## 80.00.00 INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY

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Acceleration is a central aim of clinical and technical research in magnetic resonance imaging (MRI) today, with the potential to increase robustness, accessibility and patient comfort, reduce cost, and enable entirely new kinds of examinations. A key component in this endeavor is image reconstruction, as most modern approaches build on advanced signal and image processing. Here, deep learning (DL)-based methods have recently shown considerable potential, with numerous publications demonstrating benefits for MRI reconstruction. However, these methods often come at the cost of an increased risk for subtle yet critical errors. Therefore, the aim of this thesis is to advance DL-based MRI reconstruction, while ensuring high quality and fidelity with measured data. A network architecture specifically suited for this purpose is the variational network (VN). To investigate the benefits these can bring to non-Cartesian cardiac imaging, the first part presents an application of VNs, which were specifically adapted to the reconstruction of accelerated spiral acquisitions. The proposed method is compared to a segmented exam, a U-Net and a compressed sensing (CS) model using qualitative and quantitative measures. While the U-Net performed poorly, the VN as well as the CS reconstruction showed good output quality. In functional cardiac imaging, the proposed real-time method with VN reconstruction substantially accelerates examinations over the gold-standard, from over 10 to just 1 minute. Clinical parameters agreed on average.
Generally in MRI reconstruction, the assessment of image quality is complex, in particular for modern non-linear methods. Therefore, advanced techniques for precise evaluation of quality were subsequently demonstrated.
With two distinct methods, resolution and amplification or suppression of noise are quantified locally in each pixel of a reconstruction. Using these, local maps of resolution and noise in parallel imaging (GRAPPA), CS, U-Net and VN reconstructions were determined for MR images of the brain. In the tested images, GRAPPA delivers uniform and ideal resolution, but amplifies noise noticeably. The other methods adapt their behavior to image structure, where different levels of local blurring were observed at edges compared to homogeneous areas, and noise was suppressed except at edges. Overall, VNs were found to combine a number of advantageous properties, including a good trade-off between resolution and noise, fast reconstruction times, and high overall image quality and fidelity of the produced output. Therefore, this network architecture seems highly promising for MRI reconstruction.

Protein folding achieves a clear solution structure in a huge parameter space (the so-called protein folding problem). Proteins fold in water, and get by this a highly ordered structure. Finally, inside a protein crystal for structure resolution, you have everywhere the same symmetries as there is everywhere the same unit cell. We apply this to qubit interactions to do fundamental physics:
in a modified cosmology, we replace the big bang by a condensation event in an eternal all-encompassing ocean of free qubits. Interactions of qubits in the qubit ocean are quite rare but provide a nucleus or seed for a new universe (domain) as the qubits become decoherent and freeze-out into defined bit ensembles. Second, we replace inflation by a crystallization event triggered by the nucleus of interacting qubits to which rapidly more and more qubits attach (like in everyday crystal growth). The crystal unit cell guarantees same symmetries everywhere inside the crystal. The textbook inflation scenario to explain the same laws of nature in our domain is replaced by the unit cell of the crystal formed.
Interacting qubits solidify, quantum entropy decreases (but increases in the ocean around). In a modified inflation scenario, the interacting qubits form a rapidly growing domain where the n**m states become separated ensemble states, rising long-range forces stop ultimately further growth. Then standard cosmology with the hot fireball model takes over. Our theory agrees well with lack of inflation traces in cosmic background measurements. We explain by cosmological crystallization instead of inflation: early creation of large-scale structure of voids and filaments, supercluster formation, galaxy formation, and the dominance of matter: the unit cell of our crystal universe has a matter handedness avoiding anti-matter.
We prove initiation of qubit interactions can only be 1,2,4 or 8-dimensional (agrees with E8 symmetry of our universe). Repulsive forces at ultrashort distances result from quantization, long-range forces limit crystal growth. Crystals come and go in the qubit ocean. This selects for the ability to lay seeds for new crystals, for self-organization and life-friendliness.
The phase space of the crystal agrees with the standard model of the basic four forces for n quanta. It includes all possible ensemble combinations of their quantum states m, a total of n**m states. Neighbor states reach according to transition possibilities (S-matrix) with emergent time from entropic ensemble gradients. However, in our four dimensions there is only one bit overlap to neighbor states left (almost solid, only below Planck quantum there is liquidity left). The E8 symmetry of heterotic string theory has six curled-up, small dimensions which help to keep the qubit crystal together and will never expand.
