Computing low-rank rightmost eigenpairs of a class of matrix-valued linear operators

Autor: Nicola Guglielmi, Carmela Scalone, Daniel Kressner
Rok vydání: 2021
Předmět:
Zdroj: Advances in Computational Mathematics. 47
ISSN: 1572-9044
1019-7168
DOI: 10.1007/s10444-021-09895-2
Popis: In this article, a new method is proposed to approximate the rightmost eigenpair of certain matrix-valued linear operators, in a low-rank setting. First, we introduce a suitable ordinary differential equation, whose solution allows us to approximate the rightmost eigenpair of the linear operator. After analyzing the behaviour of its solution on the whole space, we project the ODE on a low-rank manifold of prescribed rank and correspondingly analyze the behaviour of its solutions. For a general linear operator we prove that—under generic assumptions—the solution of the ODE converges globally to its leading eigenmatrix. The analysis of the projected operator is more subtle due to its nonlinearity; when ca is self-adjoint, we are able to prove that the associated low-rank ODE converges (at least locally) to its rightmost eigenmatrix in the low-rank manifold, a property which appears to hold also in the more general case. Two explicit numerical methods are proposed, the second being an adaptation of the projector splitting integrator proposed recently by Lubich and Oseledets. The numerical experiments show that the method is effective and competitive.
Databáze: OpenAIRE
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