Dissertations / Theses on the topic 'Stochastic ordinary differential equations'

PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE EXCELENCIA ACADEMICA
O presente trabalho teve como objetivo principal investigar o potencial de algoritmos computacionais evolutivos, construídos a partir das técnicas de programação genética, combinados com diferenciação automática, na obtenção de soluções analíticas, exatas ou aproximadas, para problemas de equações diferenciais ordinárias (EDO), parciais (EDP) e estocásticas. Com esse intuito, e utilizando-se o ambiente de programação Matlab, diversos algoritmos foram elaborados e soluções analíticas de diferentes tipos de equações diferenciais foram determinadas. No caso das equações determinísticas, EDOs e EDPs, foram abordados problemas de diferentes graus de dificuldade, do básico até problemas complexos como o da equação do calor e a equação de Schrödinger para o átomo de hélio. Os resultados obtidos são promissores, com soluções exatas para a grande maioria dos problemas tratados e que atestam, empiricamente, a consistência e robustez da metodologia proposta. Com relação às equações estocásticas, o trabalho apresenta uma nova proposta de solução e metodologia alternativa para a precificação de opções europeias, de compra e de venda, e realiza algumas aplicações para o mercado brasileiro, com ações da Petrobras e da Vale. Além destas aplicações, são apresentadas as soluções de alguns modelos clássicos, usualmente utilizados na modelagem de preços e retornos de ativos financeiros, como, por exemplo, o movimento Browniano geométrico. De uma forma geral, os resultados obtidos nas aplicações indicam que a metodologia proposta nesta tese pode ser uma alternativa eficiente na modelagem de problemas científicos complexos.
The main objective of this work was to investigate the potential of evolutionary algorithms, built from genetic programming techniques and combined with automatic differentiation, in obtaining exact or approximate analytical solutions for problems of ordinary (ODE), partial (PDE), and stochastic differential equations. To this end, and using the Matlab programming environment, several algorithms were developed and analytical solutions of different types of differential equations were determined. In the case of deterministic equations, ODE and PDE problems of varying degrees of difficulty were discussed, from basic to complex problems such as the heat equation and the Schrödinger equation for the helium atom. The results are promising, including exact solutions for the vast majority of the problems treated, which attest empirically the consistency and robustness of the proposed methodology. Regarding the stochastic equations, the work presents a new proposal for a solution and alternative methodology for European options pricing, buying and selling, and performs some applications for the Brazilian market, with stock prices of Petrobras and Vale. In addition to these applications, there are presented solutions of some classical models, usually used in the modeling of prices and returns of financial assets, such as the geometric Brownian motion. In a general way, the results obtained in applications indicate that the methodology proposed in this dissertation can be an efficient alternative in modeling complex scientific problems.

The stochastic process algebra PEPA is a powerful modelling formalism for concurrent systems, which has enjoyed considerable success over the last decade. Such modelling can help designers by allowing aspects of a system which are not readily tested, such as protocol validity and performance, to be analysed before a system is deployed. However, model construction and analysis can be challenged by the size and complexity of large scale systems, which consist of large numbers of components and thus result in state-space explosion problems. Both structural and quantitative analysis of large scale PEPA models suffers from this problem, which has limited wider applications of the PEPA language. This thesis focuses on developing PEPA, to overcome the state-space explosion problem, and make it suitable to validate and evaluate large scale computer and communications systems, in particular a content adaption framework proposed by the Mobile VCE. In this thesis, a new representation scheme for PEPA is proposed to numerically capture the structural and timing information in a model. Through this numerical representation, we have found that there is a Place/Transition structure underlying each PEPA model. Based on this structure and the theories developed for Petri nets, some important techniques for the structural analysis of PEPA have been given. These techniques do not suffer from the state-space explosion problem. They include a new method for deriving and storing the state space and an approach to finding invariants which can be used to reason qualitatively about systems. In particular, a novel deadlock-checking algorithm has been proposed to avoid the state-space explosion problem, which can not only efficiently carry out deadlock-checking for a particular system but can tell when and how a system structure lead to deadlocks. In order to avoid the state-space explosion problem encountered in the quantitative analysis of a large scale PEPA model, a fluid approximation approach has recently been proposed, which results in a set of ordinary differential equations (ODEs) to approximate the underlying CTMC. This thesis presents an improved mapping from PEPA to ODEs based on the numerical representation scheme, which extends the class of PEPA models that can be subjected to fluid approximation. Furthermore, we have established the fundamental characteristics of the derived ODEs, such as the existence, uniqueness, boundedness and nonnegativeness of the solution. The convergence of the solution as time tends to infinity for several classes of PEPA models, has been proved under some mild conditions. For general PEPA models, the convergence is proved under a particular condition, which has been revealed to relate to some famous constants of Markov chains such as the spectral gap and the Log-Sobolev constant. This thesis has established the consistency between the fluid approximation and the underlying CTMCs for PEPA, i.e. the limit of the solution is consistent with the equilibrium probability distribution corresponding to a family of underlying density dependent CTMCs. These developments and investigations for PEPA have been applied to both qualitatively and quantitatively evaluate the large scale content adaptation system proposed by the Mobile VCE. These analyses provide an assessment of the current design and should guide the development of the system and contribute towards efficient working patterns and system optimisation.

