Orientador: Francisco Odair Vieira de Paiva, Aloisio Freiria Neves / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica / Made available in DSpace on 2018-08-08T02:49:07Z (GMT). No. of bitstreams: 1 Malavazi_MazilioCoronel_M.pdf: 786706 bytes, checksum: 9e4d9aae3bd0fdd46d7adf64ce8958ef (MD5) Previous issue date: 2007 / Resumo: Nesta dissertação obtemos resultados de multiplicidade de soluções fracas não triviais para o problema -Du + V (x)u = f (x; u); x 2 RN; onde V é contínua, f é C1, com f (x; 0) = 0 e f é assintoticamente linear. Utilizamos métodos variacionais e a teoria de grupos críticos, para obtermos e distinguirmos as soluções. Apresentamos também resultados de existência de solução não trivial para o problema -Du + V (x)u = f (u); x 2 RN; onde V e f são funções contínuas. Utilizamos as técnicas de concentração de compacidade e de aproximação do domínio por subconjuntos limitados, para obtermos a solução / Abstract: In this dissertation we get resulted of multiplicity of not trivial weak solutions for the problem -Du + V (x)u = f (x; u); x 2 RN; where V is continuous, f is C1, with f (x; 0) = 0 and f is asymptotically linear. We use variationals methods and the theory of critical groups, to get and to distinguish the solutions. We also present results of existence of not trivial solution for the problem -Du + V (x)u = f (u); x 2 RN; where V and f are continuous functions. We use the techniques of concentration of compactness and approximation of the domain for bounded subsets, to get the solution / Mestrado / Mestre em Matemática

Orientador: Pedro Jose Catuogno / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatística e Computação Cientifica / Made available in DSpace on 2018-08-14T14:39:55Z (GMT). No. of bitstreams: 1 Castrequini_RafaelAndretto_M.pdf: 934326 bytes, checksum: e4c45bc1efde09bbe52710c44eab8bbf (MD5) Previous issue date: 2009 / Resumo: Introduzimos a teoria dos p-rough paths seguindo a abordagem de M. Gubinelli, conhecida por integração algébrica. Durante toda a dissertação nos restringimos ao caso 1 </= p < 3, o que e suficiente para lidar com trajetórias do movimento Browniano e aplicações ao Cálculo Estocástico. Em seguida, estudamos as equações diferenciais associadas aos rough paths, onde nós conectamos a abordagem de A. M. Davie (as equações) e a abordagem de M. Gubinelli (as integrais). No final da dissertação, aplicamos a teoria de rough path ao cálculo estocástico, mais precisamente relacionando as integrais de Itô e Stratonovich com a integral ao longo de caminhos. / Abstract: We introduce p-Rough Path Theory following M. Gubinelli_s approach, as known as algebraic integration. Throughout this masters thesis, we are concerned only in the case where 1 </= p < 3, witch is enough to deal with trajectories of a Brownnian motion and some applications to Stochastic Calculus. Afterwards, we study differential equations related to rough paths, where we connect the approach of A. M. Davie to equations with the approach of M. Gubinelli to integrals. At the end of this work, we apply the theory of rough paths to stochastic calculus, more precisely, we related the integrals of Itô and Stratonovich to integral along paths. / Mestrado / Sistemas estocasticos / Mestre em Matemática

A Teoria das equações integrais, desde a segunda metade do século XX, tem assumido um papel cada vez maior no âmbito de problemas aplicados. Com isso, surge a necessidade do desenvolvimento de métodos numéricos cada vez mais eficazes para a resolução deste tipo de equação. Isso tem como consequência a possibilidade de resolução de uma gama cada vez maior de problemas. Nesse sentido, outros tipos de equações integrais estão sendo objeto de estudos, dentre elas as chamadas equações integro-diferenciais. O presente trabalho tem como objetivo o estudo das equações integro-diferenciais singulares lineares e não-lineares. Mais especificamente, no caso linear, apresentamos os principais resultados necessários para a obtenção de um método numérico e a formulação de suas propriedades de convergência. O caso não-linear é apresentado através de um modelo matemático para tubulações em um tipo específico de reator nuclear (LMFBR) no qual origina-se a equação integro-diferencial. A partir da equação integro-diferencial um modelo numérico é proposto com base nas condições físicas do problema / The theory of the integral equations, since the second half of the 20th century, has been assuming an ever more important role in the modelling of applied problems. Consequently, the development of new numerical methods for integral equations is called for and a larger range of problems has been possible to be solved by these new techniques. In this sense, many types of integral equations have been derived from applications and been the object of studies, among them the so called singular integro-differential equation. The present work has, as its main objective, the study of singular integrodifferential equations, both linear and non-linear. More specifically, in the linear case, we present our main results regarding the derivation of a numerical method and its uniform convergence properties. The non-linear case is introduced through the mathematical model of boiler tubes in a specific type of nuclear reactor (LMFBR) from which the integro-differential equation originates. For this integro-differential equation a numerical method is proposed based on the physical conditions of the problem

