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Showing 1 to 9 of 9 for “"Lanczos method"”.
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Fast algorithms for Brownian dynamics simulation with hydrodynamic interactions
… we first present two fast multipole methods (FMM) for computing Du. The first FMM is a simple application of the kernel independent FMM (KIFMM) developed by Ying, Biros, and Zorin [3], which requires 9 scalar FMM calls. The second FMM, similar to the FMM for Stokeslet developed by …
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Convergence of the Arnoldi Iteration for Estimating Extreme Eigenvalues
Krylov subspace methods, like the Arnoldi iteration, are a powerful tool for efficiently solving high-dimensional linear algebra problems. In this work, we analyze the convergence of Krylov methods for estimating the numerical range of a matrix. Prior bounds on approximation error often depend on …
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Integração direta da resposta em regime permanente pelo Método de Ritz-Wilson com mudança de base
… to allow the application of the Ritz-Wilson method in the solution of dynamic response due to generic load cases. The final purpose of this work is the use of both procedures in the dynamic analysis of structural systems subject to generalized periodic excitations. Some basic ideas of the …
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Graphs, Principal Minors, and Eigenvalue Problems
… low diameter graphs. Finally, we consider the Lanczos method for computing extremal eigenvalues of a symmetric matrix and produce new error estimates for this algorithm.
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A new block Krylov subspace framework with applications to functions of matrices acting on multiple vectors
… for understanding block Krylov subspace methods, which hinges on a matrix-valued inner product. We can recast the ``classical" block Krylov methods, such as O'Leary's block conjugate gradients, global methods, and loop-interchange methods, within this framework. Leveraging the generality …
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Application of advanced diagonalization methods to quantum spin systems.
… diagonalization. In this approach, numerical methods are used to find the lowest eigenvalues and associated eigenvectors of the Hamilton matrix of the quantum system. The computational problem is thus to determine the lowest eigenpairs of an extremely large, sparse matrix. Although many …
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Recycling Bi-Lanczos Algorithms: BiCG, CGS, and BiCGSTAB
… of linear systems to the next pair. Augmented bi-Lanczos algorithm and modified two-term recurrence are developed for using the recycle space. Recycle space is built from the approximate invariant subspace corresponding to eigenvalues close to the origin. Recycling approach is extended to the CGS …
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Recycling Krylov Subspaces and Preconditioners
… Besides the benefit of only having to store few Lanczos vectors, using BiConjugate Gradients (BiCG) to solve dual linear systems may have application-specific advantages. For example, using BiCG to solve the dual linear systems arising in interpolatory model reduction provides a backward error …