The heterogeneous condensation of a vapour onto a substrate is a key step in a wide range of chemical and physical process that occur in both nature and technology. For example, dust and pollutant aerosol particles, ranging in size from several microns down to just a few nanometers, serve as cloud condensation nuclei in the atmosphere, and nanoscale structured surfaces provide templates for the controlled nucleation and growth of variety of complex materials. While much is known about the general features of heterogeneous nucleation onto macroscopic surfaces, much less is understood about both the dynamics and thermodynamics of nucleation involving nanoscale heterogeneities. The goal of this thesis is to understand the general features of condensation of vapours onto different types of nanoscale heterogeneity that range in degree of solubility from being insoluble, to partially miscible through to completely miscible. The heterogeneous condensation of the Lennard-Jones vapour onto an insoluble nanoscale seed particle is studied using a combination of molecular dynamics simulations and thermodynamic theory. The nucleation rate and free energy barrier are calculated from molecular dynamics using the mean first passage time method. These results show that the presence of a weakly interacting seed has no effect on the formation of small cluster embryos but accelerates the rate by lowering the free energy barrier of the larger clusters. A simple phenomenological model of film formation on a small seed is developed by extending the capillarity based liquid drop model. It captures the general features of heterogeneous nucleation, but a comparison with the simulation results show that the model significantly overestimates the height of the nucleation barrier while providing good estimates of the critical film size. A non-volatile liquid drop model that accounts for solution non-ideality is developed to describe the thermodynamics of partially miscible and fully miscible droplets in a solvent vapour. The model shows ideal solution drops dissolve always spontaneously, but partially miscible drops exhibit a free energy surface with two minima, associated with a partially dissolved drop and a fully dissolved drop, separated by a free energy barrier. The solubility transition between the two drops is shown to follow a hysteresis loop as a function of system volume similar to that observed in deliquescence. A simple lattice gas model describing the absorption of mono-layers of vapour onto the particle is also developed. Finally, molecular dynamics simulation of miscible and partially miscible binary Lennard-Jones mixtures are also used to study this system. For all cases studied, condensation onto the drop occurs spontaneously. Sub-monolayers of the solvent phase form when the system volume is large. At smaller system volumes, complete film formation is observed and the dynamics of film growth are dominated by cluster-cluster coalescence. Some degree of mixing into the core of the particle is observed for the miscible mixtures for all volumes. However, mixing of the solvent into the particle core only occurs below an onset volume for the partially miscible case, suggesting the presence of a solubility transition similar to the one described by the thermodynamic model.

We consider the motion of a Brownian particle trapped in an arbitrary bounded two or three-dimensional domain, whose boundary is reflecting except for a small absorbing window through which the particle can escape. We use the method of matched asymptotic expansions to calculate the mean first passage time, defined as the time taken for the Brownian particle to escape from the domain through the absorbing window. This is known as the narrow escape problem. Since the mean escape time diverges as the window shrinks, the calculation is a singular perturbation problem. We extend our results to include N absorbing windows of varying length in two dimensions and varying radius in three dimensions. We present findings in two dimensions for the unit disk, unit square and ellipse and in three dimensions for the unit sphere. The narrow escape problem has various applications in many fields including finance, biology, and statistical mechanics.

We consider the motion of a Brownian particle trapped in an arbitrary bounded two or three-dimensional domain, whose boundary is reflecting except for a small absorbing window through which the particle can escape. We use the method of matched asymptotic expansions to calculate the mean first passage time, defined as the time taken for the Brownian particle to escape from the domain through the absorbing window. This is known as the narrow escape problem. Since the mean escape time diverges as the window shrinks, the calculation is a singular perturbation problem. We extend our results to include N absorbing windows of varying length in two dimensions and varying radius in three dimensions. We present findings in two dimensions for the unit disk, unit square and ellipse and in three dimensions for the unit sphere. The narrow escape problem has various applications in many fields including finance, biology, and statistical mechanics.

Organisms have movements that are usually modeled by particles’ random walks. Under some mathematical technical assumptions the movements are described by diffusion equations. However, empirical data often show that the movements are not simple random walks. Instead, they are correlated random walks and are described by telegraph equations. This thesis considers telegraph equations with and without bias corresponding to correlated random walks with and without bias. Analytical solutions to the equations with absorbing boundary conditions and their mean passage times are obtained. Numerical simulations of the corresponding correlated random walks are also performed. The simulation results show that the solutions are approximated very well by the corresponding correlated random walks and the mean first passage times are highly consistent with those from simulations on the corresponding random walks. This suggests that telegraph equations can be a good model for organisms with the movement pattern of correlated random walks. Furthermore, utilizing the consistency of mean first passage times, we can estimate the parameters of telegraph equations through the mean first passage time, which can be estimated through experimental observation. This provides biologists an easy way to obtain parameter values. Finally, this thesis analyzes the velocity distribution and correlations of movement steps of amoebas, leaving fitting the movement data to telegraph equations as future work.

