Résumé : High-order numerical discretizations and a posteriori error estimates for variational inequalities
We propose an adaptive inexact version of a class of semismooth Newton methods for variational inequalities.
As a model problem, we study the system of variational inequalities describing the contact between two membranes.
We study a family of Galerkin numerical schemes that discretize this problem.
We consider any iterative semismooth linearization algorithm like the Newton-min or the Newton–Fischer–Burmeister which we complement by
any iterative linear algebraic solver.
In the case of finite elements, we then derive an a posteriori estimate on the error
between the exact solution at the continuous level and the approximate solution which is
valid at any step of the linearization and algebraic resolutions.
Our estimate is based on flux reconstructions in discrete subspaces of H(div,Ω) and on potential reconstructions in
discrete subspaces of H1 (Ω) satisfying the constraints.
It distinguishes the discretization, linearization, and algebraic components of the error.
Consequently, we can formulate adaptive stopping criteria for both solvers, giving rise to an adaptive version of the considered inexact semismooth Newton algorithm.
Under these criteria, the efficiency of the leading estimates is also established, meaning that we prove them equivalent with the error up to a generic constant.
Numerical experiments for the Newton-min algorithm in combination with the GMRES algebraic solver confirm the efficiency of the developed adaptive method.
An extension to unsteady problems is also discussed in the present work.
Lieu : En ligne
Résumé : TBA
Lieu : 316B
Résumé : Dans de nombreuses méthodes statistiques utilisées en valeurs extrêmes, on construit un estimateur à partir d’un sous échantillon de l’échantillon initial. Ce sous échantillon sélectionnes les $k$ observations $(X_i_X_i)$ pour lesquelles $Y_i$ dépasse sa $n-k$ ième statistique d’ordre. Nous montrons que ces méthodes peuvent être vues comme des images de mesures aléatoires qui se comportent comme des mesure empiriques si on les conditionne correctement. Travail en collaboration avec Dr Benjamin Bobbia et Pr Clément dombry.
Résumé : In my talk I will present the following topics :
1. Strong connections between generalized Gaussian processes and some class of positive definite functions on permutations group.
2. Type B Fock spaces and new Gaussian processes of type B , relations with q-Meixner-Pollaczek polynomials and Meixner probability measures like 1/cosh.
3. Thoma repsentation of central positive definite functions on Coxeter groups of type A and B and new classes of generalized Gaussian processes.
4. Open problems.
Lieu : En visio conférence
Lieu : En visio conférence
Lieu : En visioconférence