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Stochastic iterative refinement with preconditioning for solving Helmholtz equation via boundary integral equation Научная публикация

Журнал

Monte Carlo Methods and Applications
ISSN: 0929-9629 , E-ISSN: 1569-3961

Вых. Данные

Год: 2025, Том: 31, Номер: 4, Страницы: 329-342 Страниц : 14 DOI: 10.1515/mcma-2025-2022

Ключевые слова

Boundary integral equations; vector randomized algorithm; large system of linear equations; iterative refinement; Helmholtz equation; randomized SVD; stochastic projection methods

Авторы

Sabelfeld Karl K. ² , Prokopiev Alexander ¹

Организации

1	Institute of Computational Mathematics and Mathematical Geophysics , Russian Academy of Sciences
2	Sobolev Institute of Mathematics, Russian Academy of Sciences , Novosibirsk , Russia

Информация о финансировании (1)

Российский научный фонд

24-11-00107

This work suggests different Monte Carlo algorithms for solving large systems of linear algebraic equations arising from the numerical solution of the Dirichlet problem for the Helmholtz equation. Approach based on boundary integral representations, vector randomization algorithm, method of fundamental solutions, stochastic projection algorithm, and randomized singular value decomposition are applied. It is shown that the use of stochastic iterative refinement and preconditioning can significantly improve the accuracy and stability of the computations. Simulation results are presented, demonstrating the effectiveness of the proposed methods.

Sabelfeld K.K. , Prokopiev A.
Stochastic iterative refinement with preconditioning for solving Helmholtz equation via boundary integral equation
Monte Carlo Methods and Applications. 2025. V.31. N4. P.329-342. DOI: 10.1515/mcma-2025-2022 WOS Scopus OpenAlex

Поступила в редакцию:	23 июл. 2025 г.
Принята к публикации:	15 нояб. 2025 г.
Опубликована online:	16 нояб. 2025 г.
Опубликована в печати:	1 дек. 2025 г.

Web of science:	WOS:001614544300001
Scopus:	2-s2.0-105021962375
OpenAlex:	W7105754229

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