Computational and Applied Mathematics (CAM) seminar
Daniel Peterseim, Universität Augsburg: Energy-adaptive Riemannian Optimization on the Stiefel Manifold
Abstract: This talk addresses the numerical simulation of nonlinear eigenvector problems such as the Gross-Pitaevskii and Kohn-Sham equation arising in computational physics and chemistry. These problems characterize critical points of energy minimization problems on the infinite-dimensional Stiefel manifold. To efficiently compute minimizers we propose a novel Riemannian gradient descent method induced by an energy-adaptive metric. Quantified convergence of the method is established under suitable assumptions on the underlying problem. A non-monotone line search and the inexact inexact evaluation of Riemannian gradients substantially improve the overall efficiency of the method. Numerical experiments illustrate the performance of the method and demonstrates its competitiveness with well-established schemes.
This is joint work with Robert Altmann (U Augsburg) and Tatjana Stykel (U Augsburg).
Organiser: David Cohen (email@example.com). Please contact me if you need the Zoom password. Zoom meeting link: https://chalmers.zoom.us/j/69309989575
MV:L14 och online