We deal with locally ill-posed nonlinear operator equations F(x) = y in L^2(0,1), where the Fréchet derivatives A = F'(x_0) of the nonlinear forward operator F are compact linear integral operators A = M ◦ J with a multiplication operator M with integrable multiplier function m and with the simple integration operator J. In particular, we give examples of nonlinear inverse problems in natural sciences and stochastic finance that can be written in such a form with linearizations that contain multiplication operators. Moreover, we consider the corresponding ill-posed linear operator equations Ax = y and their degree of ill-posedness. In particular, we discuss the fact that the noncompact multiplication operator M has only a restricted influence on this degree of ill-posedness even if m has essential zeros of various order.

In this work we develop and analyze algorithms motivated by the parameter estimation problem corresponding to a multilayer aquifer/interbed groundwater flow model. The parameter estimation problem is formulated as an optimization problem, then addressed with algorithms based on adjoint equations, quasi-Newton schemes, and multilevel optimization. In addition to the parameter estimation problem, we consider properties of the parameter to solution map. This includes invertibility (known as identifiability) and differentiability properties of the map. For differentiability, we expand existing results on Fréchet sensitivity analysis to convection diffusion equations and groundwater flow equations. This is achieved by proving that the Fréchet  derivative of the solution operator is Hilbert-Schmidt, under smoothness assumptions for the parameter space. In addition, we approximate this operator by time dependent matrices, where their singular values and singular vectors converge to their infinite dimension peers. This decomposition proves to be very useful as it provides vital information as to which perturbations in the distributed parameters lead to the most significant changes in the solutions, as well as applications to uncertainty quantification. Numerical results complement our theoretical findings. / Ph. D.

We deal with locally ill-posed nonlinear operator equations F(x) = y in L^2(0,1), where the Fréchet derivatives A = F'(x_0) of the nonlinear forward operator F are compact linear integral operators A = M ◦ J with a multiplication operator M with integrable multiplier function m and with the simple integration operator J. In particular, we give examples of nonlinear inverse problems in natural sciences and stochastic finance that can be written in such a form with linearizations that contain multiplication operators. Moreover, we consider the corresponding ill-posed linear operator equations Ax = y and their degree of ill-posedness. In particular, we discuss the fact that the noncompact multiplication operator M has only a restricted influence on this degree of ill-posedness even if m has essential zeros of various order.

The development of highly coherent X-ray sources offers new possibilities to image biological structures at different scales exploiting the refraction of X-rays. The coherence properties of the third-generation synchrotron radiation sources enables efficient implementations of phase contrast techniques. One of the first measurements of the intensity variations due to phase contrast has been reported in 1995 at the European Synchrotron Radiation Facility (ESRF). Phase imaging coupled to tomography acquisition allows threedimensional imaging with an increased sensitivity compared to absorption CT. This technique is particularly attractive to image samples with low absorption constituents. Phase contrast has many applications, ranging from material science, paleontology, bone research to medicine and biology. Several methods to achieve X-ray phase contrast have been proposed during the last years. In propagation based phase contrast, the measurements are made at different sample-to-detector distances. While the intensity data can be acquired and recorded, the phase information of the signal has to be "retrieved" from the modulus data only. Phase retrieval is thus an illposed nonlinear problem and regularization techniques including a priori knowledge are necessary to obtain stable solutions. Several phase recovery methods have been developed in recent years. These approaches generally formulate the phase retrieval problem as a linear one. Nonlinear treatments have not been much investigated. The main purpose of this work was to propose and evaluate new algorithms, in particularly taking into account the nonlinearity of the direct problem. In the first part of this work, we present a Landweber type nonlinear iterative scheme to solve the propagation based phase retrieval problem. This approach uses the analytic expression of the Fréchet derivative of the phase-intensity relationship and of its adjoint, which are presented in detail. We also study the effect of projection operators on the convergence properties of the method. In the second part of this thesis, we investigate the resolution of the linear inverse problem with an iterative thresholding algorithm in wavelet coordinates. In the following, the two former algorithms are combined and compared with another nonlinear approach based on sparsity regularization and a fixed point algorithm. The performance of theses algorithms are evaluated on simulated data for different noise levels. Finally the algorithms were adapted to process real data sets obtained in phase CT at the ESRF at Grenoble.

