Refine
Year of publication
- 2014 (25) (remove)
Document Type
- Doctoral Thesis (25) (remove)
Language
- English (25) (remove)
Has Fulltext
- yes (25)
Is part of the Bibliography
- no (25)
Keywords
- Beschleuniger (2)
- Radio Frequenz Quadrupol (2)
- Ageing (1)
- Chopper (1)
- Coulombdissoziation (1)
- Coulombspaltung (1)
- FAIR (1)
- Functional Renormalization Group (1)
- Gammaspectroscopy (1)
- Gammaspektroskopie (1)
Institute
- Physik (25) (remove)
The nature of spontaneous brain activity during wakefulness and sleep: a complex systems approach
(2014)
In this thesis we study the organization of spontaneous brain activity during wakefulness and all stages of human non-rapid eye movement sleep using an approach based on developments and tools from the theory of complex systems. After a brief introduction to sleep physiology and different theoretical models of consciousness, we study how the organization of cortical and sub-cortical interactions is modified during the sleep cycle. Our results, obtained by modeling global brain activity as a complex functional interaction network, show that the capacity of the human brain to integrate different segregated functional modules is diminished during deep sleep, in line with an informationintegration account of consciousness. We then show that integration is impaired not only across space but also in the temporal domain, by assesing the emergence of long-range temporal correlations in brain activity and how they are modified during sleep. We propose an encompassing explanation for this observation, namely, that the brain operatsat different dynamical regimes during different states of consciousness. Finally, we gather massive amounts of data from different collaborative projects and apply machine learning techniques to reveal that the \resting state" cannot be considered as a pure brain state and is in fact a mixture containing different levels of conscious awareness. This last result has deep implications for future attempts to develop a discovery science of brain function both in health and disease.
The ab-initio molecular dynamics framework has been the cornerstone of computational solid state physics in the last few decades. Although it is already a mature field it is still rapidly developing to accommodate the growth in solid state research as well as to efficiently utilize the increase in computing power. Starting from the first principles, the ab-initio molecular dynamics provides essential information about structural and electronic properties of matter under various external conditions. In this thesis we use the ab-initio molecular dynamics to study the behavior of BaFe2As2 and CaFe2As2 under the application of external pressure. BaFe2As2 and CaFe2As2 belong to the family of iron based superconductors which are a novel and promising superconducting materials. The application of pressure is one of two key methods by which electronic and structural properties of iron based superconductors can be modified, the other one being doping (or chemical pressure). In particular, it has been noted that pressure conditions have an important effect, but their exact role is not fully understood. To better understand the effect of different pressure conditions we have performed a series of ab-initio simulations of pressure application. In order to apply the pressure with arbitrary stress tensor we have developed a method based on the Fast Inertial Relaxation Engine, whereby the unit cell and the atomic positions are evolved according to the metadynamical equations of motion. We have found that the application of hydrostatic and c axis uniaxial pressure induces a phase transition from the magnetically ordered orthorhombic phase to the non-magnetic collapsed tetragonal phase in both BaFe2As2 and CaFe2As2. In the case of BaFe2As2, an intermediate tetragonal non-magnetic tetragonal phase is observed in addition. Application of the uniaxial pressure parallel to the c axis reduces the critical pressure of the phase transition by an order of magnitude, in agreement with the experimental findings. The in-plane pressure application did not result in transition to the non-magnetic tetragonal phase and instead, rotation of the magnetic order direction could be observed. This is discussed in the context of Ginzburg-Landau theory. We have also found that the magnetostructural phase transition is accompanied by a change in the Fermi surface topology, whereby the hole cylinders centered around the Gamma point disappear, restricting the possible Cooper pair scattering channels in the tetragonal phase. Our calculations also permit us to estimate the bulk moduli and the orthorhombic elastic constants of BaFe2As2 and CaFe2As2.
To study the electronic structure in systems with broken translational symmetry, such as doped iron based superconductors, it is necessary to develop a method to unfold the complicated bandstructures arising from the supercell calculations. In this thesis we present the unfolding method based on group theoretical techniques. We achieve the unfolding by employing induced irreducible representations of space groups. The unique feature of our method is that it treats the point group operations on an equal footing with the translations. This permits us to unfold the bandstructures beyond the limit of translation symmetry and also formulate the tight-binding models of reduced dimensionality if certain conditions are met. Inclusion of point group operations in the unfolding formalism allows us to reach important conclusions about the two versus one iron picture in iron based superconductors.