We consider the motion of a Brownian particle trapped in an arbitrary bounded two or three-dimensional domain, whose boundary is reflecting except for a small absorbing window through which the particle can escape. We use the method of matched asymptotic expansions to calculate the mean first passage time, defined as the time taken for the Brownian particle to escape from the domain through the absorbing window. This is known as the narrow escape problem. Since the mean escape time diverges as the window shrinks, the calculation is a singular perturbation problem. We extend our results to include N absorbing windows of varying length in two dimensions and varying radius in three dimensions. We present findings in two dimensions for the unit disk, unit square and ellipse and in three dimensions for the unit sphere. The narrow escape problem has various applications in many fields including finance, biology, and statistical mechanics. / Science, Faculty of / Mathematics, Department of / Graduate

This dissertation presents a theoretical study of arbitrary discretizations of general nonequilibrium and non-steady-state systems. It will be shown that, without requiring the partitions of the phase-space to fulfill certain assumptions, such as culminating in Markovian partitions, a Markov chain can be constructed which has the same macro-change of probability of the occupation of the states as the original process. This is true for any classical and semiclassical system under any discrete or continuous, deterministic or stochastic, Markovian or non-Markovian dynamics. Restricted to classical and semi-classical systems, a formalism is developed which treats the projection of arbitrary (multidimensional) complex systems onto a discrete set of states of an abstract state-space using time and ensemble sampled transitions between the states of the trajectories of the original process. This formalism is then used to develop expressions for the mean first passage time and (in the case of projections resulting in pseudo-one-dimensional motion) for the individual residence times of the states using just the time and ensemble sampled transition rates. The theoretical work is illustrated by several numerical examples of non-linear diffusion processes. Those include the escape over a Kramers potential and a rough energy barrier, the escape from an entropic barrier, the folding process of a toy model of a linear polymer chain and the escape over a fluctuating barrier. The latter is an example of a non- Markovian dynamics of the original process. The results for the mean first passage time and the residence times (using both physically meaningful and non-meaningful partitions of the phase-space) confirms the theory. With an accuracy restricted only by the resolution of the measurement and/or the finite sampling size, the values of the mean first passage time of the projected process agree with those of a direct measurement on the original dynamics and with any available semi-analytical solution.

La théorie des bifurcations est utilisée pour étudier certains aspects des systèmes dynamiques qui intervient lorsqu'un petit changement d'un paramètre physique produit un changement majeur dans l'organisation du système. Ces phénomènes ont lieu dans les systèmes physiques, chimiques, biologiques, écologiques, économiques et sociaux. Cette idée unificatrice a été appliquée pour modéliser et explorer à la fois tant les systèmes sociaux que les systèmes physiques. Dans la première partie de cette thèse, nous appliquons les outils de la physique statistique et de la théorie des bifurcations pour modéliser le problème des décisions binaires dans les sciences sociales. Nous avons mis au point un schéma permettant de prédire l’apparition de sauts extrêmes dans ces systèmes en se basant sur la notion de précurseurs, utilisés comme signal d'alerte d'apparition de ces événements catastrophiques. Nous avons également résolu un modèle mathématique d’effondrement social fondé sur une équation de "régression logistique" utilisée pour décrire la croissance d’une population et la façon dont celle-ci peut être influencée par des ressources limitées. Ce modèle présente des bifurcations sous-critiques et nous avons étudié sa relation avec le phénomène social du « sunk-cost effect » (effet de coût irrécupérable). Ce dernier phénomène explique l’influence des investissements passés sur les décisions présentes, et la combinaison de ces deux phénomènes est utilisé comme modèle pour expliquer la désintégration de certaines sociétés anciennes (basés sur des témoignages archéologiques). Dans la deuxième partie de cette thèse, nous étudions les systèmes macroscopiques décrits par des équations différentielles stochastiques multidimensionnelles ou, de manière équivalente, par les équations multidimensionnelles de Fokker-Planck. Afin de calculer la fonction de distribution de probabilité (PDF), nous avons introduit un nouveau schéma alternatif de calcul basé sur les intégrales de chemin (« Path Integral ») lié aux processus stochastiques. Les calculs basés sur les intégrales de chemin sont effectués sur des systèmes uni et bidimensionnels et successivement comparés avec certains modèles dont on connaît la solution pour confirmer la validité de notre méthode. Nous avons également étendu ce schéma pour estimer le temps d’activation moyen (« Mean Exit Time »), ce qui a donné lieu à une nouvelle expression de calcul pour les systèmes à dimension arbitraire. A` noter que pour le cas des systèmes dynamiques à deux dimensions, les calculs de la fonction de distribution de probabilité ainsi que du temps de sortie moyen ont validé le schéma des intégrales du chemin. Ça vaut la peine de souligner que la perspective de poursuivre cette ligne de recherche repose sur le fait que cette méthode est valable pour les « non gradient systems » assujettis à des bruits d'intensité arbitraires. Cela ouvre la possibilité d'analyser des situations plus complexes où, à l'heure actuelle, il n'existe aucune méthode permettant de calculer les PDFs et/ou les METs. / Bifurcations in continuous dynamical systems, i.e., those described by ordinary differential equations, are found in a multitude of models such as those used to study phenomena related to physical, chemical, biological, ecological, economic and social systems. Using this concept as a unifying idea, in this thesis, we apply it to model and explore both Social as well as Physical systems. In the first part of this thesis we apply tools of statistical physics and bifurcation theory to model a problem of binary decision in Social Sciences. We find an scheme to predict the appearance of extreme jumps in these systems based on the notion of precursors which act as a kind of warning signal for the upcoming appearance of these catastrophic events. We also solve a mathematical model of social collapse based on a logistic re-growing equation used to model population grow and how limited resources change grow patterns. This model exhibits subcritical bifurcations and its relation to the social phenomenon of sunk-cost effect is studied. This last phenomenon explains how past investments affect current decisions and the combination of both phenomena is used as a model to explain the disintegration of some ancient societies, based on evidence from archeological records. In the second part of this thesis, we study macroscopic systems described by multidimensional stochastic differential equations or equivalently by their deterministic counterpart, the multidimensional FokkerPlanck equation. A new and alternative scheme of computation based on Path Integrals, related to stochastic processes is introduced in order to calculate the Probability Distribution Function. The computations based on this Path Integral scheme are performed on systems in one and two dimensions and contrasted to some soluble models completely validating this method. We also extended this scheme to the case of computation of Mean Exit Time, finding a new expression for each computation in systems in arbitrary dimensions. It is worth noting that in case of two-dimensional dynamical systems, the computations of both the probability distribution function as well as of the mean exit time validated the Path Integral scheme and the perspective for continuing this line of work are based on the fact that this method is valid for both arbitrary non gradient systems and noise intensities. This opens the possibility to explore new cases, for which no methods are known to obtain them.

