Nesta tese, mostramos que o modelo estocástico binário para expressão gênica, por um gene auto-regulado, possui solução completa. A solução dependente do tempo é escrita via expansão em termos das funções de Heun confluentes. Apresentamos um exemplo de dinâmica estocástica desse gene. Para tal, desenvolvemos uma relação de recorrência entre derivadas arbitrárias das funções de Heun confluentes. Mostramos também que o regime estacionário deste modelo possui simetria de Lie SO(2, 1) tipo Lorentz. Esta simetria é análoga à simetria do momento angular, porém com um sinal errado. O invariante desta álgebra define a meia-vida relativa do regime dinâmico do gene. O equivalente do momento angular azimutal é uma medida indireta do nível de atividade do gene. Os operadores levantamento e abaixamento conectam diferentes processos estocásticos de expressão proteínica. As flutuações destes processos estocásticos são classificadas em termos das relações entre os etiquetadores de um elemento da representação da álgebra. No arcabouço da teoria dos grupos, o modelo estocástico para um gene externamente regulado aparece como um caso particular do modelo para um gene auto-regulado. Mostramos, por fim, uma comparação entre estas duas estratégias de regulação. Demonstramos que um gene auto-regulado pode expressar proteínas em regimes sub Poisson, Poisson ou super Poisson. Por seu turno, o gene externamente regulado somente expressa proteínas em regimes Poisson ou super Poisson. Portanto, num processo estocástico, a auto-regulação mostra-se como uma forma de controle mais precisa. Também mostramos que a dinâmica de genes auto-regulados possui meia-vida mais curta que a de genes externamente regulados. Ou seja, a auto-regulação permite respostas mais rápidas à perturbações externas. / In this thesis we show that the stochastic binary model to protein synthesis by na auto-regulated gene is completely solvable. The time-dependent solution is written in terms of the confluent Heun functions. We present an example of probability dynamics to this gene. To get that, we developed a recurrence relation between arbitrary derivatives of the confluent Heun functions. We also show the existence of a Lorentz-like Lie symmetry SO(2, 1). This is an analogous to the angular momentum symmetry but presenting one wrong sign in its preserved form. This invariant defines the relative half-life of the dynamical regime of the gene. The equivalent of the azimuth angular momentum measures indirectly the activity level of the gene. The ladder operators connect distinct stochastic processes of protein synthesis. The fluctuations of these processes are classified in terms of the relation between labeling numbers of a representation of the algebra. In the group theory formalism, the stochastic model to an externally regulated gene is a particular case of the model to an auto-regulated gene. We compare these two gene regulation strategies, and show that the auto-regulated gene can synthesize proteins into the super Poisson, Poisson, and sub Poisson fluctuating regimes. The externally regulated gene only presents the super Poisson and Poisson regimes. Therefore, the auto-regulation is responsible for a more precise control of gene expression. We also show that the dynamics of the auto-regulated genes has a shorter half-life. Thus, the auto-regulation permits faster responses of the system to external perturbation.

