Organizers: Elias Jarlebring (KTH Royal Institute of Technology, Sweden) and Wim Michiels (KU Leuven, Belgium)
Matrix distance problems are at the intersection of numerical linear algebra, systems and control, and optimization. From an application point of view, distance problems form, for instance, the core of methods for assessing and optimization the transient behavior of dynamical systems, their stability robustness, as well as performance measures, expressed in terms of H-2- H-infinity criteria. Many of the recent theoretical and computational advances are based on eigenvalue perturbation theory and eigenvalue optimization algorithms. The aim of the minisymposium is to bring together experts on the topic, who will highlight several recent developments in the area of distance problems. They will pay special attention to exploiting structure and sparsity on the uncertainty, inferred from the underlying application, and on exploiting the structure of the perturbed eigenvalue problem, e.g., a nonlinearity in the eigenvalue parameter.
Francesco Borgioli, An iterative algorithm to compute the pseudospectral abscissa for real perturbations of a nonlinear eigenvalue problem
Mert Gurbuzbalaban, Approximating the Real Structured Stability Radius with Frobenius Norm Bounded Perturbations
Emre Mengi, Subspace Procedures for Large-Scale Stability Radius Problems
Bart Vandereycken, Subspace acceleration for computing the Crawford number