La caractérisation d’objets enfouis à partir de mesures d’ondes diffractées est un problème présent dans de nombreuses applications comme l’exploration géophysique, le contrôle non-destructif, l’imagerie médicale, etc. Elle peut être obtenue numériquement par la résolution d’un problème inverse. Néanmoins, c’est un problème non linéaire et mal posé, ce qui rend la tâche difficile. Une reconstruction précise nécessite un choix judicieux de plusieurs paramètres très différents, dépendant des données de la méthode numérique d’optimisation choisie.La contribution principale de cette thèse est une étude de la reconstruction complète d’obstacles élastiques immergés à partir de mesures du champ lointain diffracté. Les paramètres à reconstruire sont la frontière, les coefficients de Lamé, la densité et la position de l’obstacle. On établit tout d’abord des résultats d’existence et d’unicité pour un problème aux limites généralisé englobant le problème direct d’élasto-acoustique. On analyse la sensibilité du champ diffracté par rapport aux différents paramètres du solide, ce qui nous conduit à caractériser les dérivées partielles de Fréchet comme des solutions du problème direct avec des seconds membres modifiés. Les dérivées sont calculées numériquement grâce à la méthode de Galerkine discontinue avec pénalité intérieure et le code est validé par des comparaisons avec des solutions analytiques. Ensuite, deux méthodologies sont introduites pour résoudre le problème inverse. Toutes deux reposent sur une méthode itérative de type Newton généralisée et la première consiste à retrouver les paramètres de nature différente indépendamment, alors que la seconde reconstruit tous les paramètre en même temps. À cause du comportement différent des paramètres, on réalise des tests de sensibilité pour évaluer l’influence de ces paramètres sur les mesures. On conclut que les paramètres matériels ont une influence plus faible sur les mesures que les paramètres de forme et, ainsi, qu’une stratégie efficace pour retrouver des paramètres de nature distincte doit prendre en compte ces différents niveaux de sensibilité. On a effectué de nombreuses expériences à différents niveaux de bruit, avec des données partielles ou complètes pour retrouver certains paramètres, par exemple les coefficients de Lamé et les paramètres de forme, la densité, les paramètres de forme et la localisation. Cet ensemble de tests contribue à la mise en place d’une stratégie pour la reconstruction complète des conditions plus proches de la réalité. Dans la dernière partie de la thèse, on étend ces résultats à des matériaux plus complexes, en particulier élastiques anisotropes. / The characterization of hidden objects from scattered wave measurements arises in many applications such as geophysical exploration, non destructive testing, medical imaging, etc. It can be achieved numerically by solving an Inverse Problem. However, this is a nonlinear and ill-posed problem, thus a difficult task. A successful reconstruction requires careful selection of very different parameters depending on the data and the chosen optimization numerical method.The main contribution of this thesis is an investigation of the full reconstruction of immersed elastic scatterers from far-field pattern measurements. The sought-after parameters are the boundary, the Lamé coefficients, the density and the location of the obstacle. First, existence and uniqueness results of a generalized Boundary Value Problem including the direct elasto-acoustic problem are established. The sensitivity of the scattered field with respect to the different parametersdescribing the solid is analyzed and we end up with the characterization of the corresponding partial Fréchet derivatives as solutions to the direct problem with modified right-hand sides. These Fréchet derivatives are computed numerically thanks to the Interior Penalty Discontinuous Galerkin method and the code is validated thanks to comparison with analytical solutions. Then, two solution methodologies are introduced for solving the inverse problem. Both are based on an iterative regularized Newton-type methodology and the first one consists in retrieving the parameters of different nature independently, while the second one reconstructs all parameters together. Due to the different behavior of the parameters, sensitivity tests are performed to assess the impact of the parameters on the measurements. We conclude that material parameters have a weaker influence on the measurements than shape parameters, and therefore, a successful strategy to retrieve parameters of distinct nature should take into account these different levels of sensitivity. Various experiments at different noise levels and with full or limited aperture data are carried out to retrieve some of the physical properties, e.g. Lamé coefficients with shape parameters, density with shape parameters a, density, shape and location. This set of tests contributes to a final strategy for the full reconstruction and in more realistic conditions. In the final part of the thesis, we extend the results to more complex material parameters, in particular anisotropic elastic.