Au sein d’un échangeur à air, les trompes à air permettent de créer l’écoulement d’air froid nécessaireà son bon fonctionnement. Ces dispositifs, qui peuvent ^etre assimilés à des jets subsoniques confinésen conduit, peuvent contribuer au bruit rayonné par les avions lors des phases au sol. Nous proposonsdans cette thèse de développer un outil numérique prédictif de l’acoustique rayonnée par ces dispositifsafin de pouvoir proposer des solutions de réduction de bruit appropriées. Cet outil est adapté au contexteindustriel de Liebherr Aerospace. Une méthode stochastique permet, à partir d’un calcul stationnaireRANS, de générer un champ de vitesse turbulente qui autorise la formation d’un terme de forçage dansles équations d’Euler linéarisées qui sont alors utilisées comme un opérateur de propagation. Un nouveaumodèle stochastique basé sur l’hypothèse de sweeping est développé. Ce dernier permet de produiredes champs instationnaires respectant certaines propriétés aérodynamiques statistiques dans le cadre dejets libres subsoniques. Cette méthode est couplée avec le solveur Euler de l’Onera sAbrinA_v0 et l’outilrésultant est appliqué sur le cas d’un jet libre subsonique à M=0.72. Moyennant une calibration duterme source, la méthodologie permet de reproduire les spectres acoustiques en champ lointain, exceptépour les angles faibles. L’outil numérique est ensuite couplé avec un solveur FW-H pour étudier le casconcret de la trompe à air. Les résultats aérodynamiques et acoustiques sont validés par comparaison àune base de données aérodynamique et acoustique constituée au préalable à partir d’une campagne d’essaiscomprenant des mesures par anémométrie laser Doppler à l’intérieur du conduit et des microphonesacoustiques en champ lointain. / In air exchangers, the cool air flow can be produced by jet pumps. These devices, which can be consideredas subsonic jets confined in ducts, could contribute directly to ramp noise. A predictive numerical toolof the acoustic radiated by jet pumps is therefore developped in order to be able to propose appropriatenoise reduction solutions. This tool is adapted to Liebherr Aerospace’s industrial context. A stochasticmethod allows, starting from a steady RANS computation, to synthetise a turbulent velocity fields andto enforce source terms in the linearized Euler equations therefore used as a wave propagator. A newstochastic model relying on the sweeping hypothesis is developped. Unsteady fields reproducing someaerodynamics features of a free subsonic jet flow can be generated. This method is then coupled withOnera’s Euler solver sAbrinA_v0 and the resulting tool is applied on a free subsonic jet configuration atMach 0.72. Assuming a cabration of the source terms, this methodology models properly the far fieldacoustic spectra except for small angles. The numerical tool is then coupled with a FW-H solver to studya realistic jet pump. Aerodynamic and acoustic results are validated by comparison with a data baseobtained from an experimental campaign including laser Doppler anemometry measures inside the ductand pressure recording in the far-field.

Dans cette thèse, nous étudions les effets cohérents associés à la propagation d’ondes dans les milieux diffusants, en particulier les ondes électromagnétiques.En milieux faiblement désordonnés, l'intensité lumineuse fluctue spatialement sur de grandes distances. Ce phénomène est le résultat d'effets cohérents mésoscopiques complexes, qui se produisent à une échelle microscopique. Nous montrons que ces fluctuations mésoscopiques cohérentes de la lumière induisent des forces de rayonnement d'un nouveau genre. L'amplitude de ces forces fluctuantes est déterminée par un paramètre unique et facilement réglable, la conductance adimensionnée, qui dépend à la fois de la géométrie et des propriétés de diffusion du milieu. Notre découverte devrait donc avoir des applications intéressantes, telles que de nouveaux capteurs pour la matière molle ou la biophysique.Du point de vue méthodologique, nous utilisons une approche à la Langevin pour décrire les fluctuations lumineuses cohérentes, où un bruit précisément calculé rend compte des effets cohérents mésoscopiques. Nous montrons comment inclure systématiquement les corrections cohérentes dans le terme de bruit, afin de reproduire les fluctuations d'intensité. Cette description permet de comprendre les fluctuations cohérentes comme résultant d’un flux lumineux hors équilibre, caractérisé par deux paramètres seulement, le coefficient de diffusion et la mobilité, qui sont par ailleurs liés par une relation d’Einstein. Un avantage évident de cette méthode est sa dépendance à deux paramètres seulement, ce qui fournit une description à la fois compacte et précise des riches effets cohérents sous-jacents. De plus, la correspondance que nous présentons entre la lumière cohérente et l'hydrodynamique hors d'équilibre est facilement généralisable à une large classe de problèmes d'ondes quantiques ou classiques.Pour les perspectives futures, cette connexion entre les effets cohérents mésoscopiques et les processus stochastiques hors équilibre devraient intéresser les communautés de la mésoscopie et de la mécanique statistique. Pour les premiers, le lien avec l'hydrodynamique hors équilibre fournit un nouvel éclairage sur la physique mésoscopique, ainsi que des outils utiles pour étudier les quantités jusqu'ici difficiles d'accès, telles que les fonctions de corrélation d'intensité d'ordres supérieurs. Pour les seconds, ces travaux devraient motiver une étude plus approfondie des processus indépendants du temps inspirés de la mésoscopie. / In this work, we study coherent effects associated to wave propagation in scattering media, in particular electromagnetic waves.In weakly disordered media, light intensity fluctuates spatially over large distances. This phenomenon is the result of complex mesoscopic coherent effects, which occur at a microscopic scale. We show that these mesoscopic coherent