MS-8 Krylov and filtering methods for eigenvalue problems (Krylov & filtering for eigenvalues)

Organizers: Jared Aurentz (Instituto de Ciencias Matemáticas, UAM, Madrid) and Karl Meerbergen (KU Leuven, Belgium)

The algebraic eigenvalue problem is at the heart of many applications in science and engineering. The reliable and accurate solution of large scale problems is often a difficult task. We focus on recent advances in Krylov methods and rational filtering for large scale eigenvalue problems.


Thomas Mach, LAA Early Career Speaker, Inverse Free Rational Krylov Subspaces for Computing Matrix Functions

Anthony Austin, Estimating Eigenvalue Distributions

Daan Camps, On the implicit restart of the rational Krylov method

Yasunori Futamura, A real-valued method for improving efficiency of a contour integral eigenvalue solver

Brendan Gavin, The FEAST Eigenvalue Algorithm with Inexact Solves

Vjeran Hari, On Element-wise and Block-wise Jacobi Methods for PGEP

Vassilis Kalantzis, Rational filtering Schur complement techniques for the solution of large-scale generalized symmetric eigenvalue problems

Yousef Saad, Rational and polynomial filtering, spectrum slicing, and the EVSL package

Roel van Beeumen, A rational filtering connection between contour integration and rational Krylov methods for large scale eigenvalue problems