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To gain a better understanding of complex mechanisms in biological systems, simultaneous control over multiple processes is key. To this purpose selective photouncaging has been developed. Photo-uncaging is an experimental scheme in which a molecule of interest has been inactivated synthetically and is activated by light. Usually a bond is cleaved and a leaving group is set free. The molecule which inactivates the molecule of interest and sets the leaving group free is called (photo-)cage. In a selective photo-uncaging scheme a number of leaving groups can be released independently, usually by irradiation with light of different wavelengths. This approach is, however, seriously limited in its applicability due to the properties of the involved cages and irradiation schemes. A major drawback is the usually quite broad UV-Vis absorption of the cages. This makes a selective activation by light difficult and limits the maximal number of independent cages severely.
Therefore, the aim of this thesis is to introduce the Vibrationally Promoted Electronic Resonance (VIPER) 2D-IR pulse sequence in a alternative selective uncaging scheme.
The VIPER 2D-IR pulse sequence is a spectroscopic tool which allows to generate 2D-IR signals whose lifetime are independent of the vibrational relaxation lifetime. It has been first used to monitor chemical exchange. It consists of a narrowband infared pump pulse, a subsequent UV-Vis pump pulse and a broadband infrared probe pulse. The UV-Vis pump pulse is off-resonant with regard to the UV-Vis absorption band. Electronic excitation becomes only possible, if the infrared pump pulse modulates the UV-Vis transition of the IR-excited molecule. This modulation brings the UV-Vis transition in resonance with the UV-Vis pump pulse. Thereby, only the molecules which were pre-excited with the infrared pulse can be excited into the electronically excited state. A computational prediction of the modulation was carried out by Jan von Cosel in the Burghardt group.
The narrowband infrared pump pulse can be used to selectively excite a subensemble of molecules in a mixture into an electronically excited state even if the UV-Vis spectra of all molecules are virtually identical. For this the sub-ensemble needs to exhibit an identifiable infrared spectrum. Combined with the introduction of isotope labels, which lead to changes in the infrared absorption spectra, the larger selectivity in the infrared region can be exploited for an alternative selective uncaging approach. In VIPER uncaging the infrared pump pulse selects the species and the subsequent UV-Vis pulse provides the energy needed for electronic excitation upon which the photo cleavage can occur.
After an introduction of the principle idea of uncaging and VIPER spectroscopy, the concept of VIPER uncaging is introduced and its limits and requirements are discussed. Some examples for possible VIPER cages are reviewed.
A coumarin molecule (7-diethylamino coumarin) which can release an azide group was chosen as a first test molecule for VIPER uncaging. Its isotopomers were characterized to determine suitable spectroscopic markers for successful uncaging and to find fitting experimental conditions. The chosen coumarin cage has an UV-Vis absorption band at approximately 380 nm and a steep flank on the high wavelength side of the band. The quantum yield for the azide compound is between 10-20 % depending on the solvent’s water content. The release was found to be on a picosecond timescale which is among the fastest known photo reactions, but the photo reaction mechanism has proven to be not straightforward. For the VIPER experiment on the mixture two isotopomers were chosen with a 13C atom at different positions. In one species a ring mode of the coumarin is changed by the 13C atom. In the other isotopomer the carbonyl stretching mode is influenced. The change in the ring mode region allows to select one species or the other with the infrared pre-excitation. Because of experimental difficulties only isotopomers with the same leaving group could be used. The successful selective electronic excitation of the individual isotopomers in a mixture was monitored by probing the carbonyl region.
As a second VIPER cage, para-hydroxyphenacyl (pHP) was chosen. A thiocyanate group was selected as leaving group. pHP cages have their electronic transition in the UV, with a maximum absorption at 290 nm. The shape of the spectrum is suitable and the quantum yield is very high, with values in the literature of up to 90 %. Also the photo reaction is well studied and the expected byproducts are well characterized. The chosen isotopologues were characterized spectroscopically. The resulting data on the photo reaction were in agreement with the mechanism proposed in the literature. The mixture for the VIPER experiment consisted of two isotopologues, where for one species all the C atoms in the ring were labelled and for the other the C-atom in the thiocyanate leaving group was labelled. Here the release of the different leaving groups, labelled and unlabelled thiocyanate, could be monitored selectively. This shows that it is possible to selectively release a molecule in a mixture of caged molecules by applying the VIPER pulse sequence.
