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This paper investigates using the conjugate gradient iterative solver for ill-posed problems. We show that preconditioner and Tikhonov-regularization work in conjunction. In particular when they employ the same symmetric positive…

Numerical Analysis · Mathematics 2025-12-12 Ahmed Chabib , Jean-Francois Witz , Vincent Magnier , Pierre Gosselet

We compare two approaches to compute a portion of the spectrum of dense symmetric definite generalized eigenproblems: one is based on the reduction to tridiagonal form, and the other on the Krylov-subspace iteration. Two large-scale…

For linear inverse problems with a large number of unknown parameters, uncertainty quantification remains a challenging task. In this work, we use Krylov subspace methods to approximate the posterior covariance matrix and describe efficient…

Numerical Analysis · Mathematics 2019-05-22 Arvind K. Saibaba , Julianne Chung , Katrina Petroske

We consider the solution to the biharmonic equation in mixed form discretized by the Hybrid High-Order (HHO) methods. The two resulting second-order elliptic problems can be decoupled via the introduction of a new unknown, corresponding to…

Numerical Analysis · Mathematics 2024-09-06 Paola F. Antonietti , Pierre Matalon , Marco Verani

In this paper, we study the restarted Krylov subspace method, which is typically represented by the GMRES(m) method. Our work mainly focused on the amount of change in the iterative solution of GMRES(m) at each restart. We propose an…

Numerical Analysis · Mathematics 2018-10-25 Hou-biao Li , Peng-hui He , Shao-Liang Zhang

Classical iterative methods for tomographic reconstruction include the class of Algebraic Reconstruction Techniques (ART). Convergence of these stationary linear iterative methods is however notably slow. In this paper we propose the use of…

Numerical Analysis · Mathematics 2015-01-22 Siegfried Cools , Pieter Ghysels , Wim van Aarle , J. Sijbers , Wim Vanroose

This study investigates the iterative regularization properties of two Krylov methods for solving large-scale ill-posed problems: the changing minimal residual Hessenberg method (CMRH) and a novel hybrid variant called the hybrid changing…

Numerical Analysis · Mathematics 2024-11-11 Ariana N. Brown , Malena Sabaté Landman , James G. Nagy

Krylov subspace methods are linear solvers based on matrix-vector multiplications and vector operations. While easily parallelizable, they are sensitive to rounding errors and may experience convergence issues. ILU(0), an incomplete LU…

Numerical Analysis · Mathematics 2025-07-10 Tomonori Kouya

We present a polynomial preconditioner for solving large systems of linear equations. The polynomial is derived from the minimum residual polynomial (the GMRES polynomial) and is more straightforward to compute and implement than many…

Numerical Analysis · Mathematics 2022-01-13 Jennifer A. Loe , Ronald B. Morgan

Solving short and long time dynamics of closed quantum many-body systems is one of the main challenges of both atomic and condensed matter physics. For locally interacting closed systems, the dynamics of local observables can always be…

Quantum Physics · Physics 2025-11-20 Nicolas Loizeau , Berislav Buča , Dries Sels

A general formula is presented for any order derivative of Chebyshev polynomials instead of the existing recursive relationship. Hence, the Chebyshev finite difference method is made applicable not only to second order problems but also to…

Numerical Analysis · Mathematics 2016-09-15 Soner Aydinlik , Ahmet Kiris

We consider the approximation of $B^T (A+sI)^{-1} B$ for large s.p.d. $A\in\mathbb{R}^{n\times n}$ with dense spectrum and $B\in\mathbb{R}^{n\times p}$, $p\ll n$. We target the computations of Multiple-Input Multiple-Output (MIMO) transfer…

Numerical Analysis · Mathematics 2025-04-18 Vladimir Druskin , Jörn Zimmerling

We study energy-conserving Hamiltonian Boundary Value Methods (HBVMs) for Hamiltonian systems, which arise in applications where long-term preservation of energy and symplecticity is essential. HBVMs are multi-stage schemes whose stage…

Numerical Analysis · Mathematics 2026-05-18 Fabio Durastante , Mariarosa Mazza

Most current prevalent iterative methods can be classified into the so-called extended Krylov subspace methods, a class of iterative methods which do not fall into this category are also proposed in this paper. Comparing with traditional…

Numerical Analysis · Mathematics 2015-11-26 Wujian Peng , Qun Lin

This paper investigates iterative methods for solving bi-level optimization problems where both inner and outer functions have a composite structure. We establish novel theoretical results, including the first analysis that provides…

Optimization and Control · Mathematics 2025-10-07 Shimrit Shtern , Adeolu Taiwo

This paper discusses model order reduction of large sparse second-order index-3 differential algebraic equations (DAEs) by applying Iterative Rational Krylov Algorithm (IRKA). In general, such DAEs arise in constraint mechanics, multibody…

Optimization and Control · Mathematics 2021-01-11 Xin Du , M. Monir Uddiny , A. Mostakim Fonyz , Md. Tanzim Hossainx , Md. Nazmul Islam Shuzan

A parallel time integration method for nonlinear partial differential equations is proposed. It is based on a new implementation of the Paraexp method for linear partial differential equations (PDEs) employing a block Krylov subspace…

Numerical Analysis · Mathematics 2015-09-16 G. L. Kooij , M. A. Botchev , B. J. Geurts

We consider the solution of linear saddle-point problems, using the alternating direction method-of-multipliers (ADMM) as a preconditioner for the generalized minimum residual method (GMRES). We show, using theoretical bounds and empirical…

Optimization and Control · Mathematics 2016-04-28 Richard Y. Zhang , Jacob K. White

Efficient simulation of nonlinear and dispersive free-surface flows governed by the incompressible Navier-Stokes equations remains a central challenge in ocean and coastal engineering. The computational bottleneck arises from solving a…

We introduce an iterative solver named MINARES for symmetric linear systems $Ax \approx b$, where $A$ is possibly singular. MINARES is based on the symmetric Lanczos process, like MINRES and MINRES-QLP, but it minimizes $\|Ar_k\|$ in each…

Numerical Analysis · Mathematics 2023-10-04 Alexis Montoison , Dominique Orban , Michael A. Saunders