Parameter estimation techniques have been successfully and extensively applied to deterministic models based on ordinary differential equations but are in early development for stochastic models. In this thesis, we first investigate using parameter estimation techniques for a deterministic model to approximate parameters in a corresponding stochastic model. The basis behind this approach lies in the Kurtz limit theorem which implies that for large populations, the realizations of the stochastic model converge to the deterministic model. We show for two example models that this approach often fails to estimate parameters well when the population size is small. We then develop a new method, the MCR method, which is unique to stochastic models and provides significantly better estimates and smaller confidence intervals for parameter values. Initial analysis of the new MCR method indicates that this method might be a viable method for parameter estimation for continuous time Markov chain models.

The performance modelling of large-scale systems using discrete-state approaches is fundamentally hampered by the well-known problem of state-space explosion, which causes exponential growth of the reachable state space as a function of the number of the components which constitute the model. Because they are mapped onto continuous-time Markov chains (CTMCs), models described in the stochastic process algebra PEPA are no exception. This thesis presents a deterministic continuous-state semantics of PEPA which employs ordinary differential equations (ODEs) as the underlying mathematics for the performance evaluation. This is suitable for models consisting of large numbers of replicated components, as the ODE problem size is insensitive to the actual population levels of the system under study. Furthermore, the ODE is given an interpretation as the fluid limit of a properly defined CTMC model when the initial population levels go to infinity. This framework allows the use of existing results which give error bounds to assess the quality of the differential approximation. The computation of performance indices such as throughput, utilisation, and average response time are interpreted deterministically as functions of the ODE solution and are related to corresponding reward structures in the Markovian setting. The differential interpretation of PEPA provides a framework that is conceptually analogous to established approximation methods in queueing networks based on meanvalue analysis, as both approaches aim at reducing the computational cost of the analysis by providing estimates for the expected values of the performance metrics of interest. The relationship between these two techniques is examined in more detail in a comparison between PEPA and the Layered Queueing Network (LQN) model. General patterns of translation of LQN elements into corresponding PEPA components are applied to a substantial case study of a distributed computer system. This model is analysed using stochastic simulation to gauge the soundness of the translation. Furthermore, it is subjected to a series of numerical tests to compare execution runtimes and accuracy of the PEPA differential analysis against the LQN mean-value approximation method. Finally, this thesis discusses the major elements concerning the development of a software toolkit, the PEPA Eclipse Plug-in, which offers a comprehensive modelling environment for PEPA, including modules for static analysis, explicit state-space exploration, numerical solution of the steady-state equilibrium of the Markov chain, stochastic simulation, the differential analysis approach herein presented, and a graphical framework for model editing and visualisation of performance evaluation results.

Stochastic effects in cellular systems are usually modeled and simulated with Gillespie's stochastic simulation algorithm (SSA), which follows the same theoretical derivation as the chemical master equation (CME), but the low efficiency of SSA limits its application to large chemical networks. To improve efficiency of stochastic simulations, Haseltine and Rawlings proposed a hybrid of ODE and SSA algorithm, which combines ordinary differential equations (ODEs) for traditional deterministic models and SSA for stochastic models. In this dissertation, accuracy analysis, efficient implementation strategies, and application of of Haseltine and Rawlings's hybrid method (HR) to a budding yeast cell cycle model are discussed. Accuracy of the hybrid method HR is studied based on a linear chain reaction system, motivated from the modeling practice used for the budding yeast cell cycle control mechanism. Mathematical analysis and numerical results both show that the hybrid method HR is accurate if either numbers of molecules of reactants in fast reactions are above certain thresholds, or rate constants of fast reactions are much larger than rate constants of slow reactions. Our analysis also shows that the hybrid method HR allows for a much greater region in system parameter space than those for the slow scale SSA (ssSSA) and the stochastic quasi steady state assumption (SQSSA) method. Implementation of the hybrid method HR requires a stiff ODE solver for numerical integration and an efficient event-handling strategy for slow reaction firings. In this dissertation, an event-handling strategy is developed based on inverse interpolation. Performances of five wildly used stiff ODE solvers are measured in three numerical experiments. Furthermore, inspired by the strategy of the hybrid method HR, a hybrid of ODE and SSA stochastic models for the budding yeast cell cycle is developed, based on a deterministic model in the literature. Simulation results of this hybrid model match very well with biological experimental data, and this model is the first to do so with these recently available experimental data. This study demonstrates that the hybrid method HR has great potential for stochastic modeling and simulation of large biochemical networks.
Ph. D.

Diplomová práce se zabývá problematikou obyčejných stochastických diferenciálních rovnic. Po souhrnu teorie stochastických procesů, zejména tzv. Brownova pohybu je zaveden stochastický Itôův integrál, diferenciál a tzv. Itôova formule. Poté je definováno řešení počáteční úlohy stochastické diferenciální rovnice a uvedena věta o existenci a jednoznačnosti řešení. Pro případ lineární rovnice je odvozen tvar řešení a rovnice pro jeho střední hodnotu a rozptzyl. Závěr tvoří rozbor vybraných rovnic.

COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
Neste texto estudamos diversos aspectos de singularidades de campos vetoriais holomorfos em dimensão 2. Discutimos detalhadamente o caso particular de uma singularidade sela-nó e o papel desempenhado pelas normalizações setoriais. Isto nos conduz à classificação analítica de difeomorfismos tangentes à identidade. seguir abordamos o Teorema de Seidenberg, tratando da redução de singularidades degeneradas em singularidades simples, através do procedimento de blow-up. Por fim, estudamos a demonstração do Teorema de Mattei-Moussu, acerca da existência de integrais primeiras para folheações holomorfas.
In the present text, we study the different aspects of singularities of holomorphic vector fields in dimension 2. We discuss in detail the particular case of a saddle-node singularity and the role of the sectorial normalizations. This leads us to the analytic classiffication of diffeomorphisms which are tangent to the identity. Next, we approach the Seidenberg Theorem, dealing with the reduction of degenerated singularities into simple ones, by means of the blow-up procedure. Finally, we study the proof of the well-known Mattei-Moussu Theorem concerning the existence of first integrals to holomorphic foliations.

The parameter estimation problem or the inverse problem of ordinary differential equations is prevalent in many process models in chemistry, molecular biology, control system design and many other engineering applications. It concerns the re-construction of auxillary parameters by fitting the solution from the system of ordinary differential equations( from a known mathematical model) to that of measured data obtained from observing the solution trajectory. Some of the traditional techniques (for example, initial value technques, multiple shooting, etc.) used to solve this class of problem have been discussed. A new algorithm, motivated by algorithms proposed by Childs and Osborne(1996) and Z.F.Li's dissertation(2000), has been proposed. The new algorithm inherited the advantages exhibited in the above-mentioned algorithms and, most importantly, the parameters can be transformed to a form that are convenient and suitable for computation. A statistical analysis has also been developed and applied to examples. The statistical analysis yields indications of the tolerance of the estimates and consistency of the observations used.

In this thesis, the reader will be made aware of methods for finding power series solutions to ordinary differential equations. In the case that a solution to a differential equation may not be expressed in terms of elementary functions, it is practical to obtain a solution in the form of an infinite series, since many differential equations which yield such a solution model an actual physical situation. In this thesis, we introduce conditions that guarantee existence and uniqueness of analytic solutions, both in the linear and nonlinear case. Several methods for obtaining analytic solutions are introduced as well. For the sake of pure mathematics, and particularly in the applications involving these differential equations, it is useful to find a radius of convergence for a power series solution. For these reasons, several methods for finding a radius of convergence are given. We will prove all results in this thesis.

In this work we study several topics concerning quasi-periodic time-dependent perturbations of ordinary differential equations. This kind of equations appear as models in many applied problems of Celestial Mechanics, and we have used, as an illustration, the study of the behaviour near the equilateral libration points of the real Earth-Moon system. Let us introduce this problem as a motivation. As a first approximation, suppose that the Earth and Moon arc revolving in circular orbits around their centre of masses, neglect the effect of the rest of the solar system and neglect the spherical terms coming from the Earth and Moon (of course, all the effects minor than the above mentioned) as the relativistic corrections, must be neglected). With this, we can write the equations of motion of an infinitesimal particle (by infinitesimal we mean that the particle is influenced by the Earth and Moon, but it does not affect them) by means of Newton's Jaw. The study of the motion of that particle is the so-called Restricted Three Body Problem (RTBP). Usually, in order to simplify the equations, the units of length, time and mass are chosen so that the angular velocity of rotation, the sum of masses of the bodies and the gravitational constant are all equal to one. With these normalized units, the distance between the bodies is also equal to one. If these equations of motion are written in a rotating frame leaving fixed the Earth and Moon (these main bodies are usually called primaries), it is known that the system has five equilibrium points. Two of them can be found as the third vertex of equilateral triangles having the Earth and Moon as vertices, and they are usually called equilateral libration points.

It is also known that, when the mass parameter "mi" (the mass of the small primary in the normalized units) is less than the Routh critical value "mi"(R) = 1/2(1 - square root (23/27) = 0.03852 ... (this is true in the Earth-Moon case) these points are linearly stable. Applying the KAM theorem to this case we can obtain that there exist invariant tori around these points. Now, if we restrict the motion of the particle to the plane of motion of the primaries we have that, inside each energy level, these tori split the phase space and this allows to prove that the equilateral points are stable (except for two values, "mi" = "mi"2 and "mi"= "mi"3 with low order resonances). In the spatial case, the invariant tori do not split the phase space and, due to the possible Arnold diffusion, these points can be unstable. But Arnold diffusion is a very slow phenomenon and we can have small neighbourhoods of "practical stability", that is, the particle will stay near the equilibrium point for very long time spans.

Unfortunately, the real Earth-Moon system is rather complex. In this case, due to the fact that that the motions of the Earth and the Moon are non circular (even non elliptical) and the strong influence of the Sun, the libration points do not exist as equilibrium points, and we need to define "instantaneous" libration points as the ones forming an equilateral triangle with the Earth and the Moon at each instant. If we perform some numerical integrations starting at (or near) these points we can see that the solutions go away after a short period of time, showing that these regions are unstable.

Two conclusions can be obtained from this fact. First: if we are interested in keeping a spacecraft there, we will need to use some kind of control. Second: the RTBP is not a good model for this problem} because the behaviour displayed by it is different from the one of the real system.

