Newton-Type Methods For Simultaneous Matrix Diagonalization

This paper proposes a Newton-type method to solve numerically the eigenproblem of several diagonalizable matrices, which pairwise commute. A classical result states that these matrices are simultaneously diagonalizable. From a suitable system of equations associated to this problem, we construct a sequence that converges quadratically towards the solution. This construction is not based on the resolution of a linear system as is the case in the classical Newton method. Moreover, we provide a theoretical analysis of this construction and exhibit a condition to get a quadratic convergence. We also propose numerical experiments, which illustrate the theoretical results.Comment: Calcolo, Springer Verlag, 202

Computing Nearest Gcd with Certification

International audienceA bisection method, based on exclusion and inclusion tests, is used to address the nearest univariate gcd problem formulated as a bivariate real minimization problem of a rational fraction. The paper presents an algorithm, a first implementation and a complexity analysis relying on Smale's $\alpha$-theory. We report its behavior on an illustrative example

Punctual Hilbert Schemes and Certified Approximate Singularities

In this paper we provide a new method to certify that a nearby polynomial system has a singular isolated root with a prescribed multiplicity structure. More precisely, given a polynomial system f $=(f\_1, \ldots, f\_N)\in C[x\_1, \ldots, x\_n]^N$, we present a Newton iteration on an extended deflated system that locally converges, under regularity conditions, to a small deformation of $f$ such that this deformed system has an exact singular root. The iteration simultaneously converges to the coordinates of the singular root and the coefficients of the so called inverse system that describes the multiplicity structure at the root. We use $$\alpha$$-theory test to certify the quadratic convergence, and togive bounds on the size of the deformation and on the approximation error. The approach relies on an analysis of the punctual Hilbert scheme, for which we provide a new description. We show in particular that some of its strata can be rationally parametrized and exploit these parametrizations in the certification. We show in numerical experimentation how the approximate inverse system can be computed as a starting point of the Newton iterations and the fast numerical convergence to the singular root with its multiplicity structure, certified by our criteria.Comment: International Symposium on Symbolic and Algebraic Computation, Jul 2020, Kalamata, Franc

Computing Nearest Gcd with Certification

International audienceA bisection method, based on exclusion and inclusion tests, is used to address the nearest univariate gcd problem formulated as a bivariate real minimization problem of a rational fraction. The paper presents an algorithm, a first implementation and a complexity analysis relying on Smale's $\alpha$-theory. We report its behavior on an illustrative example

A Subdivision Method for Computing Nearest Gcd with Certification

International audienceA new subdivision method for computing the nearest univariate gcd is described and analyzed. It is based on an exclusion test and an inclusion test. The xclusion test in a cell exploits Taylor expansion of the polynomial at the center of the cell. The inclusion test uses Smale's alpha-theorems to certify the existence and unicity of a solution in a cell. Under the condition of simple roots for the distance minimization problem, we analyze the complexity of the algorithm in terms of a condition number, which is the inverse of the distance to the set of degenerate systems. We report on some experimentation on representative examples to illustrate the behavior of the algorithm

Numerical analysis of a bisection-exclusion method to find zeros of univariate analytic functions

Abstract. We state precise results on the complexity of a classical bisectionexclusion method to locate zeros of univariate analytic functions contained in a square. The output of this algorithm is a list of squares containing all the zeros. It is also a robust method to locate clusters of zeros. We show that the global complexity depends on the following quantities: the size of the square, the desired precision, the number of clusters of zeros in the square, the distance between the clusters and the global behavior of the analytic function and its derivatives. We also prove that, closed to a cluster of zeros, the complexity depends only on the number of zeros inside the cluster. In particular, for a polynomial which has d simple roots separated by a distance greater than sep, we will prove the bisection-exclusion algorithm needs O(d 3 log(d/sep)) tests to isolate the d roots and the number of squares suspected to contain a zero is bounded by 4d. Moreover, always in the polynomial case, we will see the arithmetic complexity can be reduced to O(d 2 (log d) 2 log(d/sep)) using ⌈log d⌉ steps of the Graeffe iteration

APPROXIMATION NUMÉRIQUE DE RACINES ISOLÉES MULTIPLES DE SYSTÈMES ANALYTIQUES

Abstract. The approximation of a multiple isolated root is a difficult problem. In fact the root can even be a repulsive root for a fixed point method like the Newton method. However there exists a huge literature on this topic but the answers given are not satisfactory. Numerical methods allowing a local convergence analysis work often under specific hypotheses. This viewpoint favouring numerical analysis forgets the geometry and the structure of the local algebra. Thus appeared so-called symbolic-numeric methods, yet full of lessons, but their precise numerical analysis is still missing. We propose in this paper a method of symbolic-numeric kind, whose numerical treatment is certified. The general idea is to construct a finite sequence of systems, admitting the same root, and called the deflation sequence, so that the multiplicity of the root drops strictly between two successive systems. So the root becomes regular. Then we can extract a regular square system we call deflated system. We described already the construction of this deflated sequence when the singular root is known. The originality of this paper consists on one hand to construct a deflation sequence from a point close to the root and on the other hand to give a numerical analysis of this method. Analytic square integrable functions build the functional frame. Using the Bergman kernel, reproducing kernel of this functional frame, we are able to give a α-theory à la Smale. Furthermore we present new results on the determination of the numerical rank of a matrix and the closeness to zero of the evaluation map. As an important consequence we give an algorithm computing a deflation sequence free of ε, threshold quantity measuring the numerical approximation, meaning that the entry of this algorithm does not involve the variable ε.L'approximation d'une racine isolée multiple est un problème difficile. En effet la racine peut même être répulsive pour une méthode de point fixe comme la méthode de Newton. La littérature sur le sujet est vaste mais les réponses proposées pour résoudre ce problème ne sont pas satisfaisantes. Des méthodes numériques qui permettent de faire une analyse locale de convergence sont souvent élaborées sous des hypothèses particulières. Ce point de vue privilégiant l'analyse numérique néglige la géométrie et la structure de l'algèbre locale. C'est ainsi qu'ont émergé des méthodes qualifiés de symboliques-numériques. Mais l'analyse numérique précise de ces méthodes pourtant riches d'enseignement n'a pas été faite. Nous proposons dans cet article une méthode de type symbolique-numérique dont le traitement numérique est certifié. L'idée générale est de construire une suite finie de systèmes admettant la même racine, appelée suite de déflation, telle que la multiplicité de la racine chute strictement entre deux systèmes successifs. La racine devient ainsi régulière lors du dernier système. Il suffit alors d'en extraire un système carré régulier pour obtenir ce que nous appelons système déflaté. Nous avions déjà décrit la construction de cette suite de déflation quand la racine est connue. L'originalité de cette étude consiste d'une part à définir une suite de déflation à partir d'un point proche de la racine et d'autre part à donner une analyse numérique de cette méthode. Le cadre fonctionnel de cette analyse est celui des systèmes analytiques constitués de fonctions de carré intégrable. En utilisant le noyau Bergman, noyau reproduisant de cet espace fonctionnel, nous donnons une α-théorie à la Smale de cette suite de déflation. De plus nous présentons des résultats nouveaux relatifs à la détermination du rang numérique d'une matrice et à celle de la proximité à zéro de l'application évaluation. Comme conséquence importante nous donnons un algorithme de calcul d'une suite de déflation qui est libre de ε, quantité-seuil qui mesure l'approximation numérique, dans le sens que les entrées de cet algorithme ne comportent pas la variable ε. Classification mathématique par sujets (2010). 65F30, 65H10, 65Y20, 68Q25, 68W30