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Preconditioners for Krylov subspace methods: An overview
When simulating a mechanism from science or engineering, or an industrial process, one is
frequently required to construct a mathematical model, and then resolve this model …
frequently required to construct a mathematical model, and then resolve this model …
Analysis of the truncated conjugate gradient method for linear matrix equations
The matrix-oriented version of the conjugate gradient (CG) method can be used to
approximate the solution to certain linear matrix equations. To limit memory consumption …
approximate the solution to certain linear matrix equations. To limit memory consumption …
Matrix equation techniques for certain evolutionary partial differential equations
We show that the discrete operator stemming from time-space discretization of evolutionary
partial differential equations can be represented in terms of a single Sylvester matrix …
partial differential equations can be represented in terms of a single Sylvester matrix …
A tensor multigrid method for solving Sylvester tensor equations
Y Chen, C Li - IEEE Transactions on Automation Science and …, 2023 - ieeexplore.ieee.org
In this paper, we propose a tensor multigrid method and an iterative tensor multigrid method
to solve the Sylvester tensor equations which may arise from the discretization of high order …
to solve the Sylvester tensor equations which may arise from the discretization of high order …
Compress‐and‐restart block Krylov subspace methods for Sylvester matrix equations
Summary Block Krylov subspace methods (KSMs) comprise building blocks in many state‐of‐
the‐art solvers for large‐scale matrix equations as they arise, for example, from the …
the‐art solvers for large‐scale matrix equations as they arise, for example, from the …
Risk-Adaptive Experimental Design for High-Consequence Systems: LDRD Final Report
DP Kouri, JD Jakeman, JG Huerta, CB Smith, TF Walsh… - 2021 - osti.gov
Constructing accurate statistical models of critical system responses typically requires an
enormous amount of data from physical experiments or numerical simulations …
enormous amount of data from physical experiments or numerical simulations …
[PDF][PDF] Schwarz methods, Schur complements, preconditioning and numerical linear algebra
M Outrata - 2022 - archive-ouverte.unige.ch
This thesis can be divided into two parts:(optimized) Schwarz methods and related topics
and preconditioning of the stage equations of implicit Runge-Kutta methods. Schwarz …
and preconditioning of the stage equations of implicit Runge-Kutta methods. Schwarz …
Spectral analysis of implicit 2 stage block Runge-Kutta preconditioners
We analyze the recently introduced family of preconditioners in [15] for the stage equations
of implicit Runge-Kutta methods for two stage methods. We give explicit formulas for the …
of implicit Runge-Kutta methods for two stage methods. We give explicit formulas for the …
Sylvester-Preconditioned Adaptive-Rank Implicit Time Integrators for Advection-Diffusion Equations with Inhomogeneous Coefficients
We consider the adaptive-rank integration of general time-dependent advection-diffusion
partial differential equations (PDEs) with spatially variable coefficients. We employ a …
partial differential equations (PDEs) with spatially variable coefficients. We employ a …
A subspace-conjugate gradient method for linear matrix equations
The efficient solution of large-scale multiterm linear matrix equations is a challenging task in
numerical linear algebra, and it is a largely open problem. We propose a new iterative …
numerical linear algebra, and it is a largely open problem. We propose a new iterative …