For these reasons, an improved model has been developed in order to study this problem. This model includes the main perturbations (due to the solar effect and to the noncircular motion of the Moon), assuming that they are quasi-periodic. This is a very good approximation for time spans of some thousands of years. It is not clear if this is true for longer time spans, but this matter will not be considered in this work. This model is in good agreement with the vector field of the solar system directly computed by means of the JPL ephemeris, for the time interval for which the JPL model is available.

The study of this kind of models is the main purpose of this work.

First of all, we have focused our attention on linear differential equations with constant coefficients, affected by a small quasi-periodic perturbation. These equations appear as variational equations along a quasi-periodic solution of a general equation and they also serve as an introduction to nonlinear problems.

The purpose is to reduce those systems to constant coefficients ones by means of a quasi-periodic change of variables, as the classical Floquet theorem does for periodic systems. It is also interesting to nave a way to compute this constant matrix, as well as the change of variables. The most interesting case occurs when the unperturbed system is of elliptic type. Other cases, as the hyperbolic one, have already been studied. We have added a parameter ("epsilon") in the system, multiplying the perturbation, such that if "epsilon" is equal to zero we recover the unperturbed system. In this case we have found that, under suitable hypothesis of non-resonance, analyticity and non-degeneracy with respect to "epsilon", it is possible to reduce the system to constant coefficients, for a cantorian set of values of "epsilon". Moreover, the proof is constructive in an iterative way. This means that it is possible to find approximations to the reduced matrix as well as to the change of variables that performs such reduction. These results are given in Chapter 1.

The nonlinear case is now going to be studied. We have then considered an elliptic equilibrium point of an autonomous ordinary differential equation, and we have added a small quasi-periodic perturbation, in such a way that the equilibrium point does not longer exist. As in the linear case, we have put a parameter ("epsilon") multiplying the perturbation. There is some "practical" evidence that there exists a quasi-periodic orbit, having the same basic frequencies that the perturbation, such that, when the perturbation goes to zero, this orbit goes to the equilibrium point. Our results show that, under suitable hypothesis, this orbit exists for a cantorian set of values of "epsilon". We have also found some results related to the stability of this orbit. These results are given in Chapter 2.

A remarkable case occurs when the system is Hamiltonian. Here it is interesting to know what happens to the invariant tori near these points when the perturbation is added. Note that the KAM theorem can not be applied directly due to the fact that the Hamiltonian is degenerated, in the sense that it has some frequencies (the ones of the perturbation) that have fixed values and they do not depend on actions in a diffeomorphic way. In this case, we have found that some tori still exist in the perturbed system. These tori come from the ones of the unperturbed system whose frequencies are non-resonant with those of the perturbation. The perturbed tori add these perturbing frequencies to the ones they already had. This can be described saying that the unperturbed tori are "quasi-periodically dancing" under the "rhythm" of the perturbation. These results can also be found in Chapter 2 and Appendix C.

The final point of this work has been to perform a study of the behaviour near the instantaneous equilateral libration points of the real Earth-Moon system. The purpose of those computations has been to find a way of keeping a spacecraft near these points in an unexpensive way. As it has been mentioned above in the real system these points are not equilibrium points, and their neighbourhood displays unstability. This leads us to use some control to keep the spacecraft there. It would be useful to have an orbit that was always near these points, because the spacecraft could be placed on it. Thus, only a station keeping would be necessary. The simplest orbit of this kind that we can compute is the one that replaces the equilibrium point. In Chapter 3, this computation has been carried out first for a planar simplified model and then for a spatial model. Then, the solution found for this last model has been improved, by means of numerical methods, in order to have a real orbit of the real system (here, by real system we mean the model of solar system provided by the JPL tapes). This improvement has been performed for a given (fixed) time-span. That is sufficient for practical purposes. Finally, an approximation to the linear stability of this refined orbit has been computed, and a very mild unstability has been found, allowing for an unexpensive station keeping. These results are given in Chapter 3 and Appendix A.

Finally, in Appendix B the reader can find the technical details concerning the way of obtaining the models used to study the neighbourhood of the equilateral points. This has been jointly developed with Gerard Gomez, Jaume Llibre, Regina Martinez, Josep Masdemont and Carles Simó.

We study several topics concerning quasi-periodic time-dependent perturbations of ordinary differential equations. This kind of equations appear in many applied problems of Celestial Mechanics, and we have used, as an illustration, the study of the behaviour near the Lagrangian points of the real Earth-Moon system. For this purpose, a model has been developed. It includes the main perturbations (due to the Sun and Moon), assuming that they are quasi-periodic.

Firstly, we deal with linear differential equations with constant coefficients, affected by a small quasi-periodic perturbation, trying to reduce then: to constant coefficients by means of a quasi-periodic change of variables. The most interesting case occurs when the unperturbed system is of elliptic type. We have added a parameter "epsilon" in the system, multiplying the perturbation, such that if "epsilon" is equal to zero we recover the unperturbed system. In this case, under suitable hypothesis of non-resonance, analyicity and non degeneracy with respect to "epsilon", it is possible to reduce the system to constant coefficients, for a cantorian set of values of "epsilon".