fluctuations of light induce radiation forces of a new kind. The strength of these fluctuating forces is determined by a single and easily tunable parameter, the dimensionless conductance, which depends on both the geometry and the scattering properties of the medium. Our findings should therefore have interesting applications such as new sensors in soft condensed matter or biophysics.On the methodological viewpoint, we use a hydrodynamic Langevin approach to describe the coherent light fluctuations, where a properly tailored noise accounts for mesoscopic coherent effects. We show how to systematically include the coherent corrections in the noise term, in order to reproduce the intensity fluctuations. This description allows to understand coherent light fluctuations as resulting from a non equilibrium light flow, characterized by two parameters only, the diffusion coefficient and the mobility, otherwise related by an Einstein relation. A clear asset of this method is its dependence upon two parameters only, which provides a compact yet accurate description of the rich underlying coherent effects. Moreover, the mapping we present between coherent light and out of equilibrium hydrodynamics is easily generalizable to a large class of quantum or classical wave problems.For future perspectives, this connection between coherent effects in mesoscopics and non equilibrium stochastic processes should be of interest in both the mesoscopics and statistical mechanics communities. For the former, the mapping to non equilibrium hydrodynamics provides a new insight to mesoscopic physics as well as useful tools to study quantities so far difficult to access, such as higher orders intensity correlation functions. For the latter, this work should motivate further study of time independent processes inspired from mesoscopics.

Similarity computation is a difficult issue in music information retrieval tasks, because it tries to emulate the special ability that humans show for pattern recognition in general, and particularly in the presence of noisy data. A number of works have addressed the problem of what is the best representation for symbolic music in this context. The tree representation, using rhythm for defining the tree structure and pitch information for leaf and node labelling has proven to be effective in melodic similarity computation. In this dissertation we try to built a system that allowed to classify and generate melodies using the information from the tree encoding, capturing the inherent dependencies which are inside this kind of structure, and improving the current methods in terms of accuracy and running time. In this way, we try to find more efficient methods that is key to use the tree structure in large datasets. First, we study the possibilities of the tree edit similarity to classify melodies using a new approach for estimate the weights of the edit operations. Once the possibilities of the cited approach are studied, an alternative approach is used. For that a grammatical inference approach is used to infer tree languages. The inference of these languages give us the possibility to use them to classify new trees (melodies).

The handling of variability effects in structural models is a natural and necessary extension of deterministic analysis techniques. In the context of finite element and uncertainty modelling, the stochastic finite element method (SFEM), grouping the perturbation SFEM, the spectral SFEM and the Monte-Carlo simulation, has by far received the major attention. <br> The present work focuses on second moment approaches, in which the first two statistical moments of the structural response are estimated. Due to its efficiency for handling problems involving low variability levels, the perturbation method is selected for characterising the propagation of the parameter variability from an uncertain dynamic model to its structural response. A dynamic model excited by a time-harmonic loading is postulated and the extension of the perturbation SFEM to the frequency domain is provided. This method complements the deterministic analysis by a sensitivity analysis of the system response with respect to a finite set of random parameters and a response surface in terms of a Taylor series expansion truncated to the first or second order is built. Taking into account the second moment statistical data of the random design properties, the response sensitivities are appropriately condensed in order to obtain an estimation of the response mean value and covariance structure. <br> In order to handle a wide definition of variability, a computational tool is made available that is able to deal with material variability sources (material random variables and fields) as well as shape uncertainty sources. This second case requires an appropriate shape parameterisation and a shape design sensitivity analysis. The computational requirements of the tool are studied and optimised, by reducing the size of the random dimension of the problem and by improving the performances of the underlying deterministic analyses. In this context, modal approaches, which are known to provide efficient alternatives to direct approaches in frequency domain analyses, are developed. An efficient hybrid procedure, coupling the perturbation and the Monte-Carlo simulation SFEM, is proposed and analysed. <br> Finally, the developed methods are validated, by resorting mainly to the Monte-Carlo simulation technique, on different numerical applications: a cantilever beam structure, a plate bending problem (involving a 3-dimensional model), an articulated truss structure and a problem involving a plate with a random flatness default. The propagation of the model uncertainty in the response FRFs and the effects involved by random field modelling are examined. Some remarks are stated pertaining to the influence of the parameter PDF in simulation-based methods. <br> <br> La gestion de la variabilité présente dans les