Mathematics focusses on the Hurwitz proof applied to qubit interaction, a toy model of qubit interaction and repulsive forces of qubits. Vacuum energy gets appropriate low inside the crystal. We give first energy estimates for free qubits vs bound qubits, misplacements in the qubit crystal and entropy increase during qubit decoherence / crystal formation. Scalar fields for color interaction/confinement and gravity are derived from the qubit-interaction field.

Single-molecule dynamics at a bottleneck: a systematic study of the narrow escape problem in a disc
(2023)

Diffusion facilitates numerous reactions within the biological context of a cell. It is remarkable how the cost-efficient random process of Brownian motion promotes fast reactions. From the narrow escape theory, it is possible to determine the mean first passage time of such processes based on their reaction space and diffusion coefficient. The narrow escape theory of Brownian particles is characterized by a confining domain with reflective boundaries and a small reaction site. In this thesis, the mean first passage time was systematically tested in a disc as a function of the escape opening size in vitro and in silico. For the in vitro experiments, a model system of patterned supported-lipid bilayers (SLB) was established. Such a model is prepared by a combined colloid metalization approach, where a gold scaffold on glass facilitates assembly of SLB patches of distinct sizes through vesicle fusion. The model setup was evaluated and found to match all necessary requirements to test the nar- row escape problem in vitro. In particular, the reflectivity of the boundaries, the unhindered, free diffusion of the tracer lipids, and the distinct area were assessed. Observed results of the mean first passage time agreed with the theory of the narrow escape problem. There was excellent agreement in both absolute values and across a range of small escape opening sizes. Additionally, I developed a straightforward method, a correction factor, to calculate the mean first passage time from incomplete experimental traces. By re-scaling the mean first passage time to the fraction of particles that escaped, I was able to overcome the lifetime limitations of fluorescent probes. Previously inaccessible measurements of the mean first passage time relying on fluorescent probes will be made possible through this approach. The in vitro experiments were complemented with various in silico experiments. The latter were based on random walk simulations in discs, mimicking the in vitro situation with its uncertainties. The lifetime of single particles was either set sufficiently long to allow all particles to escape, or was adjusted to meet the lifetime limitations observed in the in vitro experiments. A comparison of the mean first passage time from lifetime-unlimited particles to the corrected, lifetime-limited particles did support the use of the correction factor. In agreement with the narrow escape theory, it was experimentally found that the mean first passage time is independent of the start point of the particle within the domain. This is when the particle adheres to a minimum distance to the escape site. In general, the presented random walk simulations do accurately represent the in vitro experiments in this study. The required hardware for the establishment of an astigmatism-based 3D system was installed in the existing microscope. The first attempts to analyze the obtained 3D imaging data gave insight into the potential of the method to investigate molecule dynamics in living trypanosome cells. The full functionality will be realized with the ongoing improvement of image analysis outside of this thesis.

Topological phenomena known from solid state physics have been transferred to a variety of other classical and quantum systems. Due to the equivalence of the Hamiltonian matrix describing tight binding models and the grounded circuit Laplacian describing an electrical circuit we can investigate such phenomena in circuits. By implementing different Hermitian topological models general suggestions on designing those types of circuit are worked out with the aim of minimizing unwanted coupling effects and parasitic admittances in the circuit. Here the existence and the spatial profile of topological states as well as the band structure of the model can be determined.
Due to the complex nature of electric admittance the investigations can be directly expanded to systems with broken Hermiticity. The particular advantages of the experimental investigation of non-exclusively topological phenomena by means of electric circuits come to light in the realization of non-Hermitian and non-linear models. Here we find limitation of the Hermitian bulk-boundary correspondence principle, purely real eigenvalues in non-Hermitian PT-symmetrical systems and edge localization of all eigenstates in non-Hermitian and non-reciprocal systems, which in literature is termed the non-Hermitian skin effect.
