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This thesis is devoted to optical properties of Aharonov-Bohm quantum rings in external electromagnetic fields. It contains two problems. The first problem deals with a single-electron Aharonov-Bohm quantum ring pierced by a magnetic flux and subjected to an in-plane (lateral) electric field. We predict magneto-oscillations of the ring electric dipole moment. These oscillations are accompanied by periodic changes in the selection rules for inter-level optical transitions in the ring allowing control of polarization properties of the associated terahertz radiation. The second problem treats a single-mode microcavity with an embedded Aharonov-Bohm quantum ring, which is pierced by a magnetic flux and subjected to a lateral electric field. We show that external electric and magnetic fields provide additional means of control of the emission spectrum of the system. In particular, when the magnetic flux through the quantum ring is equal to a half-integer number of the magnetic flux quantum, a small change in the lateral electric field allows tuning of the energy levels of the quantum ring into resonance with the microcavity mode, providing an efficient way to control the quantum ring-microcavity coupling strength. Emission spectra of the system are calculated for several combinations of the applied magnetic and electric fields.

Mathematical models are important tools in systems biology, since the regulatory networks in biological cells are too complicated to understand by biological experiments alone. Analytical solutions can be derived only for the simplest models and numerical simulations are necessary in most cases to evaluate the models and their properties and to compare them with measured data. This thesis focuses on the mesoscopic simulation level, which captures both, space dependent behavior by diffusion and the inherent stochasticity of cellular systems. Space is partitioned into compartments by a mesh and the number of molecules of each species in each compartment gives the state of the system. We first examine how to compute the jump coefficients for a discrete stochastic jump process on unstructured meshes from a first exit time approach guaranteeing the correct speed of diffusion. Furthermore, we analyze different methods leading to non-negative coefficients by backward analysis and derive a new method, minimizing both the error in the diffusion coefficient and in the particle distribution. The second part of this thesis investigates macromolecular crowding effects. A high percentage of the cytosol and membranes of cells are occupied by molecules. This impedes the diffusive motion and also affects the reaction rates. Most algorithms for cell simulations are either derived for a dilute medium or become computationally very expensive when applied to a crowded environment. Therefore, we develop a multiscale approach, which takes the microscopic positions of the molecules into account, while still allowing for efficient stochastic simulations on the mesoscopic level. Finally, we compare on- and off-lattice models on the microscopic level when applied to a crowded environment.

We directly model the quantum many particle dynamics during the transition of a gas of N indistinguishable bosons into a Bose-Einstein condensate. To this end, we develop a quantitative quantum master equation theory, which takes into account two body interaction processes, and in particular describes the particle number fluctuations characteristic for the Bose-Einstein phase transition. Within the Markovian dynamics assumption, we analytically prove and numerically verify the Boltzmann ergodicity conjecture for a dilute, weakly interacting Bose-Einstein condensate. The new physical bottom line of our theory is the direct microscopic monitoring of the Bose-Einstein distribution during condensate formation in real-time, after a sudden quench of the non-condensate atomic density above the critical density for Bose-Einstein condensation.

The finite state projection algorithm provides modelers a new way of directly solving the chemical master equation. The algorithm utilizes the matrix exponential function, and so the algorithm’s performance suffers when it is applied to large problems. Other work has been done to reduce the size of the exponentiation through mathematical simplifications, but efficiently exponentiating a large matrix has not been explored. This work explores implementing the finite state projection algorithm on several different high-performance computing platforms as a means of efficiently calculating the matrix exponential function for large systems. This work finds that general purpose graphics processing can accelerate the finite state projection algorithm by several orders of magnitude. Specific biological models and modeling techniques are discussed as a demonstration of the algorithm implemented on a general purpose graphics processor. The results of this work show that general purpose graphics processing will be a key factor in modeling more complex biological systems.