modèles structuraux est une extension naturelle et nécessaire des techniques de calcul déterministes. En incorporant la modélisation de l'incertitude dans le calcul aux éléments finis, la méthode des éléments finis stochastiques (groupant l'approche perturbative, l'approche spectrale et la technique de simulation Monte-Carlo) a reçu une large attention de la littérature scientifique. <br> Ce travail est orienté sur les approches dites de second moment, dans lesquelles les deux premiers moments statistiques de la réponse de la structure sont estimés. De par son aptitude à traiter des problèmes caractérisés par de faibles niveaux de variabilité, la méthode perturbative est choisie pour propager la variabilité des paramètres d'un modèle dynamique incertain sur sa réponse. Un modèle sous chargement dynamique harmonique est supposé et l'extension dans le domaine fréquentiel de l'approche perturbative est établie. Cette méthode complète l'analyse déterministe par une analyse de sensibilité de la réponse du système par rapport à un ensemble fini de variables aléatoires. Une surface de réponse en termes d'un développement de Taylor tronqué au premier ou second ordre peut alors être écrit. Les sensibilités de la réponse sont enfin condensées, en tenant compte des propriétés statistiques des paramètres de design aléatoires, pour obtenir une estimation de la valeur moyenne et de la structure de covariance de la réponse. <br> Un outil de calcul est développé avec la capacité de gestion d'une définition large de la variabilité: sources de variabilité matérielle (variables et champs aléatoires) ainsi que géométrique. Cette dernière source requiert une paramétrisation adéquate de la géométrie ainsi qu'une analyse de sensibilité à des paramètres de forme. Les exigences calcul de cet outil sont étudiées et optimisées, en réduisant la dimension aléatoire du problème et en améliorant les performances des analyses déterministes sous-jacentes. Dans ce contexte, des approches modales, fournissant une alternative efficace aux approches directes dans le domaine fréquentiel, sont dérivées. Une procédure hybride couplant la méthode perturbative et la technique de simulation Monte-Carlo est proposée et analysée. <br> Finalement, les méthodes étudiées sont validées, principalement sur base de résultats de simulations Monte-Carlo. Ces résultats sont relatifs à plusieurs applications numériques: une structure poutre-console, un problème de flexion de plaque (modèle tridimensionnel), une structure en treillis articulé et un problème de plaque présentant un défaut de planéité aléatoire. La propagation de l'incertitude du modèle dans les fonctions de réponse fréquentielle ainsi que les effets propres à la modélisation par champs aléatoires sont examinés. Quelques remarques relatives à l'influence de la loi de distribution des paramètres dans les méthodes de simulation sont évoquées.

Bien que les matériaux composites renforcés par fibres végétales (PFCs) représentent une solution attractive pour la conception de structures légères, performantes et à faible coût environnemental, leur développement nécessite des études approfondies concernant les mécanismes à la base du comportement non-linéaire en traction exprimé, ainsi que de la variabilité des propriétés mécaniques. Compte tenu de leur caractère multi-échelle, ces travaux de thèse visent à contribuer, via une approche numérique, à l’étude de la propagation de comportement à travers les échelles des PFCs. Dans un premier temps, l’étude se focalise sur l’échelle fibre : un modèle 3D de comportement de la paroi est d’abord implémenté dans un calcul EF, afin d’établir l’influence de la morphologie de la fibre sur le comportement exprimé. Une fois l’impact non négligeable de la morphologie déterminé, une étude des liens entre morphologie, matériau et ultrastructure et comportement en traction est menée via une analyse de sensibilité dans le cas du lin et du chanvre. La deuxième partie du travail es dédiée à l’échelle du pli de composite. Une nouvelle approche multi-échelle stochastique est développée et implémentée. Elle est basée sur la définition d’un volume élémentaire (VE) à microstructure aléatoire pour décrire le comportement du pli. L’approche est ensuite utilisée pour étudier la sensibilité du comportement du VE aux paramètres nano, micro et mésoscopiques. L’analyse de sensibilité, menée via le développement de la réponse sur la base du chaos polynomial, nous permet ainsi de construire un métamodèle du comportement du pli. / Although plant-fiber reinforced composites (PFCs) represent an attractive solution for the design of lightweight, high performance and low environmental cost structures, their development requires in-depth studies of the mechanisms underlying their nonlinear tensile behavior, as well as variability of mechanical properties. Given their multi-scale nature, this thesis aims to contribute, using a numerical approach, to the study of the propagation of behavior across the scales of PFCs. Firstly, the study focuses on the fiber scale: a 3D model of the behavior of the wall is first implemented in an EF calculation, in order to establish the influence of fiber morphology on the tensile behavior. Once the non-negligible impact of the morphology has been determined, a study of the links between morphology, material and ultrastructure and tensile behavior is conducted via a sensitivity analysis in the case of flax and hemp. The second part of the work is dedicated to the composite ply scale. A new stochastic multi-scale approach is developed and implemented. It is based on the definition of an elementary volume (VE) with random microstructure to describe the behavior of the ply. The approach is then used to study the sensitivity of VE behavior to nano, micro and mesoscopic parameters. Sensitivity analysis, conducted via the development of the response on the basis of polynomial chaos, allows us to construct a metamodel of the tensile behavior of the ply.