When systems obeying non-linear equations are studied, the grounded circuit Laplacian based on the Fourier-transform cannot be applied anymore. By combination of the connectivity of a topological system together with non-linear van der Pol oscillators self-activated and self-sustained topological edge oscillations can be found. These robust high frequency sinusoidal edge oscillations differ significantly from low frequency relaxation oscillations, which can be found in the bulk of the system.

Das Ziel der vorliegenden Arbeit war die Entwicklung neuer, robuster Methoden der Spin-Lock-basierten MRT. Im Fokus stand hierbei vorerst die T1ρ-Quantifizierung des Myokards im Kleintiermodell. Neben der T1ρ-Bildgebung bietet Spin-Locking jedoch zusätzlich die Möglichkeit der Detektion ultra-schwacher, magnetischer Feldoszillationen. Die Projekte und Ergebnisse, die im Rahmen dieses Promotionsvorhabens umgesetzt und erzielt wurden, decken daher ein breites Spektrum der Spin-lock basierten Bildgebung ab und können grob in drei Bereiche unterteilt werden. Im ersten Schritt wurde die grundlegende Pulssequenz des Spin-Lock-Experimentes durch die Einführung des balancierten Spin-Locks optimiert. Der zweite Schritt war die Entwicklung einer kardialen MRT-Sequenz für die robuste Quantifizierung der myokardialen T1ρ-Relaxationszeit an einem präklinischen Hochfeld-MRT. Im letzten Schritt wurden Konzepte der robusten T1ρ-Bildgebung auf die Methodik der Felddetektion mittels Spin-Locking übertragen. Hierbei wurden erste, erfolgreiche Messungen magnetischer Oszillationen im nT-Bereich, welche lokal im untersuchten Gewebe auftreten, an einem klinischen MRT-System im menschlichen Gehirn realisiert.

This work introduced the reader to all relevant fields to tap into an ultrasound-based state of charge estimation and provides a blueprint for the procedure to achieve and test the fundamentals of such an approach. It spanned from an in-depth electrochemical characterization of the studied battery cells over establishing the measurement technique, digital processing of ultrasonic transmission signals, and characterization of the SoC dependent property changes of those signals to a proof of concept of an ultrasound-based state of charge estimation.
The State of the art & theoretical background chapter focused on the battery section on the mechanical property changes of lithium-ion batteries during operation. The components and the processes involved to manufacture a battery cell were described to establish the fundamentals for later interrogation. A comprehensive summary of methods for state estimation was given and an emphasis was laid on mechanical methods, including a critical review of the most recent research on ultrasound-based state estimation. Afterward, the fundamentals of ultrasonic non-destructive evaluation were introduced, starting with the sound propagation modes in isotropic boundary-free media, followed by the introduction of boundaries and non-isotropic structure to finally approach the class of fluid-saturated porous media, which batteries can be counted to. As the processing of the ultrasonic signals transmitted through lithium-ion battery cells with the aim of feature extraction was one of the main goals of this work, the fundamentals of digital signal processing and methods for the time of flight estimation were reviewed and compared in a separate section.
All available information on the interrogated battery cell and the instrumentation was collected in the Experimental methods & instrumentation chapter, including a detailed step-by-step manual of the process developed in this work to create and attach a sensor stack for ultrasonic interrogation based on low-cost off-the-shelf piezo elements.
The Results & discussion chapter opened with an in-depth electrochemical and post-mortem interrogation to reverse engineer the battery cell design and its internal structure. The combination of inductively coupled plasma-optical emission spectrometry and incremental capacity analysis applied to three-electrode lab cells, constructed from the studied battery cell’s materials, allowed to identify the SoC ranges in which phase transitions and staging occur and thereby directly links changes in the ultrasonic signal properties with the state of the active materials, which makes this work stand out among other studies on ultrasound-based state estimation. Additional dilatometer experiments were able to prove that the measured effect in ultrasonic time of flight cannot originate from the thickness increase of the battery cells alone, as this thickness increase is smaller and in opposite direction to the change in time of flight. Therefore, changes in elastic modulus and density have to be responsible for the observed effect.
