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Polynomial Krylov subspace methods are among the most widely used methods for approximating $f(A)b$, the action of a matrix function on a vector, in particular when $A$ is large and sparse. When $A$ is Hermitian positive definite, the…

Numerical Analysis · Mathematics 2025-03-07 Marcel Schweitzer

The resolvent Krylov subspace method builds approximations to operator functions $f(A)$ times a vector $v$. For the semigroup and related operator functions, this method is proved to possess the favorable property that the convergence is…

Numerical Analysis · Mathematics 2019-07-15 Volker Grimm , Tanja Göckler

We develop an algorithm for computing the solution of a large system of linear ordinary differential equations (ODEs) with polynomial inhomogeneity. This is equivalent to computing the action of a certain matrix function on the vector…

Numerical Analysis · Mathematics 2012-05-16 Jitse Niesen , Will M. Wright

In this work, we propose a reduced basis method for efficient solution of parametric linear systems. The coefficient matrix is assumed to be a linear matrix-valued function that is symmetric and positive definite for admissible values of…

Numerical Analysis · Mathematics 2021-09-28 Antti Autio , Antti Hannukainen

We develop a novel convergence analysis of the classical deterministic block Krylov methods for the approximation of $h$-dimensional dominant subspaces and low-rank approximations of matrices $ A\in\mathbb K^{m\times n}$ (where $\mathbb…

Numerical Analysis · Mathematics 2024-08-22 Pedro Massey

In this paper we present deflation and augmentation techniques that have been designed to accelerate the convergence of Krylov subspace methods for the solution of linear systems of equations. We review numerical approaches both for linear…

Numerical Analysis · Mathematics 2013-03-25 Olivier Coulaud , Luc Giraud , Pierre Ramet , Xavier Vasseur

An efficient and robust linear scaling method is presented for large scale {\it ab initio} electronic structure calculations of a wide variety of materials including metals. The detailed short range and the effective long range…

Other Condensed Matter · Physics 2016-08-31 Taisuke Ozaki

Several Krylov-type procedures are introduced that generalize matrix Krylov methods for tensor computations. They are denoted minimal Krylov recursion, maximal Krylov recursion, contracted tensor product Krylov recursion. It is proved that…

Numerical Analysis · Mathematics 2010-05-07 Berkant Savas , Lars Eldén

We consider a Krylov subspace approximation method for the symmetric differential Riccati equation $\dot{X} = AX + XA^T + Q - XSX$, $X(0)=X_0$. The method we consider is based on projecting the large scale equation onto a Krylov subspace…

Numerical Analysis · Mathematics 2021-06-24 Antti Koskela , Hermann Mena

We use a continued fraction expansion of the sign-function in order to obtain a five dimensional formulation of the overlap lattice Dirac operator. Within this formulation the inverse of the overlap operator can be calculated by a single…

High Energy Physics - Lattice · Physics 2007-05-23 Urs Wenger

A coarse grid correction (CGC) approach is proposed to enhance the efficiency of the matrix exponential and $\varphi$ matrix function evaluations. The approach is intended for iterative methods computing the matrix-vector products with…

Numerical Analysis · Mathematics 2024-04-23 Mike A. Botchev

A class of second-order algorithms is proposed for minimizing smooth nonconvex functions that alternates between regularized Newton and negative curvature steps in an iteration-dependent subspace. In most cases, the Hessian matrix is…

Optimization and Control · Mathematics 2023-08-22 Serge Gratton , Sadok Jerad , Philippe L. Toint

In this paper, we consider an efficient iterative approach to the solution of the discrete Helmholtz equation with Dirichlet, Neumann and Sommerfeld-like boundary conditions based on a compact sixth order approximation scheme and…

Numerical Analysis · Mathematics 2012-12-07 Yury Gryazin

In analogy to Neuberger's double-pass algorithm for the Conjugate Gradient inversion with multi-shifts we introduce a double-pass variant for BiCGstab(ell). One possible application is the overlap operator of QCD at non-zero chemical…

High Energy Physics - Lattice · Physics 2011-01-27 Simon Heybrock

It is well known that the block Krylov subspace solvers work efficiently for some cases of the solution of differential equations with multiple right-hand sides. In lattice QCD calculation of physical quantities on a given configuration…

High Energy Physics - Lattice · Physics 2009-12-04 T. Sakurai , H. Tadano , Y. Kuramashi

In the present paper, we present some numerical methods for computing approximate solutions to some large differential linear matrix equations. In the first part of this work, we deal with differential generalized Sylvester matrix equations…

Numerical Analysis · Computer Science 2018-05-28 M. Hached , K. Jbilou

A new algorithm to approximate Hermitian matrices by positive semidefinite Hermitian matrices based on modified Cholesky decompositions is presented. In contrast to existing algorithms, this algorithm allows to specify bounds on the…

Numerical Analysis · Mathematics 2019-12-12 Joscha Reimer

Different recently developed Krylov space methods for solving linear systems are studied and compared for the solution of the Dirac equation on the lattice. Stabilized Biconjugate Gradient (BiCGstab2) is shown to be a robust and efficient…

High Energy Physics - Lattice · Physics 2007-05-23 Artan Boriçi , Philippe de Forcrand

This paper describes practical randomized algorithms for low-rank matrix approximation that accommodate any budget for the number of views of the matrix. The presented algorithms, which are aimed at being as pass efficient as needed, expand…

Numerical Analysis · Mathematics 2018-05-25 Elvar K. Bjarkason

In the numerical solution of the algebraic Riccati equation $A^* X + X A - X BB^* X + C^* C =0$, where $A$ is large, sparse and stable, and $B$, $C$ have low rank, projection methods have recently emerged as a possible alternative to the…

Numerical Analysis · Mathematics 2016-02-02 V. Simoncini
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