Landslides cause significant damage to property and human lives throughout the world. Rainfall is the most common triggering factor for the occurrence of landslides. This dissertation presents two novel methodologies for assessment of rainfall-triggered shallow landslide hazard. The first method focuses on using remotely sensed soil moisture and soil surface properties in developing a framework for real-time regional scale landslide hazard assessment while the second method is a deterministic approach to landslide hazard assessment of the specific sites identified during first assessment. In the latter approach, landslide inducing transient seepage in soil during rainfall and its effect on slope stability are modeled using numerical analysis. Traditionally, the prediction of rainfall-triggered landslides has been performed using pre-determined rainfall intensity-duration thresholds. However, it is the infiltration of rainwater into soil slopes which leads to an increase of porewater pressure and destruction of matric suction that causes a reduction in soil shear strength and slope instability. Hence, soil moisture, pore pressure and infiltration properties of soil must be direct inputs to reliable landslide hazard assessment methods. In-situ measurement of pore pressure for real-time landslide hazard assessment is an expensive endeavor and thus, the use of more practical remote sensing of soil moisture is constantly sought. In past studies, a statistical framework for regional scale landslide hazard assessment using remotely sensed soil moisture has not been developed. Thus, the first major objective of this study is to develop a framework for using downscaled remotely sensed soil moisture available on a daily basis to monitor locations that are highly susceptible to rainfall- triggered shallow landslides, using a well-structured assessment procedure. Downscaled soil moisture, the relevant geotechnical properties of saturated hydraulic conductivity and soil type, and the conditioning factors of elevation, slope, and distance to roads are used to develop an improved logistic regression model to predict the soil slide hazard of soil slopes using data from two geographically different regions. A soil moisture downscaling model with a proven superior prediction accuracy than the downscaling models that have been used in previous landslide studies is employed in this study. Furthermore, this model provides satisfactory classification accuracy and performs better than the alternative water drainage-based indices that are conventionally used to quantify the effect that elevated soil moisture has upon the soil sliding. Furthermore, the downscaling of soil moisture content is shown to improve the prediction accuracy. Finally, a technique that can determine the threshold probability for identifying locations with a high soil slide hazard is proposed. On the other hand, many deterministic methods based on analytical and numerical methodologies have been developed in the past to model the effects of infiltration and subsequent transient seepage during rainfall on the stability of natural and manmade slopes. However, the effects of continuous interplay between surface and subsurface water flows on slope stability is seldom considered in the above-mentioned numerical and analytical models. Furthermore, the existing seepage models are based on the Richards equation, which is derived using Darcy’s law, under a pseudo-steady state assumption. Thus, the inertial components of flow have not been incorporated typically in modeling the flow of water through the subsurface. Hence, the second objective of this study is to develop a numerical model which has the capability to model surface, subsurface and infiltration water flows based on a unified approach, employing fundamental fluid dynamics, to assess slope stability during rainfall-induced transient seepage conditions. The developed model is based on the Navier-Stokes equations, which possess the capability to model surface, subsurface and infiltration water flows in a unified manner. The extended Mohr-Coulomb criterion is used in evaluating the shear strength reduction due to infiltration. Finally, the effect of soil hydraulic conductivity on slope stability is examined. The interplay between surface and subsurface water flows is observed to have a significant impact on slope stability, especially at low hydraulic conductivity values. The developed numerical model facilitates site-specific calibration with respect to saturated hydraulic conductivity, remotely sensed soil moisture content and rainfall intensity to predict landslide inducing subsurface pore pressure variations in real time.