In the nonlinear case, we have considered an elliptic equilibrium point of an autonomous differential equation, and we have added a small quasi-periodic perturbation, in such a way that the equilibrium point does not exist. As in the linear case, we have put a parameter ("epsilon") multiplying the perturbation. Then, for a cantorian set of "epsilon", there exists a quasi-periodic orbit having the same basic frequencies as the perturbation, going to the equilibrium point when t: goes to zero. Some results concerning the stability of this orbit are stated. When the system is Hamiltonian, we have found that some tori still exist in the perturbed system. These tori come from the ones of the unperturbed system whose frequencies are non-resonant with those of the perturbation, adding these perturbing frequencies to the ones they already had.

Finally, a study of the behaviour near the Lagrangian points of the real Earth-Moon system is presented. The purpose has been to find the orbit replacing the equilibrium point. This computation has been carried out first for the model mentioned above and then it has been improved numerically, in order to have a real orbit of the real system. Finally, a study of the linear stability of this refined orbit has been done.

In case of the PDE's the concept of solving by separation of variables

has a well defined meaning. One seeks a solution in a form of a

product or sum and tries to build the general solution out of these

particular solutions. There are also known systems of second order

ODE's describing potential motions and certain rigid bodies that are

considered to be separable. However, in those cases, the concept of

separation of variables is more elusive; no general definition is

given.

In this thesis we study how these systems of equations separate and find that their separation usually can be reduced to sequential separation of single first order ODE´s. However, it appears that other mechanisms of separability are possible.

We study the non-autonomous ordinary differential equation x = f (t, x) in the situation when the vector field f is of limited regularity, typically belonging to a space LP (O,T; Lq (JRn)). Such equations arise naturally when switching from an Eulerian to a Lagrangian viewpoint for the solutions of partial differential equations. We discuss some measurability issues in the foundations of the theory of regular Lagrangian flow solutions. Further, we examine the sensitivity of the choice of representative vector field f on solutions of the ordinary differential equation and, in particular, we demonstrate that every vector field can be altered on a set of measure zero to introduce non-uniqueness of solutions. We develop some geometric tools to quantify the behaviour of solutions, notably a non-autonomous version of subset avoidance and the r-codimension print that encodes the dimension of a subset S c JRn x [0, T] while distinguishing between the spatial and temporal detail of S. We relate this notion of dimension to the more familiar box-counting dimensions, for which we prove some new inequalities. Finally, motivated by the issues with measurability that can arise with irregular vector fields we prove some fundamental results in the theory of Bochner integration in order to be able to manipulate the representatives of the equivalence classes in LP (O,T; Lq (JRn)).

In this work we present some new results concerning stochastic partial differential and integro-differential equations (SPDEs and SPIDEs) that appear in non-linear filtering. We prove existence and uniqueness of solutions of SPIDEs, we give a comparison principle and we suggest an approximation scheme for the non-local integral operators. Regarding SPDEs, we use techniques motivated by the work of De Giorgi, Nash, and Moser, in order to derive global and local supremum estimates, and a weak Harnack inequality.

In this thesis we study the existence of stationary solutions for stochastic partial differential equations. We establish a new connection between solutions of backward doubly stochastic differential equations (BDSDEs) on infinite horizon and the stationary solutions of the SPDEs. For this, we prove the existence and uniqueness of the L2ρ (Rd; R1) × L2ρ (Rd; Rd) valued solutions of BDSDEs with Lipschitz nonlinear term on both finite and infinite horizons, so obtain the solutions of initial value problems and the stationary weak solutions (independent of any initial value) of SPDEs. Also the L2ρ (Rd; R1) × L2ρ (Rd; Rd) valued BDSDE with non-Lipschitz term is considered. Moreover, we verify the time and space continuity of solutions of real-valued BDSDEs, so obtain the stationary stochastic viscosity solutions of real-valued SPDEs. The connection of the weak solutions of SPDEs and BDSDEs has independent interests in the areas of both SPDEs and BSDEs.

This thesis involves the implementation of spectral methods, for numerical solution of linear Ordinary Differential Equations (ODEs) and linear Differential-Algebraic Equations (DAEs). First we consider ODEs with some ordinary problems, and then, focus on those problems in which the solution function or some coefficient functions have singularities. Then, by expressing weak and strong aspects of spectral methods to solve these kinds of problems, a modified pseudospectral method which is more efficient than other spectral methods is suggested and tested on some examples. We extend the pseudo-spectral method to solve a system of linear ODEs and linear DAEs and compare this method with other methods such as Backward Difference Formulae (BDF), and implicit Runge-Kutta (RK) methods using some numerical examples. Furthermore, by using appropriatec hoice of Gauss-Chebyshev-Radapuo ints, we will show that this method can be used to solve a linear DAE whenever some of coefficient functions have singularities by providing some examples. We also used some problems that have already been considered by some authors by finite difference methods, and compare their results with ours. Finally, we present a short survey of properties and numerical methods for solving DAE problems and then we extend the pseudo-spectral method to solve DAE problems with variable coefficient functions. Our numerical experience shows that spectral and pseudo-spectral methods and their modified versions are very promising for linear ODE and linear DAE problems with solution or coefficient functions having singularities. In section 3.2, a modified method for solving an ODE is introduced which is new work. Furthermore, an extension of this method for solving a DAE or system of ODEs which has been explained in section 4.6 of chapter four is also a new idea and has not been done by anyone previously. In all chapters, wherever we talk about ODE or DAE we mean linear.