The construction of the sensor stack from off-the-shelf piezo elements, its electromagnetic shielding, and attachment to both sides of the battery cells was treated in a subsequent section. Experiments verified the necessity of shielding and its negligible influence on the ultrasonic signals. A hypothesis describing the metal layer in the pouch foil to be the transport medium of an electrical coupling/distortion between sending and receiving sensor was formulated and tested. Impedance spectroscopy was shown to be a useful tool to characterize the resonant behavior of piezo elements and ensure the mechanical coupling of such to the surface of the battery cells. The excitation of the piezo elements by a raised cosine (RCn) waveform with varied center frequency in the range of 50 kHz to 250 kHz was studied in the frequency domain and the influence of the resonant behavior, as identified prior by impedance spectroscopy, on waveform and frequency content was evaluated to be uncritical. Therefore, the forced oscillation produced by this excitation was assumed to be mechanically coupled as ultrasonic waves into the battery cells.
The ultrasonic waves transmitted through the battery cell were recorded by piezo elements on the opposing side. A first inspection of the raw, unprocessed signals identified the transmission of two main wave packages and allowed the identification of two major trends: the time of flight of ultrasonic wave packages decreases with the center frequency of the RCn waveform, and with state of charge. These trends were to be assessed further in the subsequent sections. Therefore, methods for the extraction of features (properties) from the ultrasonic signals were established, compared, and tested in a dedicated section. Several simple and advanced thresholding methods were compared with envelope-based and cross-correlation methods to estimate the time of flight (ToF). It was demonstrated that the envelope-based method yields the most robust estimate for the first and second wave package. This finding is in accordance with the literature stating that an envelope-based method is best suited for dispersive, absorptive media [204], to which lithium-ion batteries are counted. Respective trends were already suggested by the heatmap plots of the raw signals vs. RCn frequency and SoC. To enable such a robust estimate, an FIR filter had to be designed to preprocess the transmitted signals and thereby attenuate frequency components that verifiably lead to a distorted shape of the envelope.
With a robust ToF estimation method selected, the characterization of the signal properties ToF and transmitted energy content (EC) was performed in-depth. A study of cycle-to-cycle variations unveiled that the signal properties are affected by a long rest period and the associated relaxation of the multi-particle system “battery cell” to equilibrium. In detail, during cycling, the signal properties don’t reach the same value at a given SoC in two subsequent cycles if the first of the two cycles follows a long rest period. In accordance with the literature, a break-in period, making up for more than ten cycles post-formation, was observed. During this break-in period, the mechanical properties of the system are said to change until a steady state is reached [25]. Experiments at different C-rate showed that ultrasonic signal properties can sense the non-equilibrium state of a battery cell, characterized by an increasing area between charge and discharge curve of the respective signal property vs. SoC plot. This non-equilibrium state relaxes in the rest period following the discharge after the cut-off voltage is reached. The relaxation in the rest period following the charge is much smaller and shows little C-rate dependency as the state is prepared by constant voltage charging at the end of charge voltage. For a purely statistical SoC estimation approach, as employed in this work, where only instantaneous measurements are taken into account and the historic course of the measurement is not utilized as a source of information, the presence of hysteresis and relaxation leads to a reduced estimation accuracy. Future research should address this issue or even utilize the relaxation to improve the estimation accuracy, by incorporating historic information, e.g., by using the derivative of a signal property as an additional feature. The signal properties were then tested for their correlation with SoC as a function of RCn frequency. This allowed identifying trends in the behavior of the signal properties as a function of RCn frequency and C-rate in a condensed fashion and thereby enabled to predict the frequency range, about 50 kHz to 125 kHz, in which the course of the signal properties is best suited for SoC estimation.