The samples were synthesized by Matiss Reinfelds from the Heckel group and the VIPER experiments were done together with Carsten Neumann and with support
of the Bredenbeck group.
The leaving groups were chosen because of their infrared absorption which allowed to directly monitor the successful cleavage by spectroscopy. This was needed for the proof-of-concept experiment and to allow direct optimization of the experimental parameters but is not necessarily a requirement for VIPER uncaging.
Concerning the selectivity of the VIPER uncaging, the approach is at the moment mainly limited by the infrared pulse energy. The selective VIPER excitation is competing with unselective excitation directly by just the UV-Vis pulse. A more intense infrared pump pulse would increase only the selective VIPER excitation and thereby improve the contrast to the unspecific background.
To address this issue, the first steps towards an alternative infrared light generation are undertaken. In this alternative approach the infrared light for preexcitation is directly generated by difference frequency generation of the laser output, i.e. the high energy 800 nm fundamental, and the output of a non-collinear optical parametric amplifier (NOPA). To achieve a narrowband pump pulse the pulses are chirped before mixing. In the scope of this thesis a NOPA has been installed and the mixing has been tested with available test crystal medium. While infrared wavelength region and power were not in the aspired range with this alternative crystal the feasibility of mixing between a NOPA output and the fundamental could be shown.
Other possibilities to increase the contrast to the unspecific background excitation by the UV-Vis pump pulse are discussed. For most applications of selective VIPER uncaging the detection by fs-laser spectroscopy will not be needed and could be replaced by other methods e.g. chromatography. This will allow the experimental parameters of the VIPER pulse sequence to be changed in a way which reduces unspecific excitation i.e. reducing the UV-Vis-pump energy and result in much better contrast.
In conclusion, the experimental data in this thesis shows the VIPER pulse sequence to be applicable to selective uncaging schemes and indicates measures to arrive at the specificity necessary for uncaging applications. This thesis was focused on uncaging photo reactions with isotopomers and isotopologues, but other types of photo reactions could in principle be controlled in the same way. It should be possible to address different isomers in mixtures or different ground states of proteins selectively. The discussed experiments are a significant step towards control over photo reactions in mixtures.
Cortical circuits exhibit highly dynamic and complex neural activity. Intriguingly, cortical activity exhibits consistently two key features across observed species and brain areas. First, individual neurons tend to be co-active in spatially localized domains forming orderly arranged, modular layouts with a typical spatial scale. Second, cortical elements are correlated in their activity over large distances reflecting long-range network interactions distributed over several millimeters. Currently, it is unclear how these two fundamental properties emerge in the early developing cortical activity.
Here, I aim to fill this gap by combining analyses of chronic imaging data and network models of developing cortical activity. Neural recordings of spontaneous and visually evoked activity in primary visual cortex of ferrets during their early cortical development were obtained using in vivo 2-photon and widefield epi-fluorescence calcium imaging. Spontaneous activity was used to probe the early state of cortical networks as its spatiotemporal organization is independent of a stimulus-imposed structure, and it is already present early in cortical development prior to reliably evoked responses. To assess the mature functional organization of distributed networks in cortex, the tuning of neural responses to stimulus features, in particular to the orientation of an edge-like stimulus, was assessed. Cortical responses to moving gratings of varying orientations form an orderly arranged layout of orientation domains extending over several millimeters.
To begin with, I showed that spontaneous activity correlations extend over several millimeters, supporting the assumption of using spontaneous activity to assess distributed networks in cortex.
Next, I asked how distributed networks in the mature visual cortex - assessed by spontaneous activity correlations - are related to its fine-scale functional organization. I found that the spatially extended and modular spontaneous correlation patterns accurately predict the fine spatial structure of visually evoked orientation domains several millimeters away. These results suggest a close relation between spontaneous correlations and visually evoked responses on a fine spatial scale and across large spatial distances.
