Bifurcation analysis of the Topp model

In this paper, we study the 3-dimensional Topp model for the dynamicsof diabetes. We show that for suitable parameter values an equilibrium of this modelbifurcates through a Hopf-saddle-node bifurcation. Numerical analysis suggests thatnear this point Shilnikov homoclinic orbits exist. In addition, chaotic attractors arisethrough period doubling cascades of limit cycles.Keywords Dynamics of diabetes · Topp model · Reduced planar quartic Toppsystem · Singular point · Limit cycle · Hopf-saddle-node bifurcation · Perioddoubling bifurcation · Shilnikov homoclinic orbit · Chao

Complexity of Sparse Polynomial Solving 2: Renormalization

Renormalized homotopy continuation on toric varieties is introduced as a tool for solving sparse systems of polynomial equations, or sparse systems of exponential sums. The cost of continuation depends on a renormalized condition length, defined as a line integral of the condition number along all the lifted renormalized paths. The theory developed in this paper leads to a continuation algorithm tracking all the solutions between two generic systems with the same structure. The algorithm is randomized, in the sense that it follows a random path between the two systems. The probability of success is one. In order to produce an expected cost bound, several invariants depending solely of the supports of the equations are introduced. For instance, the mixed area is a quermassintegral that generalizes surface area in the same way that mixed volume generalizes ordinary volume. The facet gap measures for each direction in the 0-fan, how close is the supporting hyperplane to the nearest vertex. Once the supports are fixed, the expected cost depends on the input coefficients solely through two invariants: the renormalized toric condition number and the imbalance of the absolute values of the coefficients. This leads to a non-uniform complexity bound for polynomial solving in terms of those two invariants. Up to logarithms, the expected cost is quadratic in the first invariant and linear in the last one.Comment: 90 pages. Major revision from the previous versio

Détection d'un objet immergé dans un fluide

Cette thèse s inscrit dans le domaine des mathématiques appelé optimisation de formes. Plus précisément, nous étudions ici un problème inverse de détection à l aide du calcul de forme et de l analyse asymptotique. L objectif est de localiser un objet immergé dans un fluide visqueux, incompressible et stationnaire. Les questions principales qui ont motivé ce travail sont les suivantes : peut-on détecter un objet immergé dans un fluide à partir d une mesure effectuée à la surface ? peut-on reconstruire numériquement cet objet, i.e. approcher sa position et sa forme, à partir de cette mesure ? peut-on connaître le nombre d objets présents dans le fluide en utilisant cette mesure ?Les résultats obtenus sont décrits dans les cinq chapitres de cette thèse : le premier met en place un cadre mathématique pour démontrer l existence des dérivées de forme d ordre un et deux pour les problèmes de détection d inclusions ; le deuxième analyse le problème de détection à l aide de l optimisation géométrique de forme : un résultat d identifiabilité est montré, le gradient de forme de plusieurs types de fonctionnelles de forme est caractérisé et l instabilité de ce problème inverse est enfin démontrée ; le chapitre 3 utilise nos résultats théoriques pour reconstruire numériquement des objets immergés dans un fluide à l aide d un algorithme de gradient de forme ; le chapitre 4 analyse la localisation de petites inclusions dans un fluide à l aide de l optimisation topologique de forme : le gradient topologique d une fonctionnelle de forme de Kohn-Vogelius est caractérisé ; le dernier chapitre utilise cette dernière expression théorique pour déterminer numériquement le nombre et la localisation de petits obstacles immergés dans un fluide à l aide d un algorithme de gradient topologique.This dissertation takes place in the mathematic field called shape optimization. More precisely, we focus on a detecting inverse problem using shape calculus and asymptotic analysis. The aim is to localize an object immersed in a viscous, incompressible and stationary fluid. This work was motivated by the following main questions: can we localize an obstacle immersed in a fluid from a boundary measurement? can we reconstruct numerically this object, i.e. be close to its localization and its shape, from this measure? can we know how many objects are included in the fluid using this measure?The results are described in the five chapters of the thesis: the first one gives a mathematical framework in order to prove the existence of the shape derivatives oforder one and two in the frame of the detection of inclusions; the second one analyzes the detection problem using geometric shape optimization: an identifiabilityresult is proved, the shape gradient of several shape functionals is characterized and the instability of thisinverse problem is proved; the chapter 3 uses our theoretical results in order to reconstruct numerically some objets immersed in a fluid using a shape gradient algorithm; the fourth chapter analyzes the detection of small inclusions in a fluid using the topological shape optimization : the topological gradient of a Kohn-Vogelius shape functional is characterized; the last chapter uses this theoretical expression in order to determine numerically the number and the location of some small obstacles immersed in a fluid using a topological gradient algorithm.PAU-BU Sciences (644452103) / SudocSudocFranceF

Estimation of multiple-regime regressions with least absolutes deviation

This paper considers least absolute deviations estimation of a regression model with multiple change points occurring at unknown times. Some asymptotic results, including rates of convergence and asymptotic distributions, for the estimated change points and the estimated regression coefficient are derived. Results are obtained without assuming that each regime spans a positive fraction of the sample size. In addition, the number of change points is allowed to grow as the sample size increases. Estimation of the number of change points is also considered. A feasible computational algorithm is developed. An application is also given, along with some monte carlo simulations.Multiple change points, multiple-regime regressions, least absolute deviation, asymptotic distribution

