A Low-Rank Inexact Newton–Krylov Method for Stochastic Eigenvalue Problems
A Low-Rank Inexact Newton–Krylov Method for Stochastic Eigenvalue Problems
Abstract This paper aims at the efficient numerical solution of stochastic eigenvalue problems. Such problems often lead to prohibitively high-dimensional systems with tensor product structure when discretized with the stochastic Galerkin method. Here, we exploit this inherent tensor product structure to develop a globalized low-rank inexact Newton method with which …