As the principles governing the functional organization and development of distributed network interactions in the neocortex remain poorly understood, I next asked how long range correlated activity arises early in development. I found that key features of mature spontaneous activity introduced in this work, including long-range spontaneous correlations, were present already early in cortical development prior to the maturation of long-range, horizontal connections, and the predicted mature orientation preference layout. Even after silencing feed-forward input drive by inactivating retina or thalamus, long-range correlated and modular activity robustly emerged in early cortex. These results suggest that local recurrent connections in early cortical circuits can generate structured long-range network correlations that guide the formation of visually-evoked distributed functional networks.
To investigate how these large-scale cortical networks emerge prior to the maturation and elaboration of long-range horizontal connectivity, I examined a statistical network model describing an ensemble of spatially extended spontaneous activity patterns. I found a direct relationship between the dimensionality of this ensemble of activity patterns and the decay of its correlation structure. Specifically, reducing the dimensionality of the ensemble leads to an increase in the spatial range of the correlation structure.
To test whether this mechanism could generate a long-range correlation structure in cortical circuits, I studied a dynamical network model implementing a dimensionality reduction mechanism. Based on previous work demonstrating that network heterogeneity reduces the dimensionality of activity patterns, I showed that by increasing the degree of heterogeneity in the network, the dimensionality of the ensemble of activity patterns decreases and in turn their correlations extend over a greater range. A comparison to experimental data revealed a quantitative match between the network model and the observations in vivo in several of the key features of the early cortex including the spatial scale of correlations. Low dimensionality of spontaneous activity thus might provide an organizational principle explaining the observed long-range correlation structure in the early cortex.
Finally, I asked whether a network with a biologically plausible architecture can generate modular activity. Several classical models showed that modular activity patterns can emerge via an intracortical mechanism involving lateral inhibition. However, this assumption appears to be in conflict with current experimental evidence. Moreover, these network models were not experimentally tested, so far. Here, I showed by using linear stability analysis that spatially localized self-inhibition relaxes the constraints on the connectivity structure in a network model, such that biologically more plausible network motifs with shorter ranging inhibition than excitation can robustly generate modular activity.
Importantly, I also provided several model predictions to make the class of network models experimentally testable in view of recent technological advancements in imaging and manipulation of cortical circuits. A critical prediction of the model is the decrease in spacing of active domains when the total amount of inhibition increases. These results provide a novel mechanism of how cortical circuits with short-range inhibition can form modular activity.
Taken together, this thesis provides evidence that the two described fundamental features of neural activity are already present in the early cortex and shows that activity with those features can be generated in network models with an architecture consistent with the early cortex using basic principles.
The last decades have brought tremendous progress in understanding the phase structure of the strongly interacting matter. This has been driven by studying heavy-ion collisions on the experimental side and Lattice QCD, functional approaches to QCD, perturbation theory and effective theories on the theoretical side. Of particular interest is the transition from hadrons to partonic degrees of freedom which is expected to occur at high temperatures or high baryon densities. These phases play an important role in the early universe and the core of neutron stars. Nowadays, the existence of a deconfined phase, i.e. Quark Gluon Plasma (QGP) and its phase transition at vanishing and small net-baryon densities, are well established. However, the situation at larger densities is less clear.
Complementary to the studies of matter at high temperatures and low net-baryon densities performed at RHIC and LHC, the proposed Compressed Baryonic Matter (CBM) experiment at the future FAIR facility, aims to explore the QCD phase diagram at very high baryon-net densities and moderate temperatures. The CBM research program includes the search for the deconfinement phase transition, the study of chiral symmetry restoration in super dense baryonic matter, the search for the critical endpoint, and the study of the nuclear equation of state at high densities. While other experiments (STAR-BES at BNL, BM@N at NICA) are suited to measure bulk observables, CBM is explicitly designed to access rare observables, such as multi-strange hadrons, dileptons, hypernuclei and charmonium. Therefore, a key feature of CBM is the very high interaction rate, exceeding those of contemporary and proposed nuclear collision experiments by several orders of magnitude. However, some of the rare probes have a complex signature, hidden in a background of several hundreds of charged tracks. This forbids a conventional, hardware-triggered readout; instead, the experiment combines self-triggered front-end electronics, fast and free-streaming data transport, online event reconstruction and online event selection.
