Results 21 to 30 of about 641 (184)
Sampling Error Analysis in Quantum Krylov Subspace Diagonalization [PDF]
QuantumQuantum Krylov subspace diagonalization (QKSD) is an emerging method used in place of quantum phase estimation in the early fault-tolerant era, where limited quantum circuit depth is available. In contrast to the classical Krylov subspace diagonalization
Gwonhak Lee, Dongkeun Lee, Joonsuk Huh
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Preserving Symmetry in Preconditioned Krylov Subspace Methods [PDF]
SIAM Journal on Scientific Computing, 1998 The authors consider the problem of solving linear systems of equations with coefficient matrices which are ``nearly'' (very close to be) symmetric and when symmetric positive definite preconditioners are used. They show that it is possible to improve upon the standard practice of using nonsymmetric preconditioners for that matrices along with a left ...
Tony F. Chan +3 more
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A Geometric Multigrid Method for 3D Magnetotelluric Forward Modeling Using Finite-Element Method
Remote Sensing, 2023 The traditional three-dimensional (3D) magnetotelluric (MT) forward modeling using Krylov subspace algorithms has the problem of low modeling efficiency.
Xianyang Huang +8 more
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A Framework for Deflated and Augmented Krylov Subspace Methods [PDF]
SIAM Journal on Matrix Analysis and Applications, 2013 We consider deflation and augmentation techniques for accelerating the convergence of Krylov subspace methods for the solution of nonsingular linear algebraic systems. Despite some formal similarity, the two techniques are conceptually different from preconditioning.
André Gaul +3 more
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Extending quasi-GMRES method to solve generalized Sylvester tensor equations via the Einstein product [PDF]
Iranian Journal of Numerical Analysis and OptimizationThis paper aims to extend a Krylov subspace technique based on an in-complete orthogonalization of Krylov tensors (as a multidimensional exten-sion of the common Krylov vectors) to solve generalized Sylvester tensor equations via the Einstein product ...
M.M. Izadkhah
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On Numerical Approximations of the Koopman Operator
Mathematics, 2022 We study numerical approaches to computation of spectral properties of composition operators. We provide a characterization of Koopman Modes in Banach spaces using Generalized Laplace Analysis.
Igor Mezić
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Flexible Inner-Outer Krylov Subspace Methods [PDF]
SIAM Journal on Numerical Analysis, 2002 Flexible Krylov methods refer to a class of methods which accept preconditioning that can change from one step to the next. An important special case is found when a fixed preconditioner is only approximated and the approximation changes from one step to the next.
Simoncini V., Szyld D. B.
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Structural Reliability Analysis Using Stochastic Finite Element Method Based on Krylov Subspace
AlgorithmsThe stochastic finite element method is an important tool for structural reliability analysis. In order to improve the calculation efficiency, a stochastic finite element method based on the Krylov subspace is proposed for the static reliability analysis
Jianyun Huang +3 more
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Reduced-Rank Adaptive Filtering Using Krylov Subspace
EURASIP Journal on Advances in Signal Processing, 2002 A unified view of several recently introduced reduced-rank adaptive filters is presented. As all considered methods use Krylov subspace for rank reduction, the approach taken in this work is inspired from Krylov subspace methods for iterative solutions ...
Burykh Sergueï, Abed-Meraim Karim
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Krylov Subspace Methods in the Electronic Industry [PDF]
, 2006 In most practical cases, the convergence of the GMRES method applied to a linear algebraic system Ax -- b is determined by the distribution of eigenvalues of A. In theory, however, the information about the eigenvalues alone is not sufficient for determining the convergence. In this paper the previous work of Greenbaum et al.
Heres, P.J., Schilders, W.H.A.
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