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The COLTRIMS Reaction Microscope C-REMI can image the momentum vectors of all emitted charged fragments in an atomic or molecular reactions similar to the bubble chamber in high energy particle physics. C-REMI can detect fragments with “zero” kinetic energy in an ultrahigh vacuum environment by projecting them with weak electromagnetic fields onto position-sensitive detectors. Geometrically a nearly 4π collection solid angle and a nearly 50% efficiency for a fivefold multi-coincidence can be achieved. Measuring time-of-flight and detector position the momenta of the fragments can be measured with excellent resolution (<0.01 a.u.; see A1 in the Appendix). Thus, multivector correlations in momentum space are measured, which provide insight into the entangled dynamics of atomic and molecular quantum systems. From these vector-correlations phases and energies can be deduced which allow for relative time measurements even in the zeptosecond range. C-REMI provides a “spyhole” into the secrets of ultrafast dynamics of atomic and molecular processes. It is applied today around the globe in numerous research projects in physics and chemistry. The purpose for writing this article is to demonstrate the universal application possibilities of C-REMI, and its high multi-coincidence efficiency and high momentum resolution. This paper will not give a review on all milestone experiments performed with C-REMI.
Neurons are cells with a highly complex morphology; their dendritic arbor spans up to thousands of micrometers. This extended arbor poses a challenge for the logistics of neuronal processes: mRNA, proteins, and organelles have to be transported to dendrites, hundreds of micrometers away from the soma. This thesis aims to calculate the minimum number of proteins needed to populate the dendritic trees for different scenarios.
In chapter 2, I analyzed the ability of different mechanisms to populate the dendritic arbor. I started from the solution of the diffusion equation in Sec. 2.1, then I included the contribution of active transport in Sec. 2.2 and showed how it could have either the effect of increasing the effective diffusion coefficient or of introducing a bias in the diffusion process. In Sec. 2.3 I studied the spatial distribution of locally synthesized protein, accordingly with actively and passively transported mRNA. In Sec. 2.5, I derived the boundary condition for branches showing a qualitatively different behavior of surface and cytoplasmic proteins induced by the medium’s dimensionality in which they diffuse.
In chapter 3, I introduced the concept of protein requirement, defined as the minimum number of proteins that the neuron needs to produce to provide at least one protein to each micrometer of the dendritic arbor. In Sec. 3.1, I derived the protein requirement for diffusive proteins for somatic translation and constant translation in the dendritic arbor. In Sec. 3.2, I analyzed numerically the protein requirement in the case of actively transported protein synthesized in the soma, and, in Sec. 3.3, in the case of actively transported proteins synthesized in the dendritic arbor. In Sec. 3.4, I analyzed the protein requirement of protein synthesized in the dendrite accordingly with the distribution of mRNA described in Sec. 3.3 and 3.2. In Sec. 3.5, I derived the protein requirement for a single branch and purely diffusive proteins.
In chapter 4, I analyzed the relation between the radii of the three afferent dendrites in a branch, their length, and the diffusion length of a protein. In Sec. 4.1 I derived the optimal ratio between the radii of the daughter dendrites that minimizes the protein requirement. In Sec. 4.3 I introduced the 3/2− Rall Rule and in Sec. 4.5 its generalization. Finally, I used those rules to estimate the fraction of proteins diffusing away from and toward the soma.
In chapter 5, I analyzed the radii distribution for three categories of neurons: cultured hippocampal neurons in Sec. 5.1, stomatogastric ganglia neuron in Sec. 5.2, and 3DEM reconstructed prefrontal pyramidal neurons in Sec. 5.3. For each of these three classes, I analyzed the distribution of radii, Rall exponents, and the probability ratio. For most of them, I found that the probability of a protein diffusing away from the soma is higher for surface proteins than for cytoplasmic ones. I quantified this with a parameter called surface bias.
In Chapter 6, I analyzed the fluorescent ratio imaged by our collaborators Anne-Sophie Hafner, for a surface protein, GFP::Nlg, and a soluble one, GFP, in cultured hippocampal neurons, and I compared the fluorescent ratio with the probability ratio obtained in 5.1, finding that they are in good agreement.
In chapter 7, I compared the real dendritic morphologies imaged by one of our collaborators Ali Karimi with the optimal branching rule obtained in Sec. 4.1 and I calculated the cost for not having optimal branching radii.
Finally, in Chapter 8, I used the knowledge of the branching statistics gathered in 5.3 to simulate the protein profile on three different classes of neurons: pyramidal neurons, granule neuron, and Purkinje neurons. I compared the protein profile for surface and cytoplasmic neurons for each morphology for two different values of the diffusion length: λ = 109µm and λ = 473µm, both for optimized radii and symmetrical radii. I showed how the radii optimization reduces the protein requirement of a factor 10 4 for pyramidal neurons.