Neste trabalho estudamos as transições de fases cinéticas e o comportamento crítico da produção de entropia em modelos de spins com interação entre primeiros vizinhos e sujeitos a duas dinâmicas de Glauber, as quais simulam dois banhos térmicos a diferentes temperaturas. Para tanto, é admitido que o sistema corresponde a um processo markoviano contínuo no tempo o qual obedece a uma equação mestra. Dessa forma, o sistema atinge naturalmente estados estacionários, que podem ser de equilíbrio ou de não-equilíbrio. O primeiro corresponde exatamente ao modelo de Ising, que ocorre quando o sistema se encontra em contato com apenas um dos reservatórios. Dessa forma, há uma transição de fase na temperatura de Curie e o balanceamento detalhado é seguramente satisfeito. No segundo caso, os dois banhos térmicos são responsáveis por uma corrente de probabilidade que só existe visto que a reversibilidade microscópica não é mais verificada. Como conseqüência, nesse regime de não-equilíbrio o sistema apresenta uma produção de entropia não nula. Para avaliarmos os diagramas de fase e a produção de entropia utilizamos as aproximações de pares e as simulações de Monte Carlo. Além disso, admitimos que a teoria de escala finita pode ser aplicada no modelo. Esses métodos foram capazes de preverem as transições de fases sofridas pelo sistema. Os expoentes e os pontos críticos foram estimados através dos resultados numéricos. Para a magnetização e a susceptibilidade obtemos = 0,124(1) e = 1,76(1), o que nos permite concluir que o nosso modelo pertence à mesma classe de Ising. Esse resultado refere-se ao princípio da universalidade do ponto crítico, que é verificado devido o nosso modelo apresentar a mesma simetria de inversão que a do modelo de Ising. Além disso, as aproximações de pares também mostraram uma singularidade na derivada da produção de entropia no ponto crítico. E as simulações de Monte Carlo nos permitem sugerir que tal comportamento é uma divergência logarítmica cujo expoente crítico associado vale 1. / We study kinetic phase transitions and the critical behavior of the entropy production in spin models with nearest neighbor interactions subject to two Glauber dynamics, which simulate two thermal baths at different temperatures. In this way, it is assumed that the system corresponds to a continuous time Markov process which obeys the master equation. Thus, the system naturally reaches steady states, which can be equilibrium or nonequilibrium. The former corresponds exactly to the Ising model, which occurs since the system is in contact with only one of the reservoirs. In this case, there is a phase transition at the Curie temperature and the detailed balance surely holds. In the second case, the two thermal baths create a non trivial probability current only when microscopic reversibility is not verified. As a consequence, there is a positive entropy production in a non-equilibrium steady state. Pair approximations and Monte Carlo simulations are employed to evaluate the phase diagrams and the entropy production. Furthermore, we assume that the finite-size scaling theory can be applied to the model. These methods were able to predict the phase transitions undergone by the system. The exponents and the critical points were estimated by the numerical results. Our best estimates of critical exponents to the magnetization and susceptibility are = 0,124 (1) and = 1,76 (1), which allows us to conclude that our model belongs to the same class of Ising. This result refers to the principle of universality of the critical point, which is checked because our model has the same inversion symmetry of the Ising model. Moreover, the pair approximation also showed a singularity in the derivative of the entropy production at the critical point. And Monte Carlo simulations allow us to suggest that the divergence at the critical point is of the logarithmic type whose critical exponent is 1

Ce travail se décompose en deux grandes parties, "Estimations répétées dans le cadre de la modélisation bayésienne" et "Modélisation de la transmission de maladies infectieuses dans une population. Estimation des paramètres.". Les techniques développées dans la première partie sont utilisées en fin de la seconde partie. La première partie est consacrée à des optimisations d'algorithmes stochastiques très souvent utilisés, notamment dans le contexte des modélisations Bayésiennes. Cette optimisation est particulièrement faite lors de l'étude empirique d'estimateurs des paramètres d'un modèle où les qualités des estimateurs sont évaluées sur un grand nombre de jeux de données simulées. Quand les lois a posteriori ne sont pas explicites, le recours à des algorithmes stochastiques itératifs (de la famille des algorithmes dits de Monte Carlo par Chaîne de Makov) pour approcher les lois a posteriori est alors très couteux en temps car doit être fait pour chaque jeu de données. Dans ce contexte, ce travail