The quantum dynamics and grand canonical thermodynamics of many-mode (one-, two-, and three-dimensional) interacting Bose gases are simulated from first principles. The model uses a lattice Hamiltonian based on a continuum second-quantized model with two-particle interactions, external potential, and interactions with an environment, with no further approximations. The interparticle potential can be either an (effective) delta function as in Bose-Hubbard models, or extended with a shape resolved by the lattice. Simulations are of a set of stochastic equations that in the limit of many realizations correspond exactly to the full quantum evolution of the many-body systems. These equations describe the evolution of samples of the gauge P distribution of the quantum state, details of which are developed. Conditions under which general quantum phase-space representations can be used to derive stochastic simulation methods are investigated in detail, given the criteria: 1) The simulation corresponds exactly to quantum mechanics in the limit of many trajectories. 2) The number of equations scales linearly with system size, to allow the possibility of efficient first-principles quantum mesoscopic simulations. 3) All observables can be calculated from one simulation. 4) Each stochastic realization is independent to allow straightforward use of parallel algorithms. Special emphasis is placed on allowing for simulation of open systems. In contrast to typical Monte Carlo techniques based on path integrals, the phase-space representation approach can also be used for dynamical calculations. Two major (and related) known technical stumbling blocks with such stochastic simulations are instabilities in the stochastic equations, and pathological trajectory distributions as the boundaries of phase space are approached. These can (and often do) lead to systematic biases in the calculated observables. The nature of these problems are investigated in detail. Many phase-space distributions have, however, more phase-space freedoms than the minimum required for exact correspondence to quantum mechanics, and these freedoms can in many cases be exploited to overcome the instability and boundary term problems, recovering an unbiased simulation. The stochastic gauge technique, which achieves this in a systematic way, is derived and heuristic guidelines for its use are developed. The gauge P representation is an extension of the positive P distribution, which uses coherent basis states, but allows a variety of useful stochastic gauges that are used to overcome the stability problems. Its properties are investigated, and the resulting equations to be simulated for the open interacting Bose gas system are derived. The dynamics of the following many-mode systems are simulated as examples: 1) Uniform one-dimensional and two-dimensional Bose gases after the rapid appearance of significant two-body collisions (e.g. after entering a Feshbach resonance). 2) Trapped bosons, where the size of the trap is of the same order as the range of the interparticle potential. 3) Stimulated Bose enhancement of scattered atom modes during the collision of two Bose-Einstein condensates. The grand canonical thermodynamics of uniform one-dimensional Bose gases is also calculated for a variety of temperatures and collision strengths. Observables calculated include first to third order spatial correlation functions (including at finite interparticle separation) and momentum distributions. The predicted phenomena are discussed. Improvements over the positive P distribution and other methods are discussed, and simulation times are analyzed for Bose-Hubbard lattice models from a general perspective. To understand the behavior of the equations, and subsequently optimize the gauges for the interacting Bose gas, single- and coupled two-mode dynamical and thermodynamical models of interacting Bose gases are investigated in detail. Directions in which future progress can be expected are considered. Lastly, safeguards are necessary to avoid biased averages when exponentials of Gaussian-like trajectory distributions are used (as here), and these are investigated.