New drugs are urgently needed to combat the global TB epidemic. Targeting simultaneously multiple respiratory enzyme complexes of Mycobacterium tuberculosis is regarded as one of the most effective treatment options to shorten drug administration regimes, and reduce the opportunity for the emergence of drug resistance. During infection and proliferation, the cytochrome bd oxidase plays a crucial role for mycobacterial pathophysiology by maintaining aerobic respiration at limited oxygen concentrations. Here, we present the cryo-EM structure of the cytochrome bd oxidase from M. tuberculosis at 2.5 Å. In conjunction with atomistic molecular dynamics (MD) simulation studies we discovered a previously unknown MK-9-binding site, as well as a unique disulfide bond within the Q-loop domain that defines an inactive conformation of the canonical quinol oxidation site in Actinobacteria. Our detailed insights into the long-sought atomic framework of the cytochrome bd oxidase from M. tuberculosis will form the basis for the design of highly specific drugs to act on this enzyme.
How long does it take to emit an electron from an atom? This question has intrigued scientists for decades. As such emission times are in the attosecond regime, the advent of attosecond metrology using ultrashort and intense lasers has re-triggered strong interest on the topic from an experimental standpoint. Here, we present an approach to measure such emission delays, which does not require attosecond light pulses, and works without the presence of superimposed infrared laser fields. We instead extract the emission delay from the interference pattern generated as the emitted photoelectron is diffracted by the parent ion’s potential. Targeting core electrons in CO, we measured a 2d map of photoelectron emission delays in the molecular frame over a wide range of electron energies. The emission times depend drastically on the photoelectrons’ emission directions in the molecular frame and exhibit characteristic changes along the shape resonance of the molecule.
The first part of this work addresses the automatic online tuning of transfer lines in particle accelerator facilities. In the second part the focus lies on the automatic construction and optimisation of such transport lines. It can be shown that genetic algorithms can be used very well for optimisation in both cases. Automatic online tuning can be performed very efficiently at accelerators under certain boundary conditions and is particularly well suited for initial beam commissioning with low intensity pilot beams. The construction of transfer lines can also be formulated and solved as an minimisation problem with an adopted parameterisation. Thereby, both the imaging properties of the beam transport and the robustness against error studies can be optimised at the same time.
The main focus of research in the field of high-energy heavy-ion physics is the study of the quark-gluon plasma (QGP). Topic of the present work is the measurement of electron-positron pairs (dielectrons), which grant direct access to some of the key properties of this state of matter, since after their formation they leave the hot and dense medium without significant interaction. In particular, the measurement of the initial QGP temperature is considered a "holy grail" of heavy-ion physics. Therefore, in addition to the analysis of existing data, a feasibility study has been conducted to determine to which extent this goal would be achievable by upgrading the ALICE experiment at CERN.
Dielectrons are produced during all stages of a heavy-ion collision, with their invariant mass reflecting the amount of energy available at the time of their formation. Dielectrons of highest mass are thus produced in the initial scatterings of the colliding nuclei by quark-antiquark annihilation. Correlated electron-positron pairs can also emerge from the decay chains of early-produced pairs of heavy-flavour (HF) particles. During the QGP stage and at the beginning of the hadronic phase, the system emits thermal radiation in the form of photons and dielectrons, which carry information about the medium temperature to the observer. In the final stage of the collision, decays of light-flavour (LF) hadrons produce additional contributions to the dielectron spectrum.
The present work is based on early data from the ALICE experiment recorded from lead-lead collisions at a center-of-mass energy of 2.76 TeV. Due to the limited amount of data, a focus is placed on achieving high efficiencies throughout the analysis. To this end, a special electron identification strategy is developed and a custom track selection applied, together resulting in a tenfold increase in pair efficiency. The dielectron spectrum is evaluated on a statistical basis, using a pair prefilter, which is optimized based on two signal quality criteria, to reduce the fraction of electrons and positrons from unwanted sources at minimum signal loss. In addition, an artifact of the track reconstruction is exploited to suppress pairs from photon conversions and to correct the dielectron yield for a contribution from different-conversion pairs. The main signal uncertainty is extracted from the deviation between results of 20 analysis settings and amounts to 20% in most of the studied kinematic range.
For comparison with the analysis results, a hadronic cocktail consisting of the LF and HF contributions is simulated, which can reasonably well describe the measured dielectron production, with a hint of an enhancement at low invariant mass. Two approaches to model the in-medium modification of the heavy-flavour are followed, resulting in up to 50% suppression, which creates some additional space for a thermal contribution at intermediate mass.
