The thesis deals with so-called evolutionary equations, a class of abstract linear operator equations, which cover a huge class of partial differential equation with and without memory. We provide a unified Hilbert space framework for the well-posedness of such equations. Moreover, we inspect the exponential stability of those problems and construct spaces of admissible inital values and pre-histories, on which a strongly continuous semigroup could be associated with the given problem. The theoretical results are illustrated by several examples.

Cell migration, the active translocation of cells is involved in various biological processes, e.g. development of tissues and organs, tumor invasion and wound healing. Cell migration behavior can be divided into two distinct classes: single cell migration and collective cell migration. Single cell migration describes the migration of cells without interaction with other cells in their environment. Collective cell migration is the joint, active movement of multiple cells, e.g. in the form of strands, cohorts or sheets which emerge as the result of individual cell-cell interactions. Collective cell migration can be observed during branching morphogenesis, vascular sprouting and embryogenesis. Experimental studies of single cell migration have been extensive. Collective cell migration is less well investigated due to more difficult experimental conditions than for single cell migration. Especially, experimentally identifying the impact of individual differences in cell phenotypes on individual cell migration behavior inside cell populations is challenging because the tracking of individual cell trajectories is required. In this thesis, a novel mathematical modeling approach, individual-based lattice-gas cellular automata (IB-LGCA), that allows to investigate the migratory behavior of individual cells inside migrating cell populations by enabling the tracking of individual cells is introduced. Additionally, stochastic differential equation (SDE) approximations of individual cell trajectories for IB-LGCA models are constructed. Such SDE approximations allow the analytical description of the trajectories of individual cells during single cell migration. For a complete analytical description of the trajectories of individual cell during collective cell migration the aforementioned SDE approximations alone are not sufficient. Analytical approximations of the time development of selected observables for the cell population have to be added. What observables have to be considered depends on the specific cell migration mechanisms that is to be modeled. Here, partial integro-differential equations (PIDE) that approximate the time evolution of the expected cell density distribution in IB-LGCA are constructed and coupled to SDE approximations of individual cell trajectories. Such coupled PIDE and SDE approximations provide an analytical description of the trajectories of individual cells in IB-LGCA with density-dependent cell-cell interactions. Finally, an IB-LGCA model and corresponding analytical approximations were applied to investigate the impact of changes in cell-cell and cell-ECM forces on the migration behavior of an individual, labeled cell inside a population of epithelial cells. Specifically, individual cell migration during the epithelial-mesenchymal transition (EMT) was considered. EMT is a change from epithelial to mesenchymal cell phenotype which is characterized by cells breaking adhesive bonds with surrounding epithelial cells and initiating individual migration along the extracellular matrix (ECM). During the EMT, a transition from collective to single cell migration occurs. EMT plays an important role during cancer progression, where it is believed to be linked to metastasis development. In the IB-LGCA model epithelial cells are characterized by balanced cell-cell and cell-ECM forces. The IB-LGCA model predicts that the balance between cell-cell and cell-ECM forces can be disturbed to some degree without being accompanied by a change in individual cell migration behavior. Only after the cell force balance has been strongly interrupted mesenchymal migration behavior is possible. The force threshold which separates epithelial and mesenchymal migration behavior in the IB-LGCA has been identified from the corresponding analytical approximation. The IB-LGCA model allows to obtain quantitative predictions about the role of cell forces during EMT which in the context of mathematical modeling of EMT is a novel approach.