Le développement de sources cohérentes de rayons X offre de nouvelles possibilités pour visualiser les structures biologiques à différentes échelles en exploitant la réfraction des rayons X. La cohérence des sources synchrotron de troisième génération permettent des implémentations efficaces des techniques de contraste de phase. Une des premières mesures des variations d’intensité dues au contraste de phase a été réalisée en 1995 à l’Installation Européenne de Rayonnement Synchrotron (ESRF). L’imagerie de phase couplée à l’acquisition tomographique permet une imagerie tridimensionnelle avec une sensibilité accrue par rapport à la tomographie standard basée sur absorption. Cette technique est particulièrement adaptée pour les échantillons faiblement absorbante ou bien présentent des faibles différences d’absorption. Le contraste de phase a ainsi une large gamme d’applications, allant de la science des matériaux, à la paléontologie, en passant par la médecine et par la biologie. Plusieurs techniques de contraste de phase aux rayons X ont été proposées au cours des dernières années. Dans la méthode de contraste de phase basée sur le phénomène de propagation l’intensité est mesurée pour différentes distances de propagation obtenues en déplaçant le détecteur. Bien que l’intensité diffractée puisse être acquise et enregistrée, les informations de phase du signal doivent être "récupérées" à partir seulement du module des données mesurées. L’estimation de la phase est donc un problème inverse non linéaire mal posé et une connaissance a priori est nécessaire pour obtenir des solutions stables. Si la plupart de méthodes d’estimation de phase reposent sur une linéarisation du problème inverse, les traitements non linéaires ont été eux très peu étudiés. Le but de ce travail était de proposer et d’évaluer des nouveaux algorithmes, prenant en particulier en compte la non linéarité du problème direct. Dans la première partie de ce travail, nous présentons un schéma de type Landweber non linéaire itératif pour résoudre le problème de la récupération de phase. Cette approche utilise l’expression analytique de la dérivée de Fréchet de la relation phase-intensité et de son adjoint. Nous étudions aussi l’effet des opérateurs de projection sur les propriétés de convergence de la méthode. Dans la deuxième partie de cette thèse, nous étudions la résolution du problème inverse linéaire avec un algorithme en coordonnées ondelettes basé sur un seuillage itératif. Par la suite, les deux algorithmes sont combinés et comparés avec une autre approche non linéaire basée sur une régularisation parcimonieuse et un algorithme de point fixe. Les performances des algorithmes sont évaluées sur des données simulées pour différents niveaux de bruit. Enfin, les algorithmes ont été adaptés pour traiter des données réelles acquises en tomographie de phase à l’ESRF à Grenoble. / The development of highly coherent X-ray sources offers new possibilities to image biological structures at different scales exploiting the refraction of X-rays. The coherence properties of the third-generation synchrotron radiation sources enables efficient implementations of phase contrast techniques. One of the first measurements of the intensity variations due to phase contrast has been reported in 1995 at the European Synchrotron Radiation Facility (ESRF). Phase imaging coupled to tomography acquisition allows threedimensional imaging with an increased sensitivity compared to absorption CT. This technique is particularly attractive to image samples with low absorption constituents. Phase contrast has many applications, ranging from material science, paleontology, bone research to medicine and biology. Several methods to achieve X-ray phase contrast have been proposed during the last years. In propagation based phase contrast, the measurements are made at different sample-to-detector distances. While the intensity data can be acquired and recorded, the phase information of the signal has to be "retrieved" from the modulus data only. Phase retrieval is thus an illposed nonlinear problem and regularization techniques including a priori knowledge are necessary to obtain stable solutions. Several phase recovery methods have been developed in recent years. These approaches generally formulate the phase retrieval problem as a linear one. Nonlinear treatments have not been much investigated. The main purpose of this work was to propose and evaluate new algorithms, in particularly taking into account the nonlinearity of the direct problem. In the first part of this work, we present a Landweber type nonlinear iterative scheme to solve the propagation based phase retrieval problem. This approach uses the analytic expression of the Fréchet derivative of the phase-intensity relationship and of its adjoint, which are presented in detail. We also study the effect of projection operators on the convergence properties of the method. In the second part of this thesis, we investigate the resolution of the linear inverse problem with an iterative thresholding algorithm in wavelet coordinates. In the following, the two former algorithms are combined and compared with another nonlinear approach based on sparsity regularization and a fixed point algorithm. The performance of theses algorithms are evaluated on simulated data for different noise levels. Finally the algorithms were adapted to process real data sets obtained in phase CT at the ESRF at Grenoble.