consiste en l'étude de solutions évitant un trop grand nombre d'appels à ces algorithmes mais permettant bien-sûr d'obtenir malgré tout des résultats précis. La principale technique étudiée dans cette partie est celle de l'échantillonnage préférentiel. La seconde partie est consacrée aux études de modèles épidémiques, en particulier le modèle compartimental dit SIS (Susceptible-Infecté-Susceptible) dans sa version stochastique. L'approche stochastique permet de prendre en compte l'hétérogénéité de l'évolution de la maladie dans la population. les approches par des processus Markoviens sont étudiés où la forme des probabilités de passage entre les états est non linéaire. La solution de l'équation différentielle en probabilité n'est alors en général pas explicite. Les principales techniques utilisées dans cette partie sont celles dites de développement de l'équation maîtresse ("master equation") appliquées au modèle SIS avec une taille de population constante. Les propriétés des estimateurs des paramètres sont étudiées dans le cadre fréquentiste et bayésien. Concernant l'approche Bayésienne, les solutions d'optimisation algorithmique de la première partie sont appliquées. / This work consists in two parts, "Repeated estimates in bayesian modelling " and " Modelling of the transmission of infectious diseases in a population. Estimation of the parameters". Techniques developed in the first part are used at the end of the second part.The first part deals with optimizations of very often used stochastic algorithms, in particular in the context of Bayesian modelling. This optimization is particularly made when empirical study of estimates based on numerous simulated data sets is done. When posterior distribution of parameters are not explicit, its approximation is obtained via iterative stochastic algorithms (of the family of Markov Chain Monte Carlo) which is computationally expensive because has to be done on each data set. In this context, solutions are proposed avoiding an excess large number of MCMC calls but nevertheless giving accurate results. The Importance Sampling method is used in combination with MCMC in Bayesian simulation study. The second part deals with epidemic models, in particular the compartimental model SIS (Susceptible-Infectious-Susceptible) in its stochastic version. The stochastic approach allows to take into account the heterogeneousness of disease evolution in the population. Markov Process is particularly studied where transition probability between states is not linear, the solution of the differential equation in probability being then generally not explicit. The main techniques used in this part are the ones based on Master equation applied on SIS model with a constant population size. Empirical properties of parameters estimates are studied in frequentist and Bayesian context with algorithmic optimization presented in the first part.

Neste trabalho estudamos as transições de fases cinéticas e o comportamento crítico da produção de entropia em modelos de spins com interação entre primeiros vizinhos e sujeitos a duas dinâmicas de Glauber, as quais simulam dois banhos térmicos a diferentes temperaturas. Para tanto, é admitido que o sistema corresponde a um processo markoviano contínuo no tempo o qual obedece a uma equação mestra. Dessa forma, o sistema atinge naturalmente estados estacionários, que podem ser de equilíbrio ou de não-equilíbrio. O primeiro corresponde exatamente ao modelo de Ising, que ocorre quando o sistema se encontra em contato com apenas um dos reservatórios. Dessa forma, há uma transição de fase na temperatura de Curie e o balanceamento detalhado é seguramente satisfeito. No segundo caso, os dois banhos térmicos são responsáveis por uma corrente de probabilidade que só existe visto que a reversibilidade microscópica não é mais verificada. Como conseqüência, nesse regime de não-equilíbrio o sistema apresenta uma produção de entropia não nula. Para avaliarmos os diagramas de fase e a produção de entropia utilizamos as aproximações de pares e as simulações de Monte Carlo. Além disso, admitimos que a teoria de escala finita pode ser aplicada no modelo. Esses métodos foram capazes de preverem as transições de fases sofridas pelo sistema. Os expoentes e os pontos críticos foram estimados através dos resultados numéricos. Para a magnetização e a susceptibilidade obtemos = 0,124(1) e = 1,76(1), o que nos permite concluir que o nosso modelo pertence à mesma classe de Ising. Esse resultado refere-se ao princípio da universalidade do ponto crítico, que é verificado devido o nosso modelo apresentar a mesma simetria de inversão que a do modelo de Ising. Além disso, as aproximações de pares também mostraram uma singularidade na derivada da produção de entropia no ponto crítico. E as simulações de Monte Carlo nos permitem sugerir que tal comportamento é uma divergência logarítmica cujo expoente crítico associado vale 1. / We study kinetic