A robust, open-source implementation of the locally optimal block preconditioned conjugate gradient for large eigenvalue problems in quantum chemistry
In: ISSN: 1432-881X ; EISSN: 1432-2234, 2023
Online
academicJournal
Zugriff:
International audience ; We present two open-source implementations of the Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) algorithm to find a few eigenvalues and eigenvectors of large, possibly sparse matrices. We then test LOBPCG for various quantum chemistry problems, encompassing medium to large, dense to sparse, wellbehaved to ill-conditioned ones, where the standard method typically used is Davidson's diagonalization. Numerical tests show that, while Davidson's method remains the best choice for most applications in quantum chemistry, LOBPCG represents a competitive alternative, especially when memory is an issue, and can even outperform Davidson for ill-conditioned, non diagonally dominant problems.
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A robust, open-source implementation of the locally optimal block preconditioned conjugate gradient for large eigenvalue problems in quantum chemistry
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Autor/in / Beteiligte Person: | Nottoli, Tommaso ; Giannı̀, Ivan ; Levitt, Antoine ; Lipparini, Filippo ; University of Pisa - Università di Pisa ; Laboratoire de Mathématiques d'Orsay (LMO) ; Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) |
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Zeitschrift: | ISSN: 1432-881X ; EISSN: 1432-2234, 2023 |
Veröffentlichung: | HAL CCSD ; Springer Verlag, 2023 |
Medientyp: | academicJournal |
DOI: | 10.1007/s00214-023-03010-y |
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