The quantum dynamics and grand canonical thermodynamics of many-mode (one-, two-, and three-dimensional) interacting Bose gases are simulated from first principles. The model uses a lattice Hamiltonian based on a continuum second-quantized model with two-particle interactions, external potential, and interactions with an environment, with no further approximations. The interparticle potential can be either an (effective) delta function as in Bose-Hubbard models, or extended with a shape resolved by the lattice. Simulations are of a set of stochastic equations that in the limit of many realizations correspond exactly to the full quantum evolution of the many-body systems. These equations describe the evolution of samples of the gauge P distribution of the quantum state, details of which are developed. Conditions under which general quantum phase-space representations can be used to derive stochastic simulation methods are investigated in detail, given the criteria: 1) The simulation corresponds exactly to quantum mechanics in the limit of many trajectories. 2) The number of equations scales linearly with system size, to allow the possibility of efficient first-principles quantum mesoscopic simulations. 3) All observables can be calculated from one simulation. 4) Each stochastic realization is independent to allow straightforward use of parallel algorithms. Special emphasis is placed on allowing for simulation of open systems. In contrast to typical Monte Carlo techniques based on path integrals, the phase-space representation approach can also be used for dynamical calculations. Two major (and related) known technical stumbling blocks with such stochastic simulations are instabilities in the stochastic equations, and pathological trajectory distributions as the boundaries of phase space are approached. These can (and often do) lead to systematic biases in the calculated observables. The nature of these problems are investigated in detail. Many phase-space distributions have, however, more phase-space freedoms than the minimum required for exact correspondence to quantum mechanics, and these freedoms can in many cases be exploited to overcome the instability and boundary term problems, recovering an unbiased simulation. The stochastic gauge technique, which achieves this in a systematic way, is derived and heuristic guidelines for its use are developed. The gauge P representation is an extension of the positive P distribution, which uses coherent basis states, but allows a variety of useful stochastic gauges that are used to overcome the stability problems. Its properties are investigated, and the resulting equations to be simulated for the open interacting Bose gas system are derived. The dynamics of the following many-mode systems are simulated as examples: 1) Uniform one-dimensional and two-dimensional Bose gases after the rapid appearance of significant two-body collisions (e.g. after entering a Feshbach resonance). 2) Trapped bosons, where the size of the trap is of the same order as the range of the interparticle potential. 3) Stimulated Bose enhancement of scattered atom modes during the collision of two Bose-Einstein condensates. The grand canonical thermodynamics of uniform one-dimensional Bose gases is also calculated for a variety of temperatures and collision strengths. Observables calculated include first to third order spatial correlation functions (including at finite interparticle separation) and momentum distributions. The predicted phenomena are discussed. Improvements over the positive P distribution and other methods are discussed, and simulation times are analyzed for Bose-Hubbard lattice models from a general perspective. To understand the behavior of the equations, and subsequently optimize the gauges for the interacting Bose gas, single- and coupled two-mode dynamical and thermodynamical models of interacting Bose gases are investigated in detail. Directions in which future progress can be expected are considered. Lastly, safeguards are necessary to avoid biased averages when exponentials of Gaussian-like trajectory distributions are used (as here), and these are investigated.

Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro / As técnicas inversas têm sido usadas na determinação de parâmetros importantes envolvidos na concepção e desempenho de muitos processos industriais. A aplicação de métodos estocásticos tem aumentado nos últimos anos, demonstrando seu potencial no estudo e análise dos diferentes sistemas em aplicações de engenharia. As rotinas estocásticas são capazes de otimizar a solução em uma ampla gama de variáveis do domínio, sendo possível a determinação dos parâmetros de interesse simultaneamente. Neste trabalho foram adotados os métodos estocásticos Luus-Jaakola (LJ) e Random Restricted Window (R2W) na obtenção dos ótimos dos parâmetros cinéticos de adsorção no sistema de cromatografia em batelada, tendo por objetivo verificar qual método forneceria o melhor ajuste entre os resultados obtidos nas simulações computacionais e os dados experimentais. Este modelo foi resolvido empregando o método de Runge- Kutta de 4 ordem para a solução de equações diferenciais ordinárias. / The inverse techniques have been used in the determination of parameters involved in design and performance of many industrial processes. The application of stochastic methods has increased in recent years, demonstrating their potential in study and analysis of different systems in engineering applications. Stochastic routines are able to optimize the solution in a wide range of variables, it is possible to determine the parameters of interest simultaneously. In this work two adopted the stochastic methods, Luus-Jaakola (LJ) and Restricted Random Window (R2W), to obtain the optimum parameters for adsorption kinetics in batch chromatography system, aiming to determine which method would provide the best fit between the results obtained in computer simulations and experimental data. This model was solved using the Runge-Kutta 4th order for ordinary differential equations solution.