Cell migration, the active translocation of cells is involved in various biological processes, e.g. development of tissues and organs, tumor invasion and wound healing. Cell migration behavior can be divided into two distinct classes: single cell migration and collective cell migration. Single cell migration describes the migration of cells without interaction with other cells in their environment. Collective cell migration is the joint, active movement of multiple cells, e.g. in the form of strands, cohorts or sheets which emerge as the result of individual cell-cell interactions. Collective cell migration can be observed during branching morphogenesis, vascular sprouting and embryogenesis. Experimental studies of single cell migration have been extensive. Collective cell migration is less well investigated due to more difficult experimental conditions than for single cell migration. Especially, experimentally identifying the impact of individual differences in cell phenotypes on individual cell migration behavior inside cell populations is challenging because the tracking of individual cell trajectories is required. In this thesis, a novel mathematical modeling approach, individual-based lattice-gas cellular automata (IB-LGCA), that allows to investigate the migratory behavior of individual cells inside migrating cell populations by enabling the tracking of individual cells is introduced. Additionally, stochastic differential equation (SDE) approximations of individual cell trajectories for IB-LGCA models are constructed. Such SDE approximations allow the analytical description of the trajectories of individual cells during single cell migration. For a complete analytical description of the trajectories of individual cell during collective cell migration the aforementioned SDE approximations alone are not sufficient. Analytical approximations of the time development of selected observables for the cell population have to be added. What observables have to be considered depends on the specific cell migration mechanisms that is to be modeled. Here, partial integro-differential equations (PIDE) that approximate the time evolution of the expected cell density distribution in IB-LGCA are constructed and coupled to SDE approximations of individual cell trajectories. Such coupled PIDE and SDE approximations provide an analytical description of the trajectories of individual cells in IB-LGCA with density-dependent cell-cell interactions. Finally, an IB-LGCA model and corresponding analytical approximations were applied to investigate the impact of changes in cell-cell and cell-ECM forces on the migration behavior of an individual, labeled cell inside a population of epithelial cells. Specifically, individual cell migration during the epithelial-mesenchymal transition (EMT) was considered. EMT is a change from epithelial to mesenchymal cell phenotype which is characterized by cells breaking adhesive bonds with surrounding epithelial cells and initiating individual migration along the extracellular matrix (ECM). During the EMT, a transition from collective to single cell migration occurs. EMT plays an important role during cancer progression, where it is believed to be linked to metastasis development. In the IB-LGCA model epithelial cells are characterized by balanced cell-cell and cell-ECM forces. The IB-LGCA model predicts that the balance between cell-cell and cell-ECM forces can be disturbed to some degree without being accompanied by a change in individual cell migration behavior. Only after the cell force balance has been strongly interrupted mesenchymal migration behavior is possible. The force threshold which separates epithelial and mesenchymal migration behavior in the IB-LGCA has been identified from the corresponding analytical approximation. The IB-LGCA model allows to obtain quantitative predictions about the role of cell forces during EMT which in the context of mathematical modeling of EMT is a novel approach.

The thesis deals with so-called evolutionary equations, a class of abstract linear operator equations, which cover a huge class of partial differential equation with and without memory. We provide a unified Hilbert space framework for the well-posedness of such equations. Moreover, we inspect the exponential stability of those problems and construct spaces of admissible inital values and pre-histories, on which a strongly continuous semigroup could be associated with the given problem. The theoretical results are illustrated by several examples.

Die Auswertung von Mehrschleifen-Feynman-Integralen ist eine der größten Herausforderungen bei der Berechnung präziser theoretischer Vorhersagen für die am LHC gemessenen Wirkungsquerschnitte. In den vergangenen Jahren hat sich die Nutzung von Differentialgleichungen bei der Berechnung von Feynman-Integralen als sehr erfolgreich erwiesen. Es wurde dabei beobachtet, dass die von den Feynman-Integralen erfüllte Differentialgleichung oftmals in eine sogenannte kanonische Form transformiert werden kann, welche die Integration der Differentialgleichung mittels iterierter Integrale wesentlich vereinfacht. Das zentrale Ergebnis der vorliegenden Arbeit ist ein Algorithmus zur Berechnung rationaler Transformationen von Differentialgleichungen von Feynman-Integralen in eine kanonische Form. Neben der Existenz einer solchen rationalen Transformation stellt der Algorithmus keinerlei weitere Bedingungen an die Differentialgleichung. Insbesondere ist der Algorithmus auf Mehrskalenprobleme anwendbar und erlaubt eine rationale Abhängigkeit der Differentialgleichung vom dimensionalen Regulator. Bei der Anwendung des Algorithmus wird zunächst das Transformationsgesetz im dimensionalen Regulator entwickelt, um Differentialgleichungen für die Koeffizienten in der Entwicklung der Transformation herzuleiten. Diese Differentialgleichungen werden dann mit einem rationalen Ansatz für die gesuchte Transformation gelöst. Es wird zudem eine Implementation des Algorithmus in dem Mathematica Paket CANONICA vorgestellt, welches das erste veröffentlichte Programm dieser Art ist, das auf Mehrskalenprobleme anwendbar ist. CANONICAs Potential für moderne Mehrschleifenrechnungen wird anhand mehrerer nicht trivialer Mehrschleifen-Integraltopologien demonstriert. Die gezeigten Topologien hängen von bis zu drei Variablen ab und umfassen auch vormals ungelöste Topologien, die zu Korrekturen höherer Ordnung zum Wirkungsquerschnitt der Produktion einzelner Top-Quarks am LHC beitragen. / The evaluation of multi-loop Feynman integrals is one of the main challenges in the computation of precise theoretical predictions for the cross sections measured at the LHC. In recent years, the method of differential equations has proven to be a powerful tool for the computation of Feynman integrals. It has been observed that the differential equation of Feynman integrals can in many instances be transformed into a so-called canonical form, which significantly simplifies its integration in terms of iterated integrals. The main result of this thesis is an algorithm to compute rational transformations of differential equations of Feynman integrals into a canonical form. Apart from requiring the existence of such a rational transformation, the algorithm needs no further assumptions about the differential equation. In particular, it is applicable to problems depending on multiple kinematic variables and also allows for a rational dependence on the dimensional regulator. First, the transformation law is expanded in the dimensional regulator to derive differential equations for the coefficients of the transformation. Using an ansatz in terms of rational functions, these differential equations are then solved to determine the transformation. This thesis also presents an implementation of the algorithm in the Mathematica package CANONICA, which is the first publicly available program to compute transformations to a canonical form for differential equations depending on multiple variables. The main functionality and its usage are illustrated with some simple examples. Furthermore, the package is applied to state-of-the-art integral topologies appearing in recent multi-loop calculations. These topologies depend on up to three variables and include previously unknown topologies contributing to higher-order corrections to the cross section of single top-quark production at the LHC.