The final section provided a proof of concept of the ultrasound-based SoC estimation, by applying a support vector regression (SVR) to before thoroughly studied ultrasonic signal properties, as well as current and battery cell voltage. The included case study was split into different parts that assessed the ability of an SVR to estimate the SoC in a variety of scenarios. Seven battery cells, prepared with sensor stacks attached to both faces, were used to generate 14 datasets. First, a comparison of self-tests, where a portion of a dataset is used for training and another for testing, and cross-tests, which use the dataset of one cell for training and the dataset of another for testing, was performed. A root mean square error (RMSE) of 3.9% to 4.8% SoC and 3.6% to 10.0% SoC was achieved, respectively. In general, it was observed that the SVR is prone to overestimation at low SoCs and underestimation at high SoCs, which was attributed to the pronounced hysteresis and relaxation of the ultrasonic signal properties in this SoC ranges. The fact that higher accuracy is achieved, if the exact cell is known to the model, indicates that a variation between cells exists. This variation between cells can originate from differences in mechanical properties as a result of production variations or from differences in manual sensor placement, mechanical coupling, or resonant behavior of the ultrasonic sensors. To mitigate the effect of the cell-to-cell variations, a test was performed, where the datasets of six out of the seven cells were combined as training data, and the dataset of the seventh cell was used for testing. This reduced the spread of the RMSE from (3.6 - 10.0)% SoC to (5.9 – 8.5)% SoC, respectively, once again stating that a databased approach for state estimation becomes more reliable with a large data basis. Utilizing self-tests on seven datasets, the effect of additional features on the state estimation result was tested. The involvement of an additional feature did not necessarily improve the estimation accuracy, but it was shown that a combination of ultrasonic and electrical features is superior to the training with these features alone. To test the ability of the model to estimate the SoC in unknown cycling conditions, a test was performed where the C-rate of the test dataset was not included in the training data. The result suggests that for practical applications it might be sufficient to perform training with the boundary of the use cases in a controlled laboratory environment to handle the estimation in a broad spectrum of use cases.
In comparison with literature, this study stands out by utilizing and modifying off-the-shelf piezo elements to equip state-of-the-art lithium-ion battery cells with ultrasonic sensors, employing a range of center frequencies for the waveform, transmitted through the battery cell, instead of a fixed frequency and by allowing the SVR to choose the frequency that yields the best result. The characterization of the ultrasonic signal properties as a function of RCn frequency and SoC and the assignment of characteristic changes in the signal properties to electrochemical processes, such as phase transitions and staging, makes this work unique. By studying a range of use cases, it was demonstrated that an improved SoC estimation accuracy can be achieved with the aid of ultrasonic measurements – thanks to the correlation of the mechanical properties of the battery cells with the SoC.

This work deals with the acceleration of cardiovascular MRI for the assessment
of functional information in steady-state contrast and for viability assessment
during the inversion recovery of the magnetization. Two approaches
are introduced and discussed in detail. MOCO-MAP uses an exponential
model to recover dynamic image data, IR-CRISPI, with its low-rank plus
sparse reconstruction, is related to compressed sensing.
MOCO-MAP is a successor to model-based acceleration of parametermapping
(MAP) for the application in the myocardial region. To this end, it
was augmented with a motion correction (MOCO) step to allow exponential
fitting the signal of a still object in temporal direction. Iteratively, this
introduction of prior physical knowledge together with the enforcement of
consistency with the measured data can be used to reconstruct an image
series from distinctly shorter sampling time than the standard exam (< 3 s
opposed to about 10 s). Results show feasibility of the method as well as
detectability of delayed enhancement in the myocardium, but also significant
discrepancies when imaging cardiac function and artifacts caused already by
minor inaccuracy of the motion correction.
IR-CRISPI was developed from CRISPI, which is a real-time protocol
specifically designed for functional evaluation of image data in steady-state
contrast. With a reconstruction based on the separate calculation of low-rank
and sparse part, it employs a softer constraint than the strict exponential
model, which was possible due to sufficient temporal sampling density via
spiral acquisition. The low-rank plus sparse reconstruction is fit for the use on
dynamic and on inversion recovery data. Thus, motion correction is rendered
unnecessary with it.
IR-CRISPI was equipped with noise suppression via spatial wavelet filtering.
A study comprising 10 patients with cardiac disease show medical
applicability. A comparison with performed traditional reference exams offer
insight into diagnostic benefits. Especially regarding patients with difficulty
to hold their breath, the real-time manner of the IR-CRISPI acquisition provides
a valuable alternative and an increase in robustness.
In conclusion, especially with IR-CRISPI in free breathing, a major acceleration
of the cardiovascular MR exam could be realized. In an acquisition
of less than 100 s, it not only includes the information of two traditional
protocols (cine and LGE), which take up more than 9.6 min, but also allows
adjustment of TI in retrospect and yields lower artifact level with similar
image quality.