phase transitions and the critical behavior of the entropy production in spin models with nearest neighbor interactions subject to two Glauber dynamics, which simulate two thermal baths at different temperatures. In this way, it is assumed that the system corresponds to a continuous time Markov process which obeys the master equation. Thus, the system naturally reaches steady states, which can be equilibrium or nonequilibrium. The former corresponds exactly to the Ising model, which occurs since the system is in contact with only one of the reservoirs. In this case, there is a phase transition at the Curie temperature and the detailed balance surely holds. In the second case, the two thermal baths create a non trivial probability current only when microscopic reversibility is not verified. As a consequence, there is a positive entropy production in a non-equilibrium steady state. Pair approximations and Monte Carlo simulations are employed to evaluate the phase diagrams and the entropy production. Furthermore, we assume that the finite-size scaling theory can be applied to the model. These methods were able to predict the phase transitions undergone by the system. The exponents and the critical points were estimated by the numerical results. Our best estimates of critical exponents to the magnetization and susceptibility are = 0,124 (1) and = 1,76 (1), which allows us to conclude that our model belongs to the same class of Ising. This result refers to the principle of universality of the critical point, which is checked because our model has the same inversion symmetry of the Ising model. Moreover, the pair approximation also showed a singularity in the derivative of the entropy production at the critical point. And Monte Carlo simulations allow us to suggest that the divergence at the critical point is of the logarithmic type whose critical exponent is 1

ABSTRACT A theoretical and experimental study of the vibrational and chemical relaxation rates of diatomic gases, in flows behind shock waves and along nozzles,is made here. ¶ The validity of the conventional relaxation rate models, which are generally used to analyse experiments, is tested by developing a detailed microscopic description of the diatomic relaxation processes. Assuming the diatomic molecules to be represented by the anharmonic Morse Oscillator, the vibrational Master equation, which describes the time variation of each vibrational energy level population, is constructed by allowing one-quantum vibration to translation (V-T) energy exchanges and vibration to vibration (V-V) energy exchanges between the molecules. Dissociation and recombination are allowed to occur from, and to, the uppermost vibrational level. Solving the Master equation, it is found that a number of effects are explained by the inclusion of V-V transitions. In particular it is found that V-V energy exchanges cause the induction time for H2 dissociation to be increased; suggest that the linear rate law, for H2 and Ar mixtures, fails for a H2 mole fraction above 20%; give an acceleration of vibrational excitation as equilibrium is approached for H2 and N2; cause the vibrational temperature to be lower than the value found without V-V transitions for vibrational de-excitation in nozzle flows of H2 and N2, and conversely for recombination of H2 in nozzle flows. The most important result is the demonstration that conventional nozzle flow calculations, with shock-tube-determined dis-sociation and vibrational excitation rates, appear to be valid for the recombining and vibrationally de-excitating flows considered. ¶ The dissociation rates of undiluted nitrogen are measured in the free-piston shock tube DDT, using time-resolved optical interferometry, over a temperature range of 6000-14000K and confirm the strong temperature dependence of the pre-exponential factor observed by Hanson and Baganoff (1972). ¶ The vibrational de-excitation and excitation rates are determined in the small free-piston shock tunnel T2 over temperature ranges of 2000-4000K and 7000-10300K, respectively, by measuring the shock angles and curvatures, from optical interferograms, of flow over an inclined flat plate in the nonequilibrium nozzle flow. The de-excitation rate is found to be within a factor of ten of the excitation rate, while the excitation rate of N2 by collision with N is found to be less than about 50 times the excitation rate of N2 by N2. The dissociation rates of nitrogen, in the flow behind a shock attached to a wedge, are investigated in the large free-piston shock tunnel, using the shock curvature technique. The discrepancy, reported by Kewley and Hornung (1974b), between theory and experiment at the highest enthalpy is found to be resolved by including the measured helium contamination (Crane 1975) in the free-stream. Reasonable agreement is obtained between experimental shock curvatures and calculations using accepted dissociation rates.

