We introduce renormalized integrals which generalize conventional measure theoretic integrals. One approximates the integration domain by measure spaces and defines the integral as the limit of integrals over the approximating spaces. This concept is implicitly present in many mathematical contexts such as Cauchy's principal value, the determinant of operators on a Hilbert space and the Fourier transform of an L^p function. We use renormalized integrals to define a path integral on manifolds by approximation via geodesic polygons. The main part of the paper is dedicated to the proof of a path integral formula for the heat kernel of any self-adjoint generalized Laplace operator acting on sections of a vector bundle over a compact Riemannian manifold.

This doctoral thesis is concerned with some theoretical and practical questions related to backward stochastic differential equations (BSDEs) and more specifically their connection with some parabolic partial differential equations (PDEs). The thesis is made of three parts. In the first part, we study the probabilistic representation for a class of multidimensional PDEs with quadratic nonlinearities of a special form. We obtain a representation formula for the PDE solution in terms of the solutions to a Lipschitz BSDE. We then use this representation to obtain an estimate on the gradient of the PDE solutions by probabilistic means. In the course of our analysis, we are led to prove some results for the associated multidimensional quadratic BSDEs, namely an existence result and a partial uniqueness result. In the second part, we study the well-posedness of a very general quadratic reflected BSDE driven by a continuous martingale. We obtain the comparison theorem, the special comparison theorem for reflected BSDEs (which allows to compare the increasing processes of two solutions), the uniqueness and existence of solutions, as well as a stability result. The comparison theorem (from which uniqueness follows) and the special comparison theorem are obtained through natural techniques and minimal assumptions. The existence is based on a perturbative procedure, and holds for a driver whis is Lipschitz, or slightly-superlinear, or monotone with arbitrary growth in y. Finally, we obtain a stability result, which gives in particular a local Lipschitz estimate in BMO for the martingale part of the solution. In the third and last part, we study the time-discretization of BSDEs having nonlinearities that are monotone but with polynomial growth in the primary variable. We show that in that case, the explicit Euler scheme is likely to diverge, while the implicit scheme converges. In fact, by studying the family of θ-schemes, which are mixed explicit-implicit, θ characterizing the degree of implicitness, we find that the scheme converges when the implicit component is dominant (θ ≥ 1/2 ). We then propose a tamed explicit scheme, which converges. We show that the implicit-dominant schemes with θ > 1/2 and our tamed explicit scheme converge with order 1/2 , while the trapezoidal scheme (θ = 1/2) converges with order 7/4.

Cette thèse porte sur le développement de méthodes de Monte-Carlo pour calculer des représentations Feynman-Kac impliquant des opérateurs sous forme divergence avec un coefficient de diffusion constant par morceaux. Les méthodes proposées sont des variantes de la marche sur les sphères à l'intérieur des zones avec un coefficient de diffusion constant et des techniques de différences finies stochastiques pour traiter les conditions aux interfaces aussi bien que les conditions aux limites de différents types. En combinant ces deux techniques, on obtient des marches aléatoires dont le score calculé le long du chemin fourni un estimateur biaisé de la solution de l'équation aux dérivées partielles considérée. On montre que le biais global de notre algorithme est en général d'ordre deux par rapport au pas de différences finies. Ces méthodes sont ensuite appliquées au problème direct lié à la tomographie par impédance électrique pour la détection de tumeurs. Une technique de réduction de variance est également proposée dans ce cadre. On traite finalement du problème inverse de la détection de tumeurs à partir de mesures de surfaces à l'aide de deux algorithmes stochastiques basés sur une représentation paramétrique de la tumeur ou des tumeurs sous forme d'une ou plusieurs sphères. De nombreux essais numériques sont proposés et montrent des résultats probants dans la localisation des tumeurs. / This thesis deals with the development of Monte-Carlo methods to compute Feynman-Kac representations involving divergence form operators with a piecewise constant diffusion coefficient. The proposed methods are variations around the walk on spheres method inside the regions with a constant diffusion coefficient and stochastic finite differences techniques to treat the interface conditions as well as the different kinds of boundary conditions. By combining these two techniques, we build random walks which score computed along the walk gives us a biased estimator of the solution of the partial differential equation we consider. We prove that the global bias is in general of order two with respect to the finite difference step. These methods are then applied for tumour detection to the forward problem in electrical impedance tomography. A variance reduction technique is also proposed in this case. Finally, we treat the inverse problem of tumours detection from surface measurements using two stochastics algorithms based on a spherical parametric representation of the tumours. Many numerical tests are proposed and show convincing results in the localization of the tumours.

第一筆金融交換出現以來，短短的十一、二年 場成長迅速，成為不可或 缺的財務工具。有鑑鷟艦瘣城竣@簡要的介紹，並建立金融交換之定 珓洶妨堨腄A主要承襲S. Sundaresan 對金融交bS. Sundaresan 的研究中 ，只針對一般的金融交A未考慮特殊型態的金融交換。所以本文的目的在B 下利率限制的金融交融之定價模型，主要定價的般的、capped、floored 、及 collared金融交換。漱隤k上，採用與其他研究不同的Feynman-Kac So- 融交換定價模型之前，必須先建立一般的金融交C再利用利率caps 和floors之特性，加入一般金融A以推導出有上下利率限制的金融交換定 價模型。F導出金融交換之定價模型外，並對所建立的模型k，計算出金融 交換和collar的價值，同時分析@般金融交換與collar金融交換的價值。 提供銀j眾，在進行金融交換時作為參考。