And finally, we present the results of ab-initio structure prediction in the cases of giant volume collapse in MnS2 and alkaline doped picene. In the case of MnS2, a previously unobserved high pressure arsenopyrite structure of MnS2 is predicted and stability regions for the two competing metastable phases under pressure are determined. In the case of alkaline doped picene, crystal structures with different levels of doping were predicted and used to study the role of electronic correlations.
In this thesis hard probes are studied in the partonic transport model BAMPS (Boltzmann Approach to MultiParton Scatterings). Employing Monte Carlo techniques, this model describes the 3+1 dimensional evolution of the quark gluon plasma phase in ultra-relativistic heavy-ion collisions by propagating all particles in space and time and carrying out their collisions according to the Boltzmann equation. Since hard probes are produced in hard processes with a large momentum transfer, the value of the running coupling is small and their interactions should be describable within perturbative QCD (pQCD). This work focuses on open heavy flavor, but also addresses the suppression of light parton jets, in particular to highlight differences due to the mass. For light partons, radiative processes are the dominant contribution to their energy loss. For heavy quarks, we show that also binary interactions with a running coupling and an improved Debye screening matched to hard-thermal-loop calculations play an important role. Furthermore, the impact of the mass in radiative interactions, prominently named the dead cone effect, and the interplay with the Landau-Pomeranchuk-Migdal (LPM) effect are studied in great detail. Since the transport model BAMPS has access to all medium properties and the space time information of heavy quarks, it is the ideal tool to study the dissociation and regeneration of J/psi mesons, which is also investigated in this thesis.
In this thesis, a novel 257 kHz chopper device was numerically developed, technically designed and experimentally commissioned; a 4-solenoid, low-energy ion beam transport line was numerically investigated, installed and experimentally commissioned; and a novel massless beam-separation system was numerically developed.
The chopper combines a pulsed electric field with a static magnetic field in an ExB or Wien-filter type field configuration. Chopped beam pulses with a 257 kHz repetition rate and rise times of 110 ns were experimentally achieved using a 14 keV helium beam.
Due to the achieved results, the complete LEBT line for the future Frankfurt Neutron Source FRANZ is ready to deliver a dc or a pulsed beam. At the same time, the LEBT section represents an attractive test stand for the study of low-energy ion beams. It combines magnetic lenses, which allow space-charge compensated beam transport, and a chopper system capable of producing short beam pulses in the hundred nanosecond range. Since these beam pulses are transported onwards, their longitudinal and transverse properties can be analyzed. The pulse duration and time of flight are well below the rise time for the space-charge compensation through residual gas ionization. This opens the possibility for dedicated investigations of the transport of short, low-energy beam pulses including longitudinal and transverse space-charge effects and of relevant issues like the dynamics of space-charge compensation and electron effects in short pulses.
Cryo-electron tomography (CET) is a unique technique to visualize biological objects under near-to-native conditions at near-atomic resolution. CET provides three-dimensional (3D) snapshots of the cellular proteome, in which the spatial relations between macromolecular complexes in their near native cellular context can be explored. Due to the limitation of the electron dose applicable on biological samples, the achievable resolution of a tomogram is restricted to a few nanometers, higher resolution can be achieved by averaging of structures occurring in multiples. For this purpose, computational techniques such as template matching, sub-tomogram averaging and classification are essential for a meaningful processing of CET data.
This thesis introduces the techniques of template matching and sub-tomogram averaging and their applications on real biological data sets. Subsequently, the problem of reference bias, which restricts the applicability of those techniques, is addressed. Two methods that estimate the reference bias in Fourier and real space are demonstrated. The real space method, which we have named the “M-free” score, provides a reliable estimation of the reference bias, which gives access to the reliability of the template matching or sub-tomogram averaging process. Thus, the “M-free” score makes those approaches more applicable to structural biology. Furthermore, a classification algorithm based on Neural Networks (NN) called “KerDenSOM3D” is introduced, which is implemented in 3D and compensates for the missing-wedge. This approach helps extracting different structural states of macromolecular complexes or increasing the class purity of data sets by eliminating outliers. A comprehensive comparison with other classification methods shows superior performance of KerDenSOM3D.