Tato diplomová práce se zabývá numerickými metodami pro řešení počátečních problémů zlomkových diferenciálních rovnic s Caputovou derivací. Jsou uvedeny dva numerické přístupy spolu s přehledem základních aproximačních formulí. Dvě verze Eulerovy metody jsou realizovány v Matlabu a porovnány na základě numerických experimentů.

Im Folgenden wird die analytische Lösung der eindimensionalen, instationären Wärmeleitungsgleichung mit einer Randbedingung 3. Art gegeben. Die Außentemperatur wird dabei als harmonische Schwingung angenommen. Abhängig von den materialspezifischen Eigenschaften des Bauteils (Wärmeleitfähigkeit, Rohdichte, spezifische Wärmekapazität) kommt es zur Dämpfung und zeitlichen Verschiebung der Temperaturwelle im Bauteil. Die analytische Lösung liefert den raum- und zeitaufgelösten Temperaturverlauf innerhalb des Bauteils. Die analytische Lösung ist primär für die Kalibrierung und Validierung numerischer Approximationsverfahren relevant. Die zeitliche Verfügbarkeit von thermischer Speichermasse ist für die thermische Gebäude- und Raumsimulation von besonderer Wichtigkeit. Daher muss ein numerisches Berechnungsverfahren diese Prozesse gut abbilden können. Die hier gezeigte analytische Lösung kann daher zur Bewertung der Güte der gewählten numerischen Approximation verwendet werden. Zu diesem Zweck werden Ergebnisse beispielhaft für zwei getrennte Konstruktionen angegeben.

In this paper, we discuss methods for developing a stochastic model which incorporates behavior differences in the predation movements of Anelosimus studiosus (a subsocial spider). Stochastic models for animal movement and, in particular, spider predation movement have been developed previously; however, this paper focuses on the development and implementation of the necessary mathematical and statistical methods required to expand such a model in order to capture a variety of distinct behaviors. A least squares optimization algorithm is used for parameter estimation to fit a single stochastic model to an individual spider during predation resulting in unique parameter values for each spider. Similarities and variations between parameter values across the spiders are analyzed and used to estimate probability distributions for the variable parameter values. An aggregate stochastic model is then created which incorporates the individual dynamics. The comparison between the optimal individual models to the aggregate model indicate the methodology and algorithm developed in this paper are appropriate for simulating a range of individualistic behaviors.

In this paper, we develop a stochastic differential equation model to simulate the movement of a social/subsocial spider species, Anelosimus studiosus, during prey capture using experimental data collected in a structured environment. In a subsocial species, females and their maturing offspring share a web and cooperate in web maintenance and prey capture. Furthermore, observations indicate these colonies change their positioning throughout the day, clustered during certain times of the day while spaced out at other times. One key question was whether or not the spiders spaced out "optimally" to cooperate in prey capture. In this paper, we first show the derivation of the model where experimental data is used to determine key parameters within the model. We then use this model to test the success of prey capture under a variety of different spatial configurations for varying colony sizes to determine the best spatial configuration for prey capture.