The central detector for tracking and momentum determination of charged particles in the CBM experiment is the Silicon Tracking System (STS). It is designed to measure up to 700 charged particles in nucleus-nucleus collisions between 0.1 and 10 MHz interaction rate, to achieve a momentum resolution in 1 Tm dipole magnetic field better than 2%, and to be capable of identifying complex particle decays topologies, e.g., such with strangeness content. The STS comprises 8 tracking stations equipped with double-sided silicon microstrip sensors. Two million channels are read out with self-triggering electronics, matching the data streaming and on-line event analysis concept applied throughout the experiment. The detector’s functional building block consists of a silicon sensor, aluminum-kapton microcables and two front-end electronics boards integrated in a module. The custom-designed ASIC (STS-XYTER) implements the analog front-end, the digitizer and the generation of individual hit data for each signal.
Design of the front-end chip requires finding an optimal solution for time and input charge measurements with tight constraints: small area (58 μm channel pitch), low noise levels (below 1500 ENC(e− )), low power consumption (610 mW/channel), radiation hard architecture and speed requirements. Being a part of the first processing stage in the full readout and data acquisition chain, the characterization of the chip and its integration with the detector components is a crucial task. In this work, various methods and tools are established for testing and qualifying the ASIC analog front-end. A procedure for amplitude and timing calibration is developed using different functionalities of the chip. The procedure is optimized for our prototype system in order to achieve the best accuracy in the shortest amount of time. Results were verified using a gamma source and an external pulse generator, showing discrepancies below 5%.
Among the multiple operation requirements of the ASIC, the noise performance is of essential importance. The characterization of the chip noise is carried out as a function of a large number of parameters such as: low-voltage power regulators, input capacitance, shaping time, temperature and bond’s protective glue (glob-top). These studies allowed to optimize the ASIC configuration settings, to identify possible malfunctions in the low voltage powering scheme and to select possible glob-top materials to be used in the module assembly. Moreover, important differences are found among odd and even channels, which main cause was related to the bias scheme of the amplifiers of the two groups of channels. This effect has been corrected in the new version (v2.1) of the ASIC.
Despite the STS front-end electronics being located outside of the physics acceptance, they will be exposed to high fluxes of charged particles. Considering the SIS100 possible running scenario, the lifetime dose at the location of the electronics is expected not to exceed 800 krad. Consequently, the STS-XYTERv2 ASIC implements a radiation hard design based on dual-interlocked cells (DICE), and triple modular redundancy (TMR).
Multiple dedicated beam campaigns were carried out to evaluate the ASIC’s design in terms of immunity to single event upsets (SEU) errors and overall performance after a lifetime doses. The DICE cell SEU cross section was measured in a high-intensity proton beam. Result show a significant improvement of the SEU immunity in the STS-XYTERv2 compared to its predecessor, and allows to estimate the upset rate in the CBM running scenario, resulting in less than one SEU/ASIC/day.
The studies on the total ionizing dose (TID) show that the overall noise levels for the ASIC, at the end of the experiment lifetime, are expected to increase by approximately 40 – 60%. Moreover, they demonstrated that short periods of annealing at room temperature can favorably influence the noise performance of the chip.
The assembly and test of the STS modules, a complex process with multiple stages and a long learning curve, is illustrated in different parts of this work. The first prototype modules were built with the front-end board type B (FEBs-B), capable of reading out 128 channels for p and n side respectively. The studies were conducted with a relativistic proton beam of 1.7 GeV/c momentum at the COSY accelerator facility, Research Center Juelich, in March 2018. The campaign brought valuable insights to the development of an effective grounding and powering scheme for reading out the detectors. The signal-to-noise was measured for one of the prototype modules, resulting in values larger than 15 for both polarities. A deeper analysis into the collected data allowed the identification of a logic error in the ASIC that affected the readout rate and the quality of the data. This issue was corrected in the new version of the chip.
A precursor of the STS detector, named mini-STS (mSTS), has been built within the mCBM project carried out in FAIR Phase0. mSTS was built from 4 fully assembled detector modules. To ensure the proper operation of the ASICs that were used in the module assembly, it was required to develop a rigorous quality assurance procedure. A dedicated setup was built based on a custom designed pogo-pin station and a total of 339 chips were tested. More than 90% of good-quality and operational ASICs were obtained. In the mCBM beam campaign of March 2019, four detector modules were successfully operated in a close-to-final readout chain and valuable data were collected. The mSTS detector was exposed to the products of Ag+Au collisions at energies above 1.58 AGeV and overall interaction rates up to 106 , which resembles the real conditions of the CBM experiment.