El objetivo de esta tesis doctoral es desarrollar nuevos métodos basados en splines para la resolución de sistemas de ecuaciones diferenciales del tipo Y'(x)=f(x,Y(x)) , aTung, MM. (2013). Spline approximations for systems of ordinary differential equations [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/31658
TESIS
Premiado

Cette thèse est relative aux Equations Différentielles Stochastique Rétrogrades (EDSRs) réfléchies avec deux obstacles et leurs applications aux jeux de switching de somme nulle, aux systèmes d’équations aux dérivées partielles, aux problèmes de mean-field. Il y a deux parties dans cette thèse. La première partie porte sur le switching optimal stochastique et est composée de deux travaux. Dans le premier travail, nous montrons l’existence de la solution d’un système d’EDSR réfléchies à obstacles bilatéraux interconnectés dans le cadre probabiliste général. Ce problème est lié à un jeu de switching de somme nulle. Ensuite nous abordons la question de l’unicité de la solution. Et enfin nous appliquons les résultats obtenus pour montrer que le système d’EDP associé à une unique solution au sens viscosité, sans la condition de monotonie habituelle. Dans le second travail, nous considérons aussi un système d’EDSRs réfléchies à obstacles bilatéraux interconnectés dans le cadre markovien. La différence avec le premier travail réside dans le fait que le switching ne s’opère pas de la même manière. Cette fois-ci quand le switching est opéré, le système est mis dans l’état suivant importe peu lequel des joueurs décide de switcher. Cette différence est fondamentale et complique singulièrement le problème de l’existence de la solution du système. Néanmoins, dans le cadre markovien nous montrons cette existence et donnons un résultat d’unicité en utilisant principalement la méthode de Perron. Ensuite, le lien avec un jeu de switching spécifique est établi dans deux cadres. Dans la seconde partie nous étudions les EDSR réfléchies unidimensionnelles à deux obstacles de type mean-field. Par la méthode du point fixe, nous montrons l’existence et l’unicité de la solution dans deux cadres, en fonction de l’intégrabilité des données
This thesis is related to Doubly Reflected Backward Stochastic Differential Equations (DRBSDEs) with two obstacles and their applications in zero-sum stochastic switching games, systems of partial differential equations, mean-field problems.There are two parts in this thesis. The first part deals with optimal stochastic switching and is composed of two works. In the first work we prove the existence of the solution of a system of DRBSDEs with bilateral interconnected obstacles in a probabilistic framework. This problem is related to a zero-sum switching game. Then we tackle the problem of the uniqueness of the solution. Finally, we apply the obtained results and prove that, without the usual monotonicity condition, the associated PDE system has a unique solution in viscosity sense. In the second work, we also consider a system of DRBSDEs with bilateral interconnected obstacles in the markovian framework. The difference between this work and the first one lies in the fact that switching does not work in the same way. In this second framework, when switching is operated, the system is put in the following state regardless of which player decides to switch. This difference is fundamental and largely complicates the problem of the existence of the solution of the system. Nevertheless, in the Markovian framework we show this existence and give a uniqueness result by the Perron’s method. Later on, two particular switching games are analyzed.In the second part we study a one-dimensional Reflected BSDE with two obstacles of mean-field type. By the fixed point method, we show the existence and uniqueness of the solution in connection with the integrality of the data

In under 6 decades dengue has emerged from South East Asia to become the most widespread arbovirus affecting human populations. Recent dramatic increases in epidemic dengue fever have mainly been attributed to factors such as vector expansion and ongoing ecological, climate and socio-demographic changes. The failure to control the virus in endemic regions and prevent global spread of its mosquito vectors and genetic variants, underlines the urgency to reassess previous research methods, hypotheses and empirical observations. This thesis comprises a set of studies that integrate currently neglected and emerging epidemiological, ecological and evolutionary factors into unified mathematical frameworks, in order to better understand the contemporary population biology of the dengue virus. The observed epidemiological dynamics of dengue are believed to be driven by selective forces emerging from within-host cross-immune reactions during sequential, heterologous infections. However, this hypothesis is mainly supported by modelling approaches that presume all hosts to contribute equally and significantly to the selective effects of cross-immunity both in time and space. In the research presented in this thesis it is shown that the previously proposed effects of cross-immunological reactions are weakened in agent-based modelling approaches, which relax the common deterministic and homogeneous mixing assumptions in host-host and host-pathogen interactions. Crucially, it is shown that within these more detailed models, previously reported universal signatures of dengue's epidemiology and population genetics can be reproduced by demographic and natural stochastic processes alone. While this contrasts with the proposed role of cross-immunity, it presents demographic stochasticity as a parsimonious mechanism that integrates, for the first time, multi-scale features of dengue's population biology. The implications of this research are applicable to many other pathogens, involving challenging new ways of determining the underlying causes of the complex phylodynamics of antigenically diverse pathogens.

