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Related papers: A multi-level preconditioned Krylov method for the…

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We propose an alternative implementation of preconditioning techniques for the solution of non-linear problems. Within the framework of Newton-Krylov methods, preconditioning techniques are needed to improve the performance of the solvers.…

Computational Physics · Physics 2008-04-02 G. Lapenta , S. Ju

This paper introduces a new class of algorithms for solving large-scale linear inverse problems based on new flexible and inexact Golub-Kahan factorizations. The proposed methods iteratively compute regularized solutions by approximating a…

Numerical Analysis · Mathematics 2025-10-22 Malena Sabaté Landman , Silvia Gazzola

For the large-scale linear discrete ill-posed problem $\min\|Ax-b\|$ or $Ax=b$ with $b$ contaminated by Gaussian white noise, there are four commonly used Krylov solvers: LSQR and its mathematically equivalent CGLS, the Conjugate Gradient…

Numerical Analysis · Mathematics 2020-03-20 Zhongxiao Jia

Variational regularisation is the primary method for solving inverse problems, and recently there has been considerable work leveraging deeply learned regularisation for enhanced performance. However, few results exist addressing the…

Optimization and Control · Mathematics 2024-06-18 Zakhar Shumaylov , Jeremy Budd , Subhadip Mukherjee , Carola-Bibiane Schönlieb

One of the limitations of recycled GCRO methods is the large amount of computation required to orthogonalize the basis vectors of the newly generated Krylov subspace for the approximate solution when combined with those of the recycle…

Numerical Analysis · Mathematics 2023-06-12 Stephen Thomas , Alison Baker , Stephane Gaudreault

The purpose of the current work is to find numerical solutions of the steady state inhomogeneous Vlasov equation. This problem has a wide range of applications in the kinetic simulation of non-thermal plasmas. However, the direct…

Computational Physics · Physics 2018-08-14 Markus Gasteiger , Lukas Einkemmer , Alexander Ostermann , David Tskhakaya

The Arnoldi-Tikhonov method is a well-established regularization technique for solving large-scale ill-posed linear inverse problems. This method leverages the Arnoldi decomposition to reduce computational complexity by projecting the…

Numerical Analysis · Mathematics 2025-06-02 Davide Bianchi , Marco Donatelli , Davide Furchì , Lothar Reichel

A wide variety of different (fixed-point) iterative methods for the solution of nonlinear equations exists. In this work we will revisit a unified iteration scheme in Hilbert spaces from our previous work that covers some prominent…

Numerical Analysis · Mathematics 2019-05-17 Pascal Heid , Thomas P. Wihler

Analyzing massive spatial datasets using Gaussian process model poses computational challenges. This is a problem prevailing heavily in applications such as environmental modeling, ecology, forestry and environmental heath. We present a…

Methodology · Statistics 2021-12-07 Suman Majumder , Yawen Guan , Brian J. Reich , Arvind K. Saibaba

In this paper, a new tool for Doppler tomography, Tomo-V (https://tomo-v.inasan.ru) that is developed based on the algebraic reconstruction technique (ART) has been presented. Previously, the ART method has not been widely used in…

Instrumentation and Methods for Astrophysics · Physics 2026-03-30 P. V. Kaygorodov

The multigrid algorithm is a multilevel approach to accelerate the numerical solution of discretized differential equations in physical problems involving long-range interactions. Multiresolution analysis of wavelet theory provides an…

Computational Physics · Physics 2007-05-23 D. Yesilleten , T. A. Arias

We describe a novel framework for estimating subsurface properties, such as rock permeability and porosity, from time-lapse observed seismic data by coupling full-waveform inversion, subsurface flow processes, and rock physics models. For…

Geophysics · Physics 2020-05-06 Dongzhuo Li , Kailai Xu , Jerry M. Harris , Eric Darve

For several classes of mathematical models that yield linear systems, the splitting of the matrix into its Hermitian and skew Hermitian parts is naturally related to properties of the underlying model. This is particularly so for…

Numerical Analysis · Mathematics 2023-01-02 Malak Diab , Andreas Frommer , Karsten Kahl

This work aims to accelerate the convergence of proximal gradient methods used to solve regularized linear inverse problems. This is achieved by designing a polynomial-based preconditioner that targets the eigenvalue spectrum of the normal…

We present a matrix-free parallel scalable multilevel deflation preconditioned method for heterogeneous time-harmonic wave problems. Building on the higher-order deflation preconditioning proposed by Dwarka and Vuik (SIAM J. Sci. Comput.…

Numerical Analysis · Mathematics 2025-01-06 Jinqiang Chen , Vandana Dwarka , Cornelis Vuik

The next generation ground-based telescopes rely heavily on adaptive optics for overcoming the limitation of atmospheric turbulence. In the future adaptive optics modalities, like multi-conjugate adaptive optics (MCAO), atmospheric…

Numerical Analysis · Mathematics 2015-06-15 Tapio Helin , Mykhaylo Yudytskiy

Multistep matrix splitting iterations serve as preconditioning for Krylov subspace methods for solving singular linear systems. The preconditioner is applied to the generalized minimal residual (GMRES) method and the flexible GMRES (FGMRES)…

Numerical Analysis · Mathematics 2021-11-09 Keiichi Morikuni

The solution of sequences of shifted linear systems is a classic problem in numerical linear algebra, and a variety of efficient methods have been proposed over the years. Nevertheless, there still exist challenging scenarios witnessing a…

Numerical Analysis · Mathematics 2026-01-28 Hussam Al Daas , Davide Palitta

Isogeometric Analysis (IgA) has become a viable alternative to the Finite Element Method (FEM) and is typically combined with a time integration scheme within the method of lines for time-dependent problems. However, due to a stagnation of…

Numerical Analysis · Mathematics 2021-07-13 Roel Tielen , Matthias Möller , Cornelis Vuik

When an iterative method is applied to solve the linear equation system in interior point methods (IPMs), the attention is usually placed on accelerating their convergence by designing appropriate preconditioners, but the linear solver is…

Optimization and Control · Mathematics 2023-04-28 Filippo Zanetti , Jacek Gondzio
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