Along this work, significant progress for the development of the STS detector modules was achieved. Techniques for characterization of the front-end electronics and the complete detector system were developed and worked out. They will be applied for QA of the components during the series production.
As its fundamental function, the brain processes and transmits information using populations of interconnected nerve cells alias neurons. The communication between these neurons occurs via discrete electric impulses called spikes. A core challenge in neuroscience has been to quantify how much information about relevant stimuli or signals a neuron transports in its spike sequences, or spike trains. The recently introduced correlation method allows to determine this so-called mutual information in terms of a neuron’s temporal spike correlations under certain stationarity assumptions. Based on the correlation method, I address several open questions regarding neural information encoding in the cortex.
In the first part (chapter 2), I investigate the role of temporal spike correlations for neural information transmission. Temporal correlations in neuronal spike trains diminish independence in the information that is transmitted by the different spikes and hence introduce redundancy to stimulus encoding. However, exact methods to describe how such spike correlations impact information transmission quantitatively have been lacking. Here, I provide a general measure for the information carried by spike trains of neurons with correlated rate modulations only, neglecting other spike correlations, and use it to investigate the effect of rate correlations on encoding redundancy. I derive it analytically by calculating the mutual information between a time correlated, rate-modulating signal and the resulting spikes of Poisson neurons. Whereas this information is determined by spike autocorrelations only, the redundancy in information encoding due to rate correlations depends on both the distribution and the autocorrelation of the rate histogram. I further demonstrate that, at very small signal strengths, the information carried by rate correlated spikes becomes identical to that of independent spikes, in effect measuring the rate modulation depth. In contrast, a vanishing signal correlation time maximizes information transmission but does not generally yield the information of independent spikes.
In the second part (chapter 3), I analyze the information transmission capabilities of two particular schemes of encoding stimuli in the synaptic inputs using integrate-and-fire neuron models. Specifically, I calculate the exact information contained in spike trains about signals which modulate either the mean or the variance of the somatic currents in neurons, as is observed experimentally. I show that the information content about mean modulating signals is generally substantially larger than about variance modulating signals for biological parameters. This result provides evidence, by means of exact calculations of the mutual information, against the potential benefit of variance encoding that had been suggested previously.
Another analysis reveals that higher information transmission is generally associated with a larger proportion of nonlinear signal encoding. Moreover, I show that a combination of signal-dependent mean and variance modulations of the input current can synergistically benefit information transmission through a nonlinear coupling of both channels. On a more general level, I identify what was previously considered an upper bound as the exact, full mutual information. Furthermore, by analyzing the statistics of the spike train Fourier coefficients, I identify the means of the Fourier coefficients as information-carrying features.
Overall, this work contributes answers to central questions of theoretical neuroscience concerning the neural code and neural information transmission. It sheds light on the role of signal-induced temporal correlations for neural coding by providing insight into how signal features shape redundancy and by establishing mathematical links between existing methods and providing new insights into the spike train statistics in stationary situations. Moreover, I determine what fraction of the mutual information is linearly decodable for two specific signal encoding schemes.
In this thesis, we presented the theoretical description of the magnetic properties of various frustrated spin systems. Especially in search of exotic states, such as quantum spin liquids, magnetically frustrated systems have been subject of intense research within the last four decades. Relating experimental observations in real materials with theoretical models that capture those exotic magnetic phenomena has been one of the great challenges within the field of magnetism in condensed matter.
In order to build such a bridge between experimental observations and theoretical models, we followed two complementary strategies in this thesis. One strategy was based on first principles methods that enable the theoretical prediction of electronic properties of real materials without further experimental input than the crystal structure. Based on these predictions, low-energy models that describe magnetic interactions can be extracted and, through further theoretical modelling, can be compared to experimental observations. The second strategy was to establish low-energy models through comparison of data from experiments, such as inelastic neutron scattering intensities, with calculated predictions based on a variety of plausible magnetic models guided by microscopic insights. Both approaches allow to relate theoretical magnetic models with real materials and may provide guidance for the design of new frustrated materials or the investigation of promising models related to exotic magnetic states.