In this thesis, we address several problems arising in the study of nondegenerate and degenerate parabolic SPDEs, stochastic hyperbolic conservation laws and SDEs with continues coefficients. In the first part, we are interested in degenerate parabolic SPDEs, adapt the notion of kinetic formulation and kinetic solution and establish existence, uniqueness as well as continuous dependence on initial data. As a preliminary result we obtain regularity of solutions in the nondegenerate case under the hypothesis that all the coefficients are sufficiently smooth and have bounded derivatives. In the second part, we consider hyperbolic conservation laws with stochastic forcing and study their approximations in the sense of Bhatnagar-Gross-Krook. In particular, we describe the conservation laws as a hydrodynamic limit of the stochastic BGK model as the microscopic scale vanishes. In the last part, we provide a new and fairly elementary proof of Skorkhod's classical theorem on existence of weak solutions to SDEs with continuous coefficients satisfying a suitable Lyapunov condition.

We define a new numerical integration scheme for stochastic differential equations driven by Levy processes with uniformly lower mean square remainder than that of the scheme of the same strong order of convergence obtained by truncating the stochastic Taylor series. In doing so we generalize recent results concerning stochastic differential equations driven by Wiener processes. The aforementioned works studied integration schemes obtained by applying an invertible mapping to the stochastic Taylor series, truncating the resulting series and applying the inverse of the original mapping. The shuffle Hopf algebra and its associated convolution algebra play important roles in the their analysis, arising from the combinatorial structure of iterated Stratonovich integrals. It was recently shown that the algebra generated by iterated It^o integrals of independent Levy processes is isomorphic to a quasi-shuffle algebra. We utilise this to consider map-truncate-invert schemes for Levy processes. To facilitate this, we derive a new form of stochastic Taylor expansion from those of Wagner & Platen, enabling us to extend existing algebraic encodings of integration schemes. We then derive an alternative method of computing map-truncate-invert schemes using a single step, resolving diffculties encountered at the inversion step in previous methods.

We will explore the topic of stochastic differential equations (SDEs) first by developing a foundation in probability theory and It\^o calculus. Formulas are then derived to simulate these equations analytically as well as numerically. These formulas are then applied to a basic population model as well as a logistic model and the various methods are compared. Finally, we will study a model for low dose anthrax exposure which currently implements a stochastic probabilistic uptake in a deterministic differential equation, and analyze how replacing the probablistic uptake with an SDE alters the dynamics.

The general truth that the principle of causality, that is, the future state of a system is independent of its past history, cannot support all the cases under consideration, leads to the introduction of the FDEs. However, the strong need of modelling real life problems, demands the inclusion of stochasticity. Thus, the appearance of the SFDEs (special case of which is the SDDEs) is necessary and definitely unavoidable. It has been almost a century since Langevin's model that the researchers incorporate noise terms into their work. Two of the main research interests are linked with the existence and uniqueness of the solution of the pertinent SFDE/SDDE which describes the problem under consideration, and the qualitative behaviour of the solution. This thesis, explores the SFDEs and their applications. According to the scientific literature, Ito's work (1940) contributed fundamentally into the formulation and study of the SFDEs. Khasminskii (1969), introduced a powerful test for SDEs to have non-explosion solutions without the satisfaction of the linear growth condition. Mao (2002), extended the idea so as to approach the SDDEs. However, Mao's test cannot be applied in specific types of SDDEs. Through our research work we establish an even more general Khasminskii-type test for SDDEs which covers a wide class of highly non-linear SDDEs. Following the proof of the non-explosion of the pertinent solution, we focus onto studying its qualitative behaviour by computing some moment and almost sure asymptotic estimations. In an attempt to apply and extend our theoretical results into real life problems we devote a big part of our research work into studying two very interesting problems that arise : from the area of the population dynamks and from·a problem related to the physical phenomenon of ENSO (EI Nino - Southern Oscillation)

Le travail de thèse est composé de trois thèmes principaux : le premier étudie l'existence et l'unicité pour des équations différentielles stochastiques (EDS) progressives-rétrogrades fortement couplées avec des opérateurs sous-différentiels dans les deux équations, dans l’équation progressive ainsi que l’équation rétrograde, et il discute également un nouveau type des inégalités variationnelles partielles paraboliques associées, avec deux opérateurs sous-différentiels, l’un agissant sur le domaine de l’état, l’autre sur le co-domaine. Le second thème est celui des EDS rétrogrades sans ainsi qu’avec opérateurs sous-différentiels, régies par un mouvement brownien fractionnaire avec paramètre de Hurst H> ½. Il étend de manière rigoureuse les résultats de Hu et Peng (SICON, 2009) aux inégalités variationnelles stochastiques rétrogrades. Enfin, le troisième thème met l’accent sur la caractérisation déterministe de la viabilité pour les EDS régies par un mouvement brownien fractionnaire. Ces trois thèmes de recherche mentionnés ci-dessus ont en commun d’étudier des EDS avec contraintes sur le processus d’état. Chacun des trois sujets est basé sur une publication et des manuscrits soumis pour publication, respectivement
This PhD thesis is composed of three main topics: The first one studies the existence and the uniqueness for fully coupled forward-backward stochastic differential equations (SDEs) with subdifferential operators in both the forward and the backward equations, and it discusses also a new type of associated parabolic partial variational inequalities with two subdifferential operators, one acting over the state domain and the other over the co-domain. The second topic concerns the investigation of backward SDEs without as well as with subdifferential operator, both driven by a fractional Brownian motion with Hurst parameter H> 1/2. It extends in a rigorous manner the results of Hu and Peng (SICON, 2009) to backward stochastic variational inequalities. Finally, the third topic focuses on a deterministic characterisation of the viability for SDEs driven by a fractional Brownian motion. The three research topics mentioned above have in common to study SDEs with state constraints. The discussion of each of the three topics is based on a publication and on submitted manuscripts, respectively