For a complete comparison between experimental data and theoretical expectation, two model calculations are consulted. The Thermal Fireball Model provides predictions for thermal dielectron radiation from the QGP and hadron gas. The data tends to be better described with these additional thermal contributions. For a comparison with a prediction by the UrQMD model, the HF component of the cocktail is subtracted from the data. This results in better agreement if the HF suppression by in-medium effects is taken into account.
The feasibility study in this work has served as a physical motivation for the ALICE upgrade for LHC Run 3. The precision with which the early temperature of the QGP can be determined via dielectrons is chosen as key observable. A multitude of individual contributions are merged into a fully modeled dielectron analysis. The resulting signal-to-background ratio represents some of the expected systematic uncertainties, while from the significance combined with the planned number of lead-lead collisions a realistic "measurement" with statistical fluctuations around the expected dielectron signal is generated using a Poisson sampling technique. Since the HF yield exceeds the QGP thermal radiation by about an order of magnitude, an additional analysis step exploiting the enhanced track reconstruction is introduced to reduce its contribution by up to a factor of five. The resulting reduction in pair efficiency is overcompensated by an up to hundred times higher collision rate. The entire cocktail is then subtracted from the sampled data to isolate the thermal excess yield. The final analysis of this spectrum shows that the inverse slope of the model prediction, which depends directly on the QGP temperature, can be reproduced within statistical and systematic uncertainties of about 10%.
The promising results of this study have contributed on the one hand to the realization of the ALICE upgrade and to a design decision for the new Inner Tracking System, and at the same time represent exciting predictions for upcoming measurements.
As part of the research for this thesis, a momentum spectrometer was set up and initial measurements on accelerated ions were performed. For this purpose, the necessary hardware for the operation of the spectrometer and for high-precision measurements was were assembled. A control system for remote operation was developed and the spectrometer was installed at the used beamline.
There, measurements of low-energy ion beams in superposition with electrons confined in a Gabor lens can be carried out.
Investigations were made on both the Gabor lens-generated ions and the beam ions, leading to first results regarding the charge changes of beam ions during propagation through an electron atmosphere.
Computational workflow optimization for magnetic fluctuation measurements of 3D nano-tetrapods
(2021)
The detailed understanding of micro–and nanoscale structures, in particular their magnetization dynamics, dominates contemporary solid–state physics studies. Most investigations already identified an abundance of phenomena in one–and two–dimensional nanostructures. The following thesis focuses on the magnetic fingerprint of three–dimensional CoFe nano–magnets, specifically the temporal development of their hysteresis loop. These nano–magnets were grown in a tetrahedral pattern on top of a highly susceptible home–build GaAs/AlGaAs micro–Hall sensor using focused electron beam induced deposition (FEBID).
During the measurements, utmost efforts were employed to exemplify current best research practices. The data life cycle of the present thesis is based upon open–source data science tools and packages. Data acquisition and analysis required self–written automated algorithms to handle the extensive quantity of data. Existing instrumental-controlling software was improved, and new Python packages were devised to analyze and visualize the gathered data. The open–source Python data analysis framework (ana) was developed to facilitate computational reproducibility. This framework transparently analyses and visualizes the gathered data automatically using Continuous Analysis tools based on GitLab and Continuous Integration. This automatization uses bespoke scripts combined with virtualization tools like Docker to facilitate reproducible and device–independent results.
The hysteresis loops reveal distinct differences in subsequently measured loops with identical initial experimental parameters, originating from the nano–magnet’s magnetic noise. This noise amplifies in regions where switching processes occur. In such noise–prone regions, the time–dependent scrutinization reveals presumably thermally induced metastable magnetization states. The frequency–dependent power spectral density uncovers a characteristic 1/f² behavior at noise–prone regions with metastable magnetization states.
For a long time, strong coupling expansions have not been applied systematically in lattice QCD thermodynamics, in view of the success of numerical Monte Carlo studies. The persistent sign problem at finite baryo-chemical potential, however, has motivated investigations using these methods, either by themselves or combined with numerical evaluations, as a route to finite density physics. This article reviews the strategies, by which a number of qualitative insights have been attained, notably the emergence of the hadron resonance gas or the identification of the onset transition to baryon matter in specific regions of the QCD parameter space. For the simpler case of Yang–Mills theory, the deconfinement transition can be determined quantitatively even in the scaling region, showing possible prospects for continuum physics.
We study the μ-μ45-T phase diagram of the 2+1-dimensional Gross-Neveu model, where μ denotes the ordinary chemical potential, μ45 the chiral chemical potential and T the temperature. We use the mean-field approximation and two different lattice regularizations with naive chiral fermions. An inhomogeneous phase at finite lattice spacing is found for one of the two regularizations. Our results suggest that there is no inhomogeneous phase in the continuum limit. We show that a chiral chemical potential is equivalent to an isospin chemical potential. Thus, all results presented in this work can also be interpreted in the context of isospin imbalance.