In der vorliegenden Arbeit wird die Methode der Anwendung der hyperkomplexen Funktionentheorie zur Behandlung partieller Differentialgleichungen über beschränkten Gebieten unter Benutzung einer orthogonalen Zerlegung des Raumes L_2(U) verallgemeinert. Zum einen kann diese Zerlegung als direkte Zerlegung über dem Raum L_p(G),p>1, verallgemeinert werden, was die Untersuchung partieller Differentialgleichungen über allgemeinen Sobolev-Räumen W_p^k(G),p>1,k natürliche Zahl, ermöglicht. Dies wird am Beispiel des Stokes-Problems demonstriert. Zum anderen wird ein modifizierter Cauchy-Kern über unbeschränkten Gebieten eingeführt, deren Komplement eine nichtleere offene Menge enthält. Grundlegende Resultate der Cliffordanalysis über beschränkten Gebieten werden auf diese Situation verallgemeinert und eine orthogonale Zerlegung des Raumes L_2(G) bewiesen. Diese Resultate werden im weiteren dazu benutzt, das stationäre Stokes- bzw. Navier-Stokes-Problem in dem allgemeinen Fall eines unbeschränkten Gebietes zu untersuchen. Im weiteren wird gezeigt, dass sich die entwickelten Methoden auch auf partielle Differentialgleichungen höherer Ordnung anwenden lassen. Dies wird am Beispiel der biharmonischen Gleichung mit Randbedingungen, die Komponenten in Normalenrichtung und tangentieller Richtung besitzen, demonstriert. Am Ende beschäftigen wir uns mit der Verallgemeinerung der komplexen Methoden von Vekua. Dazu werden hyperkomplexe Verallgemeinerungen des komplexen Pi-Operators untersucht und auf die Lösung von hyperkomplexen Beltramigleichungen angewandt. / A modified Cauchy kernel is introduced over unbounded domains whose complement contain non-empty open sets. Basic results on Clifford analysis over bounded domains are now carried over to this more general context. In the end boundary value problems, e.g. for the Stokes-system or the Navier-Stokes-system, will be studied in the case of an unbounded domain without using weighted Sobolev spaces. In the latter part of this paper we deal with hypercomplex generalizations of the complex Pi-operator which turn out to have most of the useful properties of their complex origin. Afterwards the application of this operator to the solution of hypercomplex Beltrami equations will be studied.

We study a class of differential inclusions involving maximal monotone relations, which cover a huge class of problems in mathematical physics. For this purpose we introduce the time derivative as a continuously invertible operator in a suitable Hilbert space. It turns out that this realization is a strictly monotone operator and thus, the question on existence and uniqueness can be answered by well-known results in the theory of maximal monotone relations. Furthermore, we show that the resulting solution operator is Lipschitz-continuous and causal, which is a natural property of evolutionary processes. Finally, the results are applied to a system of partial differential equations and inclusions, which describes the diffusion of a compressible fluid through a saturated, porous, plastically deforming media, where certain hysteresis phenomena are modeled by maximal montone relations.