The Santillan-Mackey model of the tryptophan operon was developed to characterize the anthranilate synthase activity in cultures of Escherichia coli. Similarly, the GABA reaction scheme was formulated to characterize the response of the GABAA receptor at a synapse, and the Hodgkin-Huxley model was developed to characterize the action potential of a squid giant axon. While the Hodgkin-Huxley model has been studied in great detail from a mathematical vantage, much less is known about the preceding two models in this regard. This work examines the stiffness of all three models; a novel perspective for both the Santillan-Mackey model and the GABA reaction. The characterization of the stiffness in these problems gives theoretical biologists insight into the dynamics of the reactions. It also enables them to select more computationally efficient methods for numerical simulations. The discovery of invariant manifolds in the Santillan-Mackey model and the GABA reaction in this work present experimentalists with concrete assays, against which the models can be tested.

A central objective of current systems biology research is explaining the interactions amongst components in biopathways. A standard approach is to view a biopathway as a network of biochemical reactions, which is modelled as a system of ordinary differential equations (ODEs). Conventional inference methods typically rely on searching the space of parameter values, and at each candidate, numerically solving the ODEs and comparing the output with that observed. After choosing an appropriate noise model, the form of the likelihood is defined, and a measure of similarity between the data signals and the signals described by the current set of ODE parameters can be calculated. This process is repeated, as part of either an iterative optimisation scheme or sampling procedure in order to estimate the parameters. However, the computational costs involved with repeatedly numerically solving the ODEs are usually high. Several authors have adopted approaches based on gradient matching, aiming to reduce this computational complexity. These approaches are based on the following two-step procedure. At the first step, interpolation is used to smooth the time series data, in order to avoid modelling noisy observations; in a second step, the kinetic parameters of the ODEs are either optimised or sampled, whilst minimising some metric measuring the difference between the slopes of the tangents to the interpolants, and the parameter-dependent time derivative from the ODEs. In this fashion, the ODEs never have to be numerically integrated, and the problem of inferring the typically unknown initial conditions of the system is removed, as it is not required for matching gradients. A downside to this two-step scheme is that the results of parameter inference are critically dependent on the quality of the initial interpolant. Alternatively, the ODEs can be allowed to regularise the interpolant and it has been demonstrated that it significantly improves the parameter inference accuracy and robustness with respect to noise. This thesis extends and develops methods of gradient matching for parameter inference and model selection in ODE systems in a systems biology context.

The asymptotic behaviour of nonoscillatory solutions of second order nonlinear ordinary differential equations is studied. Necessary and sufficient conditions are given for the existence of positive solutions with specified asymptotic behaviour at infinity. Existence of nonoscillatory solutions is established using the Schauder-Tychonoff fixed point theorem. Techniques such as factorization of linear disconjugate operators are employed to reveal the similar nature of asymptotic solutions of nonlinear differential equations to that of linear equations. Some examples illustrating the asymptotic theory of ordinary differential equations are given.
Science, Faculty of
Mathematics, Department of
Graduate

This thesis is concerned with methodologies for the accurate quantitative modelling of molecular biological systems. The first part is devoted to the chemical Langevin equation (CLE), a stochastic differential equation driven by a multidimensional Wiener process. The CLE is an approximation to the standard discrete Markov jump process model of chemical reaction kinetics. It is valid in the regime where molecular populations are abundant enough to assume their concentrations change continuously, but stochastic fluctuations still play a major role. We observe that the CLE is not a single equation, but a family of equations with shared finite-dimensional distributions. On the theoretical side, we prove that as many Wiener processes are sufficient to formulate the CLE as there are independent variables in the equation, which is just the rank of the stoichiometric matrix. On the practical side, we show that in the case where there are m_1 pairs of reversible reactions and m_2 irreversible reactions, there is another, simple formulation of the CLE with only m_1+m_2 Wiener processes, whereas the standard approach uses 2m_1+m_2. Considerable computational savings are achieved with this latter formulation. A flaw of the CLE model is identified: trajectories may leave the nonnegative orthant with positive probability. The second part addresses the challenge when alternative, structurally different ordinary differential equation models of similar complexity fit the available experimental data equally well. We review optimal experiment design methods for choosing the initial state and structural changes on the biological system to maximally discriminate between the outputs of rival models in terms of L_2-distance. We determine the optimal stimulus (input) profile for externally excitable systems. The numerical implementation relies on sum of squares decompositions and is demonstrated on two rival models of signal processing in starving Dictyostelium amoebae. Such experiments accelerate the perfection of our understanding of biochemical mechanisms.

A stochastic differential equationdriven by a Brownian motion where the dispersion is determined by a parameter is considered. The parameter undergoes a change at a certain time point. Estimates of the time change point and the parameter, before and after that time, is considered.The estimates were presented in Lacus 2008. Two cases are considered: (1) the drift is known, (2) the drift is unknown and the dispersion space-independent. Applications to Dow-Jones index 1971-1974  and Goldmann-Sachs closings 2005-- May 2009 are given.