Adhesion of biological cells to their environment is mediated by two-dimensional clusters of specific adhesion molecules which are assembled in the plasma membrane of the cells. Due to the activity of the cells or external influences, these adhesion sites are usually subject to physical forces. In recent years, the influence of such forces on the stability of cellular adhesion clusters was increasingly investigated. In particular, experimental methods that were originally designed for the investigation of single bond rupture under force have been applied to investigate the rupture of adhesion clusters. The transition from single to multiple bonds, however, is not trivial and requires theoretical modelling. <br><br> Rupture of biological adhesion molecules is a thermally activated, stochastic process. In this work, a stochastic model for the rupture and rebinding dynamics of clusters of parallel adhesion molecules under force is presented. In particular, the influence of (i) a constant force as it may be assumed for cellular adhesion clusters is investigated and (ii) the influence of a linearly increasing force as commonly used in experiments is considered. Special attention is paid to the force-mediated cooperativity of parallel adhesion bonds. Finally, the influence of a finite distance between receptors and ligands on the binding dynamics is investigated. Thereby, the distance can be bridged by polymeric linker molecules which tether the ligands to a substrate. / Adhäsionskontakte biologischer Zellen zu ihrer Umgebung werden durch zweidimensionale Cluster von spezifischen Adhäsionsmolekülen in der Plasmamembran der Zellen vermittelt. Aufgrund der Zellaktivität oder äußerer Einflüsse sind diese Kontakte normalerweise Kräften ausgesetzt. Der Einfluss mechanischer Kräfte auf die Stabilität zellulärer Adhäsionscluster wurde in den vergangenen Jahren verstärkt experimentell untersucht. Insbesondere wurden experimentelle Methoden, die zunächst vor allem zur Untersuchung des Reißssverhaltens einzelner Moleküle unter Kraft entwickelt wurden, zur Untersuchung von Adhäsionsclustern verwendet. Die Erweiterung von einzelnen auf viele Moleküle ist jedoch keineswegs trivial und erfordert theoretische Modellierung. <br><br> Das Reißen biologischer Adhäsionsmoleküle ist ein thermisch aktivierter, stochastischer Prozess. In der vorliegenden Arbeit wird ein stochastisches Modell zur Beschreibung der Reiß- und Rückbindedynamik von Clustern paralleler Adhäsionsmoleküle unter dem Einfluss einer mechanischen Kraft vorgestellt mit dem die Stabilität der Cluster untersucht wird. Im besonderen wird (i) der Einfluss einer konstante Kraft untersucht wie sie in zellulären Adhäsionsclustern angenommen werden kann und (ii) der Einfluss einer linear ansteigenden Kraft betrachtet wie sie gemeinhin in Experimenten angewendet wird. Besonderes Augenmerk liegt hier auf der durch die Kraft vermittelte Kooperativität paralleler Bindungen. Zuletzt wird der Einfluss eines endlichen Abstandes zwischen Rezeptoren und Liganden auf die Dynamik untersucht. Der Abstand kann hierbei durch Polymere, durch die die Liganden an das Substrat gebunden sind, überbrückt werden.