This thesis studies the role of higher moments, that is moments behind mean and variance, in continuous-time, or diffusion, processes, which are commonly used to model so-called high-frequency data. Thereby, the first part is devoted to the derivation of closed-form expression of general (un)conditional (co)moment formulas of the famous CIR process’s solution. A byproduct of this derivation will be a novel way of proving that the process’s transition density is a noncentral chi-square distribution and that its steady-state law is a Gamma distribution. In the second part, we use these moment formulas to derive a near-exact simulation algorithm to the Heston model, in the sense that our algorithm generates pseudo-random numbers that have the same first four moments as the theoretical diffusion process. We will conduct several in-depth Monte Carlo studies to determine which existing simulation algorithm performs best with respect to these higher moments under certain circumstances. We will conduct the same study for the CIR process, which serves as a diffusion for the latent spot variance in the Heston model. The third part discusses several estimation approaches to the Heston model based on high-frequency data, such as MM, GMM, and (pseudo/quasi) ML. For the GMM approach, we will use the moments derived in the first part as moment conditions. We apply the best methodology to actual high-frequency price series of cryptocurrencies and FIAT stocks to provide benchmark parameter estimates. / Die vorliegende Arbeit untersucht die Rolle von höheren Momenten, also Momente, welche über den Erwartungswert und die Varianz hinausgehen, im Kontext von zeitstetigen Zeitreihenmodellen. Solche Diffusionsprozesse werden häufig genutzt, um sogenannte Hochfrequenzdaten zu beschreiben. Teil 1 der Arbeit beschäftigt sich mit der Herleitung von allgemeinen und in geschlossener Form verfügbaren Ausdrücken der (un)bedingten (Ko-)Momente der Lösung zum CIR-Prozess. Mittels dieser Formeln wird auf einem alternativen Weg bewiesen, dass die Übergangsdichte dieses Prozesses mithilfe einer nichtzentralen Chi-Quadrat-Verteilung beschrieben werden kann, und dass seine stationäre Verteilung einer Gamma-Verteilung entspricht. Im zweiten Teil werden die zuvor entwickelten Ausdrücke genutzt, um einen nahezu exakten Simulationsalgorithmus für das Hestonmodell herzuleiten. Dieser Algorithmus ist in dem Sinne nahezu exakt, dass er Pseudo-Zufallszahlen generiert, welche die gleichen ersten vier Momente besitzen, wie der dem Hestonmodell zugrundeliegende Diffusionsprozess. Ferner werden Monte-Carlo-Studien durchgeführt, die ergründen sollen, welche bereits existierenden Simulationsalgorithmen in Hinblick auf die ersten vier Momente die besten Ergebnisse liefern. Die gleiche Studie wird außerdem für die Simulation des CIR-Prozesses durchgeführt, welcher im Hestonmodell als Diffusion für die latente, instantane Varianz dient. Im dritten Teil werden mehrere Schätzverfahren für das Hestonmodell, wie das MM-, GMM und pseudo- beziehungsweise quasi-ML-Verfahren, diskutiert. Diese werden unter Benutzung von Hochfrequenzdaten studiert. Für das GMM-Verfahren dienen die hergeleiteten Momente aus dem ersten Teil der Arbeit als Momentebedingungen. Um ferner Schätzwerte für das Hestonmodell zu finden, werden die besten Verfahren auf Hochfrequenzmarktdaten von Kryptowährungen, sowie hochliquider Aktientitel angewandt. Diese sollen zukünftig als Orientierungswerte dienen.

In a Hilbert space setting homogenization of evolutionary equations is discussed. In order to do so, a suitable topology on material laws is introduced and several properties of that topology are shown. With those properties homogenization theorems of a large class of linear evolutionary problems of classical mathematical physics can be obtained. The results are exemplified by the equations of piezo-electro-magnetism.

This thesis deals with the optimal control of PDEs. After a brief introduction in the theory of elliptic and parabolic PDEs, we introduce a software that solves systems of PDEs by the finite elements method. In the second chapter we derive optimality conditions in terms of function spaces, i.e. a systems of PDEs coupled by some pointwise relations. Now we present algorithms to solve the optimality systems numerically and present some numerical test cases. A further chapter deals with the so called lack of adjointness, an issue of gradient methods applied on parabolic optimal control problems. However, since optimal control problems lead to large numerical schemes, model reduction becomes popular. We analyze the proper orthogonal decomposition method and apply it to our model problems. Finally, we apply all considered techniques to a real world problem.