Learned iterative solvers for the Helmholtz equation

TitleLearned iterative solvers for the Helmholtz equation
Publication TypeConference
Year of Publication2019
AuthorsGabrio Rizzuti, Ali Siahkoohi, Felix J. Herrmann
Conference NameEAGE Annual Conference Proceedings
Month06
KeywordsEAGE, Helmholtz, Iterative, machine learning
Abstract

We propose a ‘learned’ iterative solver for the Helmholtz equation, by combining traditional Krylov-based solvers with machine learning. The method is, in principle, able to circumvent the shortcomings of classical iterative solvers, and has clear advantages over purely data-driven ap- proaches. We demonstrate the effectiveness of this approach under a 1.5-D assumption, when ade- quate a priori information about the velocity distribution is known.

Notes

(EAGE, Copenhagen)

URLhttps://slim.gatech.edu/Publications/Public/Conferences/EAGE/2019/rizzuti2019EAGElis/rizzuti2019EAGElis.pdf
DOI10.3997/2214-4609.201901542
Presentation
Citation Keyrizzuti2019EAGElis