Cette thèse s'intéresse à l'étude des stratégies d'introduction de populations dans l'environnement. Les deux principaux contextes présentés sont la lutte biologique et la réintroduction d'espèces. Si ces deux types d'introduction diffèrent, des processus biotiques et abiotiques les influencent de manière similaire. En particulier les populations introduites, souvent de petite taille, peuvent être sensibles à diverses formes de stochasticité, voire subir une baisse de leur taux de croissance à faible effectif, ce qu'on appelle « effet Allee ». Ces processus peuvent interagir avec les stratégies d'introduction des organismes et moduler leur efficacité. Dans un premier temps, nous modélisons le processus d'introduction à l'aide de systèmes dynamiques impulsionnels : la dynamique de la population est décrite par des équations différentielles ordinaires qui, à des instants donnés, sont perturbées par des augmentations soudaines de la taille de la population. Cette approche se concentre sur l'influence des effets Allee sur les populations isolées (réintroduction) ou dans un cadre proie-prédateur (lutte biologique). Dans un second temps, en nous concentrant sur l'aspect réintroduction, nous étendons ce cadre de modélisation pour prendre en compte des aspects stochastiques liés à l'environnement ou aux introductions elles-mêmes. Finalement, nous considérons un modèle individu centré pour étudier l'effet de la stochasticité démographique inhérente aux petites populations. Ces différentes approches permettent d'analyser l'influence de la distribution temporelle des introductions et ainsi déterminer les stratégies qui maximisent les chances de succès des introductions. / This thesis investigates introduction strategies of populations in the environment. Two main situations are considered: biological control and species reintroduction. Although these two kinds of introductions are different, many biotic and abiotic processes influence them in a similar way. Introduced populations are often small and may be sensitive to various stochastic factors. Further, small populations may suffer from a decrease of their growth rate when the population is small, a feature called "Allee effect". These processes may interact with introduction strategies and modulate their efficiency. First, we represent the introduction process using impulsive dynamical systems: population dynamics are described by ordinary differential equations that are disrupted at some instants by instantaneous increases of the population size. This approach focuses on the influence of Allee effects on single-species (reintroduction) or predator-prey interactions (biological control). Then, we concentrate on the reintroduction approach and extend the previous deterministic framework to take into consideration stochastic factors arising from the environment or from introductions themselves. Finally, we consider an individual-based model to study the effects of demographic stochasticity which is inherent to small populations. These different approaches allow to investigate the temporal distribution of introductions and determine which introduction strategies maximize the probability of success of introductions.