercell models of ordered and disordered MA cations. My results indicate a structure-dependent mobility, in range of 50–66 cm2/Vs, with the highest observed in the ordered tetragonal phase. My multi-scale model enables the study of long-range atomistic processes in complex structures in an unprecedented scale with QM accuracy, with potential applications way beyond this study.

In this thesis, we study the decoherence of cosmological scalar perturbations during inflation. We first discuss the FRW model and cosmic inflation. Inflation is a period of accelerated expansion in the early universe, in typical models caused by a scalar field called inflaton. We review cosmological perturbation theory, where perturbations of the inflaton field and scalar degrees of freedom of the metric tensor are combined into the gauge-invariant Sasaki-Mukhanov variable. We quantize this variable using canonical quantization. Then, we discuss how interactions between the perturbations and their environment can lead to decoherence. In decoherence, the reduced density operator of the perturbations becomes diagonal with respect to a particular pointer basis. We argue that the pointer basis for the cosmological scalar perturbations consists of approximate eigenstates of the field value operator. Finally, we discuss how decoherence can help understand the transition from quantum theory to classical perturbation theory, and justify the standard treatment of perturbations and their initial conditions in cosmology. We conclude that since decoherence should not spoil the observationally successful predictions of this standard treatment, it is unlikely that the actual amount of decoherence could be observed in, say, the CMB radiation.

Magnetic field has a central role in many dynamical phenomena in the solar corona, and the accurate determination of the coronal magnetic field holds the key to solving a whole range of open research problems in solar physics. In particular, realistic estimates for the magnetic structure of Coronal Mass Ejections (CMEs) enable better understanding of the initiation mechanisms of these eruptions as well as more accurate forecasts of their space weather effects. Due to the lack of direct measurements of the coronal magnetic field the best way to study the field evolution is to use data-driven modelling, in which routinely available photospheric remote sensing measurements are used as a boundary condition. Magnetofrictional method (MFM) stands out from the variety of existing modelling approaches as a particularly promising method. The approach is computationally inexpensive but still has sufficient physical accuracy. The data-based input to the MFM is the photospheric electric field as the photospheric boundary condition. The determination of the photospheric electric field is a challenging inversion problem, in which the electric field is deduced from the available photospheric magnetic field and plasma velocity measurements. This thesis presents and discusses the state-of-the-art electric field inversion methods and the properties of the currently available photospheric measurements. The central outcome of the thesis project is the development and testing of a novel ELECTRICIT software toolkit that processes the photospheric magnetic field data and uses it to invert the photospheric electric field. The main motivation for the toolkit is the coronal modelling using MFM, but the processed magnetic field and electric field data products of the toolkit are usable also in other applications such as force-free extrapolations or high-resolution studies of photospheric evolution. This thesis presents the current state of the ELECTRICIT toolkit as well as the optimization and first tests of its functionality. The tests show that the toolkit can already in its current state produce photospheric electric field estimates to a reasonable accuracy, despite the fact that some of the state-of-the-art electric field inversion methods are yet to be implemented in the toolkit. Moreover, the optimal values of the free parameters in the currently implemented inversion methods are shown to be physically justifiable. The electric field inversions of the toolkit are also used to study other questions. It is shown that the large noise levels of the vector magnetograms in the quiet Sun cause the inverted electric field to be noise-dominated, and thus the magnetic field data from this region should not be considered in the inversion. Another aspect that is studied is the electric field inversion based only on line-of-sight (LOS) magnetograms, which is a considerable option due to much shorter cadence and better availability of the LOS data. The tests show that the inversions based on the LOS data have large errors when compared to the vector data based inversions. However, the results are shown to have reasonable consistency in the horizontal components of the electric field, when the region of interest is near the centre of the solar disk.

All aerobic organisms require oxygen, which is taken into the lungs from the outside air during inhalation. From the lungs it travels all the way to the alveoli. The lung surfactant inside the alveoli consists of roughly 90% lipids and 10% proteins. Its primary functions are the reduction of the surface tension of the fluid inside the alveoli and its role as a part of the innate immune defense. The four most abundant proteins in the lung surfactant are called SP-A, SP-B, SP-C, and SP-D. The hydrophobic surfactant protein C (or SP-C) is the smallest of the four. It has a primarily α-helical structure with two palmitoylated cysteines attached to the N-terminal, helping SP-C to be bound to the surfactant membranes more tightly. The primary functions of SP-C include the transfer of lipids from lipid monolayers to multilayered structures, the enhancement of the adsorption of surface active molecules into the air-liquid interface, and the maintenance of the integrity of the multilayered structure. Lack of SP-C is known to lead to severe chronic respiratory pathologies. A potential dimerization motif has been suggested to be located near the C-terminus of SP-C. The purpose of this project was to study the possible dimerization of SP-C using the tools of molecular dynamics simulations. In this method Newton's second law is used to calculate the time evolution of the system. The resulted trajectory describes how the positions and velocities of the particles in the system change with time. Both coarse-grained (Martini force field) and atomistic (OPLS force field) models were used in the project. Dimerization was found to occur in coarse-grained simulations of 20 SP-Cs embedded into a bilayer: both aggregation and dissociation of the proteins were observed during a period of 1μs. Excessive aggregation of membrane proteins is known to be a problem when using the Martini force field. However, the dimers in the simulations were not irreversible, which indicates that the usage of the Martini force field was rather well justified. The dimerization motif found in the simulations is largely consistent with the one suggested by experiment. The dimers were also studied through atomistic simulations based on the fine-grained structures of coarse-grained simulations, and the atomistic simulations indicated the dimers to be stable. Altogether, the simulation results are in favor of the view that SP-C exists in a dimeric form. The function of the dimer structure remains to be clarified in future studies.

The presence of dislocations in metal crystals accounts for the plasticity of metals. These dislocations do not nucleate spontaneously, but require favorable conditions. These conditions include, but are not limited to, a high temperature, external stress, and an interface such as a grain boundary or a surface. The slip of dislocations leads to steps forming on the surface, as atomic planes are displaced along a line. If a void is placed very near a surface, the possibility of forming a dislocation platelet exists. The skip of the dislocation platelet would displace the surface atoms within a closed line. Repeating such a process may form a small protrusion on the surface. In this thesis, the mechanism with which a dislocations displace the surface atoms within a closed loop is studied by using molecular dynamics (MD) simulations of copper. A spherical void is placed within the lattice, and the lattice is then subjected to an external stress. The dislocation reactions which lead to the formation of the dislocation platelet after the initial dislocation nucleation on the void is studied by running MD simulations of a void with the radius of 3 nm under tensile stress. Since the dislocations are thermally activated, the simulation proceeded differently for each run. We describe the different ways the dislocations nucleate, and the dislocation reactions that occur when they intersect to form the platelet. The activation energy of this process was studied by simulating half of a much larger void, with a radius of 8 nm, in order to obtain a more realistic nucleation environment. Formulas connecting the observable and controllable simulation variables with the energies of the nucleation are derived. The activation energies are then calculated and compared with values from literature.