Results 21 to 30 of about 629 (136)
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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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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Uzawa Algorithms for Fully Fuzzy Linear Systems
International Journal of Computational Intelligence Systems, 2016 Recently, there have been many studies on solving different kinds of fuzzy equations. In this paper, the solution of a trapezoidal fully fuzzy linear system (FFLS) is studied.
H. Zareamoghaddam +3 more
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Quantum Power Method by a Superposition of Time-Evolved States
PRX Quantum, 2021 We propose a quantum-classical hybrid algorithm of the power method, here dubbed as the quantum power method, to evaluate H[over ^]^{n}|ψ⟩ with quantum computers, where n is a non-negative integer, H[over ^] is a time-independent Hamiltonian of interest,
Kazuhiro Seki, Seiji Yunoki
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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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Application of Krylov Reduction Technique for a Machine Tool Multibody Modelling
Advances in Mechanical Engineering, 2014 Quick calculation of machine tool dynamic response represents one of the major requirements for machine tool virtual modelling and virtual machining, aiming at simulating the machining process performance, quality, and precision of a workpiece.
M. Sulitka +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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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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Explicit‐Implicit Material Point Method for Dense Granular Flows With a Novel Regularized µ(I) Model
International Journal for Numerical and Analytical Methods in Geomechanics, EarlyView.ABSTRACT The material point method (MPM) is widely employed to simulate granular flows. Although explicit time integration is favored in most current MPM implementations for its simplicity, it cannot rigorously incorporate the incompressible µ(I)‐rheology, an efficient model ubiquitously adopted in other particle‐based numerical methods. While operator‐
Hang Feng, Zhen‐Yu Yin
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ILU preconditioning based on the FAPINV algorithm [PDF]
Opuscula Mathematica, 2015 A technique for computing an ILU preconditioner based on the factored approximate inverse (FAPINV) algorithm is presented. We show that this algorithm is well-defined for H-matrices.
Davod Khojasteh Salkuyeh +2 more
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