Schémas de type Godunov pour la modélisation hydrodynamique et magnétohydrodynamique

The main objective of this thesis concerns the study, design and numerical implementation of finite volume schemes based on the so-Called Godunov-Type solvers for hyperbolic systems of nonlinear conservation laws, with special attention given to the Euler equations and ideal MHD equations. First, we derive a simple and genuinely two-Dimensional Riemann solver for general conservation laws that can be regarded as an actual 2D generalization of the HLL approach, relying heavily on the consistency with the integral formulation and on the proper use of Rankine-Hugoniot relations to yield expressions that are simple enough to be applied in the structured and unstructured contexts. Then, a comparison between two methods aiming to numerically maintain the divergence constraint of the magnetic field for the ideal MHD equations is performed and we show how the 2D Riemann solver can be employed to obtain robust divergence-Free simulations. Next, we derive a relaxation scheme that incorporates gravity source terms derived from a potential into the hydrodynamic equations, an important problem in astrophysics, and finally, we review the design of finite volume approximations in curvilinear coordinates, providing a fresher view on an alternative discretization approach. Throughout this thesis, numerous numerical results are shown.L’objectif principal de cette thèse concerne l’étude, la conception et la mise en œuvre numérique de schémas volumes finis associés aux solveurs de type Godunov. On s’intéresse à des systèmes hyperboliques de lois de conservation non linéaires, avec une attention particulière sur les équations d’Euler et les équations MHD idéale. Tout d’abord, nous dérivons un solveur de Riemann simple et véritablement multidimensionnelle, pouvant s’appliquer à tout système de lois de conservation. Ce solveur peut être considéré comme une généralisation 2D de l’approche HLL. Les ingrédients de base de la dérivation sont : la consistance avec la formulation intégrale et une utilisation adéquate des relations de Rankine-Hugoniot. Au final nous obtenons des expressions assez simples et applicables dans les contextes des maillages structurés et non structurés. Dans un second temps, nous nous intéressons à la préservation, au niveau discret, de la contrainte de divergence nulle du champ magnétique pour les équations de la MHD idéale. Deux stratégies sont évaluées et nous montrons comment le solveur de Riemann multidimensionnelle peut être utilisé pour obtenir des simulations robustes à divergence numérique nulle. Deux autres points sont abordés dans cette thèse : la méthode de relaxation pour un système Euler-Poisson pour des écoulements gravitationnels en astrophysique, la formulation volumes finis en coordonnées curvilignes. Tout au long de la thèse, les choix numériques sont validés à travers de nombreux résultats numériques

ERES Methodology and Approximate Algebraic Computations

The area of approximate algebraic computations is a fast growing area in modern computer algebra which has attracted many researchers in recent years. Amongst the various algebraic computations, the computation of the Greatest Common Divisor (GCD) and the Least Common Multiple (LCM) of a set of polynomials are challenging problems that arise from several applications in applied mathematics and engineering. Several methods have been proposed for the computation of the GCD of polynomials using tools and notions either from linear algebra or linear systems theory. Amongst these, a matrix-based method which relies on the properties of the GCD as an invariant of the original set of polynomials under elementary row transformations and shifting elements in the rows of a matrix, shows interesting properties in relation to the problem of the GCD of sets of many polynomials. These transformations are referred to as Extended-Row-Equivalence and Shifting (ERES) operations and their iterative application to a basis matrix, which is formed directly from the coefficients of the given polynomials, formulates the ERES method for the computation of the GCD of polynomials and establishes the basic principles of the ERES methodology. The main objective of the present thesis concerns the improvement of the ERES methodology and its use for the efficient computation of the GCD and LCM of sets of several univariate polynomials with parameter uncertainty, as well as the extension of its application to other related algebraic problems. New theoretical and numerical properties of the ERES method are defined in this thesis by introducing the matrix representation of the Shifting operation, which is used to change the position of the elements in the rows of a matrix. This important theoretical result opens the way for a new algebraic representation of the GCD of a set polynomials, the remainder, and the quotient of Euclid's division for two polynomials based on ERES operations. The principles of the ERES methodology provide the means to develop numerical algorithms for the GCD and LCM of polynomials that inherently have the potential to efficiently work with sets of several polynomials with inexactly known coefficients. The present new implementation of the ERES method, referred to as the ``Hybrid ERES Algorithm", is based on the effective combination of symbolic-numeric arithmetic (hybrid arithmetic) and shows interesting computational properties concerning the approximate GCD and LCM problems. The evaluation of the quality, or ``strength", of an approximate GCD is equivalent to an evaluation of a distance problem in a projective space and it is thus reduced to an optimisation problem. An efficient implementation of an algorithm computing the strength bounds is introduced here by exploiting some of the special aspects of the respective distance problem. Furthermore, a new ERES-based method has been developed for the approximate LCM which involves a least-squares minimisation process, applied to a matrix which is formed from the remainders of Euclid's division by ERES operations. The residual from the least-squares process characterises the quality of the obtained approximate LCM. Finally, the developed framework of the ERES methodology is also applied to the representation of continued fractions to improve the stability criterion for linear systems based on the Routh-Hurwitz test