SLEPc: A scalable and flexible toolkit for the solution of eigenvalue problems
By Vicente Hernández, José E. Román, V. Vidal. TOMS, 2005
1,139 citations recorded by the source corpus.
Subfields: Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/57a795187ee5b28ea07f3747b40916e874390117
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In Atomic and Molecular Physics, and Optics
- Zhouchen Lin
- Zoltán Fodor
- Sándor D. Katz
- Karen E. Willcox
- John Wright
- Arvind Krishna Saibaba
- Gianmarco Manzini
- Arvind Ganesh
In Computational Theory and Mathematics
- Robert Eymard
- Raphaèle Herbin
- Karen E. Willcox
- Gianmarco Manzini
- B. V. B. Waanders
- John Wright
- Arvind Krishna Saibaba
- Florence Hubert
In Statistical and Nonlinear Physics
- Karen E. Willcox
- B. V. B. Waanders
- John Wright
- Arvind Krishna Saibaba
- Gianmarco Manzini
- Arvind Ganesh
- Chih-Jen Lin
- Omar Ghattas
Citations in the corpus
- The FEniCS Project Version 1.5 (2015, background): “In this release, support for the Trilinos Epetra backend has been removed.”
- 3D Benchmark on Discretization Schemes for Anisotropic Diffusion Problems on General Grids (2008, methodology): “For the approximate calculation of the condition number of a given matrix, the Krylov-Schur method from the Scalable Library for Eigenvalue Problem Computations (SLEPc) package version 3.1-p4 [ 22 ] was used.”
- Leading hadronic contribution to the muon magnetic moment from lattice QCD (2020, background): “60(37)(89) iso 27.175(28)(13) 206.19(0.20)(1.37) -0.906(42)(90) qed -0.0050(35)(37) 0.082(46)(34) -0.115(17)(07) qed-vv -0.0018(14)(10) 0.067(30)(21) -0.114(18)(05) qed-sv -0.00142(60)(30) -0.0222(91)(52) 0.0013(23)(00) qed-ss -0.0018(31)(38) 0.033(30)(39) -0.0027(26)(22) sib { 0.757(40)(16) -0.238(”
- Fast Convex Optimization Algorithms for Exact Recovery of a Corrupted Low-Rank Matrix (2009, methodology): “There has also been significant progress recently in developing parallelized algorithms for SVD computations [24, 13, 11].”
- CellRank for directed single-cell fate mapping (2020, neutral): “j,k=1 H (i) j,k E[(v − μ)j(v − μ)k] , (28)”
- Parallel Spectral Clustering in Distributed Systems (2011, background): “Some example solvers are SLEPc [21] and ARPACK [22] (see [20] for a comprehensive survey).”
- Efficient methods for large‐scale linear inversion using a geostatistical approach (2012, methodology): “We compute the extreme eigenvalues using the Krylov-Schur algorithm accessed via the SLEPc package [Hernandez et al., 2005].”
- Hessian‐based model reduction for large‐scale systems with initial‐condition inputs (2008, methodology): “Eigenvectors were computed using the Arnoldi eigensolver within the SLEPc package [33], which is built on PETSc.”