X-ray dark-field imaging allows to resolve the conflict between the demand for centimeter scaled fields of view and the spatial resolution required for the characterization of fibrous materials structured on the micrometer scale. It draws on the ability of X-ray Talbot interferometers to provide full field images of a sample's ultra small angle scattering properties, bridging a gap of multiple orders of magnitude between the imaging resolution and the contrasted structure scale. The correspondence between shape anisotropy and oriented scattering thereby allows to infer orientations within a sample's microstructure below the imaging resolution. First demonstrations have shown the general feasibility of doing so in a tomographic fashion, based on various heuristic signal models and reconstruction approaches. Here, both a verified model of the signal anisotropy and a reconstruction technique practicable for general imaging geometries and large tensor valued volumes is developed based on in-depth reviews of dark-field imaging and tomographic reconstruction techniques.
To this end, a wide interdisciplinary field of imaging and reconstruction methodologies is revisited. To begin with, a novel introduction to the mathematical description of perspective projections provides essential insights into the relations between the tangible real space properties of cone beam imaging geometries and their technically relevant description in terms of homogeneous coordinates and projection matrices. Based on these fundamentals, a novel auto-calibration approach is developed, facilitating the practical determination of perspective imaging geometries with minimal experimental constraints. A corresponding generalized formulation of the widely employed Feldkamp algorithm is given, allowing fast and flexible volume reconstructions from arbitrary tomographic imaging geometries. Iterative reconstruction techniques are likewise introduced for general projection geometries, with a particular focus on the efficient evaluation of the forward problem associated with tomographic imaging. A highly performant 3D generalization of Joseph's classic linearly interpolating ray casting algorithm is developed to this end and compared to typical alternatives. With regard to the anisotropic imaging modality required for tensor tomography, X-ray dark-field contrast is extensively reviewed. Previous literature is brought into a joint context and nomenclature and supplemented by original work completing a consistent picture of the theory of dark-field origination. Key results are explicitly validated by experimental data with a special focus on tomography as well as the properties of anisotropic fibrous scatterers. In order to address the pronounced susceptibility of interferometric images to subtle mechanical imprecisions, an efficient optimization based evaluation strategy for the raw data provided by Talbot interferometers is developed. Finally, the fitness of linear tensor models with respect to the derived anisotropy properties of dark-field contrast is evaluated, and an iterative scheme for the reconstruction of tensor valued volumes from projection images is proposed. The derived methods are efficiently implemented and applied to fiber reinforced plastic samples, imaged at the ID19 imaging beamline of the European Synchrotron Radiation Facility. The results represent unprecedented demonstrations of X-ray dark-field tensor tomography at a field of view of 3-4cm, revealing local fiber orientations of both complex shaped and low-contrast samples at a spatial resolution of 0.1mm in 3D. The results are confirmed by an independent micro CT based fiber analysis.

In this view point we do not change cosmology after the hot fireball starts (hence agrees well with observation), but the changed start suggested and resulting later implications lead to an even better fit with current observations (voids, supercluster and galaxy formation; matter and no antimatter) than the standard model with big bang and inflation: In an eternal ocean of qubits, a cluster of qubits crystallizes to defined bits. The universe does not jump into existence (“big bang”) but rather you have an eternal ocean of qubits in free super-position of all their quantum states (of any dimension, force field and particle type) as permanent basis. The undefined, boiling vacuum is the real “outside”, once you leave our everyday universe. A set of n Qubits in the ocean are “liquid”, in very undefined state, they have all their m possibilities for quantum states in free superposition. However, under certain conditions the qubits interact, become defined, and freeze out, crystals form and give rise to a defined, real world with all possible time series and world lines. GR holds only within the crystal. In our universe all n**m quantum possibilities are nicely separated and crystallized out to defined bit states: A toy example with 6 qubits each having 2 states illustrates, this is completely sufficient to encode space using 3 bits for x,y and z, 1 bit for particle type and 2 bits for its state. Just by crystallization, space, particles and their properties emerge from the ocean of qubits, and following the arrow of entropy, time emerges, following an arrow of time and expansion from one corner of the toy universe to everywhere else. This perspective provides time as emergent feature considering entropy: crystallization of each world line leads to defined world lines over their whole existence, while entropy ensures direction of time and higher representation of high entropy states considering the whole crystal and all slices of world lines. The crystal perspective is also economic compared to the Everett-type multiverse, each qubit has its m quantum states and n qubits interacting forming a crystal and hence turning into defined bit states has only n**m states and not more states. There is no Everett-type world splitting with every decision but rather individual world trajectories reside in individual world layers of the crystal. Finally, bit-separated crystals come and go in the qubit ocean, selecting for the ability to lay seeds for new crystals. This self-organizing reproduction selects over generations also for life-friendliness. Mathematical treatment introduces quantum action theory as a framework for a general lattice field theory extending quantum chromo dynamics where scalar fields for color interaction and gravity have to be derived from the permeating qubit-interaction field. Vacuum energy should get appropriately low by the binding properties of the qubit crystal. Connections to loop quantum gravity, string theory and emergent gravity are discussed. Standard physics (quantum computing; crystallization, solid state physics) allow validation tests of this perspective and will extend current results.