The diffusive behavior of macromolecules in solution is a key factor in the kinetics of macromolecular binding and assembly, and in the theoretical description of many experiments. Experiments on high-density protein solutions have found that a slow down of the diffusion dynamics is larger than expected from colloidal theory for non-interaction hard-spheres. It has also been shown that the rotational diffusion anisotropy in high-density protein solutions is larger than in dilute ones. High-density protein solutions are a complex fluid that is different from the neat fluid assumption used in the hydrodynamic theory. It is therefore important to have methods to accurately calculate the translational and rotational diffusion tensor from simulations as well as simulation algorithms to explore high-density solutions.
Simulations provide a powerful tool to study diffusion in complex fluids. They can be used to study the macroscopic and microscopic effects of complex fluids on the diffusive behavior. There has been already a lot of work done to accurately simulate diffusion and to determine the diffusion coefficients from simulations.
The translational diffusion of molecules in simple and complex liquids can be determined with high accuracy from simulations. This is not yet the case for rotational diffusion. Existing algorithms to calculate the rotational diffusion coefficients from simulations make assumptions about the shape of the protein or only work at short times. For the simulation of diffusive behavior of macromolecules two options exist today. An all-atom integrator with explicit solvent molecules or coarse-grained (CG) simulations with an implicit solvent. CG simulations of dynamic behavior with implicit solvent are also called Brownian dynamics (BD) simulations. For the CG simulations the Ermak-McCammon algorithm is often used to solve the underlying Langevin equation. The algorithm is an extension of the Euler-Maruyama integrator to include translation and rotation in three dimensions. This algorithm only correctly reproduces the equilibrium probability for short time-steps and the error depends linearly on the time-step. It has been shown that Monte Carlo based algorithms can produce BD for translational dynamics, when appropriately parametrized. The advantage of Monte Carlo based algorithm is that they will reproduce the correct equilibrium distribution independent of the chosen time-step. This in return allows choosing larger time-steps in simulations. The aim of this thesis is to develop novel´methods to accurately determine the rotational diffusion coefficient from simulations and extend existing Monte Carlo algorithms to include rotational dynamics.
The first project addresses the question of how to accurately determine the rotational diffusion coefficients from simulations. We develop a quaternion based method to calculate the rotational diffusion tensor from simulations and a theory for the effects of periodic boundary conditions (PBC) on the rotational diffusion coefficient in simulations.
Our method for calculating rotational diffusion coefficients is based on the quaternion covariances from Favro for a freely rotating rigid molecule. The covariances as formulated by Favro are only valid in the principal coordinate system (PCS) of the rotation diffusion tensor. The covariances can be generalized for an arbitrary reference coordinate system (RCS), i.e., a simulation, given the principle axes of the rotational diffusion tensor in the RCS. We show that no prior knowledge of the diffusion tensor and its principal axes is required to calculate the generalized covariances from simulations using common root-mean-square distance (RMSD) procedures. We develop two methods to fit the covariances calculated from simulations to our generalized equations to fit the rotational diffusion tensor. In the first method we minimize the sum of the squared error deviations between model and simulation data. For this six dimensional optimization we use a simulated annealing algorithm. Alternatively the rotational diffusion tensor can also be determined from a eigenvalue decomposition of covariance after integration. To minimize the effects of sampling noise in the integration we first apply a Laplace-transformation to smooth the covariances at large times. For ideal sampling the resulting rotational diffusion coefficient should be independent of the value of the Laplace variable. In practice, however, the best results are achieved using a value close to the inverse autocorrelation time of the rotational motion.
...
In this work we provided additional insights into our understanding of bulk QCD matter through the study of the transport coeffcients which govern the non-equilibrium microscopical processes of statistical ensembles. Specically, we focused on the low energy regime corresponding to the hadron gas, as the properties of this region of the phase diagram are still relatively unknown, and existing calculations for the transport coeffcients are either scarce, contradictory, or somewhat limited in scope; this thesis' main goal was thus to shed some light on this by providing new independent calculations of these quantities.