Cette thèse porte sur l'étude des dynamiques spatiales et évolutives d'une population à l'aide d'outils probabilistes et déterministes. Dans la première partie, nous cherchons à comprendre l'effet de l'hétérogénéité de l'environnement sur l'évolution des espèces. La population considérée est modélisée par un processus individu-centré avec interactions qui décrit les événements de naissances, morts, mutations et diffusions spatiales de chaque individu. Les taux des événements dépendent des caractéristiques des individus : traits phénotypes et positions spatiales. Dans un premier temps, nous étudions le système d'équations aux dérivées partielles qui décrit la dynamique spatiale et démographique d'une population composée de deux traits dans une limite grande population. Nous caractérisons précisément les conditions d'extinction et de survie en temps long de cette population. Dans un deuxième temps, nous étudions le modèle individuel initial sous deux asymptotiques : grande population et mutations rares de telle sorte que les échelles de temps démographiques et mutationnelles sont séparées. Ainsi, lorsqu'un mutant apparaît, la population résidente est à l'équilibre démographique. Nous cherchons alors à caractériser la probabilité de survie de la population issue de ce mutant. Puis, en étudiantle processus dans l'échelle des mutations, nous prouvons que le processus individu-centré converge vers un processus de sauts qui décrit les fixations successives des traits les plus avantagés ainsi que la répartition spatiale des populations portant ces traits. Nous généralisons ensuite le modèle pour introduire des interactions de type mutualiste entre deux espèces. Nous étudions ce modèle dans une limite de grande population. Nous donnons par ailleurs des résultats numériques et une analyse biologique détaillée des comportements obtenus autour de deux problématiques : la coévolution de niches spatiales et phénotypiques d'espèces en interaction mutualiste et les dynamiques d'invasions d'un espace homogène par des espèces mutualistes. Dans la deuxième partie de cette thèse, nous développons un modèle probabiliste pour étudier finement l'effet d'une préférence sexuelle sur la spéciation. La population est ici structurée sur deux patchs et les individus, caractérisés par un trait, sont écologiquement et démographiquement équivalents et se distinguent uniquement par leur préférence sexuelle: deux individus de même trait ont plus de chance de se reproduire que deux individus de traits distincts. Nous montrons qu'en l'absence de toute autre différence écologique, la préférence sexuelle mène à un isolement reproductif entre les deux patchs. / We study the spatial and evolutionary dynamics of a population by using probabilistic and deterministic tools. In the first part of this thesis, we are concerned with the influence of a heterogeneous environment on the evolution of species. The population is modeled by an individual-based process with some interactions and which describes the birth, the death, the mutation and the spatial diffusion of each individual. The rates of those events depend on the characteristics of the individuals : their phenotypic trait and their spatial location. First, we study the system of partial differential equations that describes the spatial and demographic dynamics of a population composed of two traits in a large population limit. We characterize precisely the conditions of extinction and long time survival for this population. Secondly, we study the initial individual-based model under two asymptotic: large population and rare mutations such as demographic and mutational timescales are separated. Thus, when a mutant appears, the resident population has reached its demographic balance. We characterize the survival probability of the population descended from this mutant. Then, by studyingthe process in the mutational scale, we prove that the microscopic process converges to a jump process which describes the successive fixations of the most advantaged traits and the spatial distribution of populations carrying these traits. We then extend the model to introduce mutualistic interactions between two species. We study this model in a limit of large population. We also give numerical results and a detailed biological behavior analysis around two issues: the co-evolution of phenotypic and spatial niches of mutualistic species and the invasion dynamics of a homogeneous space by these species. In the second part of this thesis, we develop a probabilistic model to study the effect of the sexual preference on the speciation. Here, the population is structured on two patches and the individuals, characterized by a trait, are ecologically and demographically similar and differ only in their sexual preferences: two individuals of the same trait are more likely to reproduce than two individuals of distinct traits. We show that in the absence of any other ecological differences, the sexual preferences lead to reproductive isolation between the two patches.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第21212号 / 情博第665号 / 新制||情||115(附属図書館) / 京都大学大学院情報学研究科先端数理科学専攻 / (主査)教授 磯 祐介, 教授 木上 淳, 助手 藤原 宏志 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Performing detailed simulations of plasma kinetic diffusion is a challenging task and currently requires the largest computational facilities in the world. The reason for this is that, the physics in a confined heated plasma occur on a broad range of temporal and spatial scales. It is therefore of interest to improve the computational algorithms together with the development of more powerful computational resources. Kinetic diffusion processes in plasmas are commonly simulated with the Monte Carlo method, where a discrete set of particles are sampled from a distribution function and advanced in a Lagrangian frame according to a set of stochastic differential equations. The Monte Carlo method introduces computational error in the form of statistical random noise produced by a finite number of particles (or markers) N and the error scales as αN−β where β = 1/2 for the standard Monte Carlo method. This requires a large number of simulated particles in order to obtain a sufficiently low numerical noise level. Therefore it is essential to use techniques that reduce the numerical noise. Such methods are commonly called variance reduction methods. In this thesis, we have developed new variance reduction methods with application to plasma kinetic diffusion. The methods are suitable for simulation of RF-heating and transport, but are not limited to these types of problems. We have derived a novel variance reduction method that minimizes the number of required particles from an optimization model. This implicitly reduces the variance when calculating the expected value of the distribution, since for a fixed error the  optimization model ensures that a minimal number of particles are needed. Techniques that reduce the noise by improving the order of convergence, have also been considered. Two different methods have been tested on a neutral beam injection scenario. The methods are the scrambled Brownian bridge method and a method here called the sorting and mixing method of L´ecot and Khettabi[1999]. Both methods converge faster than the standard Monte Carlo method for modest number of time steps, but fail to converge correctly for large number of time steps, a range required for detailed plasma kinetic simulations. Different techniques are discussed that have the potential of improving the convergence to this range of time steps. / QC 20120314