We employ the AdS/CFT correspondence and hydrodynamics to analyze the transport properties of \(2+1\) dimensional electron fluids. In this way, we use theoretical methods from both condensed matter and high-energy physics to derive tangible predictions that are directly verifiable in experiment.
The first research topic we consider is strongly-coupled electron fluids. Motivated by early results by Gurzhi on the transport properties of weakly coupled fluids, we consider whether similar properties are manifest in strongly coupled fluids. More specifically, we focus on the hydrodynamic tail of the Gurzhi effect: A decrease in fluid resistance with increasing temperature due to the formation of a Poiseuille flow of electrons in the sample. We show that the hydrodynamic tail of the Gurzhi effect is also realized in strongly coupled and fully relativistic fluids, but with modified quantitative features. Namely, strongly-coupled fluids always exhibit a smaller resistance than weakly coupled ones and are, thus, far more efficient conductors. We also suggest that the coupling dependence of the resistance can be used to measure the coupling strength of the fluid. In view of these measurements, we provide analytical results for the resistance as a function of the shear viscosity over entropy density \(\eta/s\) of the fluid. \(\eta/s\) is itself a known function of the coupling strength in the weak and infinite coupling limits.
In further analysis for strongly-coupled fluids, we propose a novel strongly coupled Dirac material based on a kagome lattice, Scandium-substituted Herbertsmithite (ScHb). The large coupling strength of this material, as well as its Dirac nature, provides us with theoretical and experimental access to non-perturbative relativistic and quantum critical physics. A highly suitable method for analyzing such a material's transport properties is the AdS/CFT correspondence. Concretely, using AdS/CFT we derive an estimate for ScHb's \(\eta/s\) and show that it takes a value much smaller than that observed in weakly coupled materials. In turn, the smallness of \(\eta/s\) implies that ScHb's Reynolds number, \(Re\), is large. In fact, \(Re\) is large enough for turbulence, the most prevalent feature of fluids in nature, to make its appearance for the first time in electronic fluids.
Switching gears, we proceed to the second research topic considered in this thesis: Weakly coupled parity-breaking electron fluids. More precisely, we analyze the quantitative and qualitative changes to the classical Hall effect, for electrons propagating hydrodynamically in a lead. Apart from the Lorentz force, a parity-breaking fluid's motion is also impacted by the Hall-viscous force; the shear-stress force induced by the Hall-viscosity. We show that the interplay of these two forces leads to a hydrodynamic Hall voltage with non-linear dependence on the magnetic field. More importantly, the Lorentz and Hall-viscous forces become equal at a non-vanishing magnetic field, leading to a trivial hydrodynamic Hall voltage. Moreover, for small magnetic fields we provide analytic results for the dependence of the hydrodynamic Hall voltage on all experimentally-tuned parameters of our simulations, such as temperature and density. These dependences, along with the zero of the hydrodynamic Hall voltage, are distinct features of hydrodynamic transport and can be used to verify our predictions in experiments.
Last but not least, we consider how a distinctly electronic property, spin, can be included into the hydrodynamic framework. In particular, we construct an effective action for non-dissipative spin hydrodynamics up to first order in a suitably defined derivative expansion. We also show that interesting spin-transport effects appear at second order in the derivative expansion. Namely, we show that the fluid's rotation polarizes its spin. This is the hydrodynamic manifestation of the Barnett effect and provides us with an example of hydrodynamic spintronics.
To conclude this thesis, we discuss several possible extensions of our research, as well as proposals for research in related directions.