We subsequently presented two formalisms which can be used to calculate transport coeffcients. The first one (which also was the main tool we used in the following chapters to produce our results) relies on the development of so-called Green-Kubo formulas, which relate non-equilibrium dissipative fluctuations with transport coeffcients; notably, the off-diagonal components of the energy-momentum tensor are shown to be related to the shear viscosity, its diagonal components to the bulk viscosity and fluctuations in the electric current can be related to the electric conductivity. We additionally introduced two new conductivities, namely the baryon-electric and strange electric conductivities, which we dubbed, together with the already known electric one, the "cross-conductivity", which encodes information about how electric fluctuations are correlated to changes in electric, baryonic or strange currents, or vice-versa. The second way of calculating transport coeffcient which we discussed consists in linearizing the collision term of the Boltzmann equation through the Chapman-Enskog formalism. While in principle providing direct semi-analytical results for the transport coeffcients, this approach is complicated to implement when more than a few species are considered, and as such was then mostly used as a tool to calibrate our Green-Kubo calculations.
The hadron gas model that we used for all calculations, namely the transport approach SMASH, was then presented. The main features of the model were explained, such as the collision criterion, the considered degrees of freedom and the specific way in which they microscopically interact with each other. It was verified that SMASH does reproduce analytical results of the Boltzmann equation in an expanding universe scenario, thus showing the equivalence of this transport approach and the associated kinetic theory results. A special care was taken to detail the ways in which a state of thermal and chemical equilibrium (which is necessary for Green-Kubo relations to be valid) can be reached and described using SMASH.
...
We study the Wigner function for massive spin-1/2 fermions in electromagnetic fields. The Wigner function is analytically solved in five cases when electromagnetic fields are constants. For a general space-time dependent field configuration, we use the method of semi-classical expansion and solved the Wigner function at linear order in the Planck's constant. At the same order, we obtained a generalized Boltzmann equation for particle distribution, and a generalized BMT equation for spin polarization. Using the Wigner function, we calculated some physical quantities in a thermal equilibrium system.
The present thesis is primarily concerned with the application of the functional renormalization group (FRG) to spin systems. In the first part, we study the critical regime close to the Berezinskii-Kosterlitz-Thouless (BKT) transition in several systems. Our starting point is the dual-vortex representation of the two-dimensional XY model, which is obtained by applying a dual transformation to the Villain model. In order to deal with the integer-valued field corresponding to the dual vortices, we apply the lattice FRG formalism developed by Machado and Dupuis [Phys. Rev. E 82, 041128 (2010)]. Using a Litim regulator in momentum space with the initial condition of isolated lattice sites, we then recover the Kosterlitz-Thouless renormalization group equations for the rescaled vortex fugacity and the dimensionless temperature. In addition to our previously published approach based on the vertex expansion [Phys. Rev. E 96, 042107 (2017)], we also present an alternative derivation within the derivative expansion. We then generalize our approach to the O(2) model and to the strongly anisotropic XXZ model, which enables us to show that weak amplitude fluctuations as well as weak out-of-plane fluctuations do not change the universal properties of the BKT transition.
In the second part of this thesis, we develop a new FRG approach to quantum spin systems. In contrast to previous works, our spin functional renormalization group (SFRG) does not rely on a mapping to bosonic or fermionic fields, but instead deals directly with the spin operators. Most importantly, we show that the generating functional of the irreducible vertices obeys an exact renormalization group equation, which resembles the Wetterich equation of a bosonic system. As a consequence, the non-trivial structure of the su(2) algebra is fully taken into account by the initial condition of the renormalization group flow. Our method is motivated by the spin-diagrammatic approach to quantum spin system that was developed more than half a century ago in a seminal work by Vaks, Larkin, and Pikin (VLP) [Sov. Phys. JETP 26, 188 (1968)]. By embedding their ideas in the language of the modern renormalization group, we avoid the complicated diagrammatic rules while at the same time allowing for novel approximation schemes. As a demonstration, we explicitly show how VLP's results for the leading corrections to the free energy and to the longitudinal polarization function of a ferromagnetic Heisenberg model can be recovered within the SFRG. Furthermore, we apply our method to the spin-S Ising model as well as to the spin-S quantum Heisenberg model, which allows us to calculate the critical temperature for both a ferromagnetic and an antiferromagnetic exchange interaction. Finally, we present a new hybrid formulation of the SFRG, which combines features of both the pure and the Hubbard-Stratonovich SFRG that were published recently [Phys. Rev. B 99, 060403(R) (2019)].