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Main Authors: Dayton, Aaron, Gallagher, Kiana, Huber, Sarah E., Baker, Thomas E.
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2604.25625
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author Dayton, Aaron
Gallagher, Kiana
Huber, Sarah E.
Baker, Thomas E.
author_facet Dayton, Aaron
Gallagher, Kiana
Huber, Sarah E.
Baker, Thomas E.
contents Making new methods for quantum problems often relies on using basic operations in linear algebra. Often these routines are hidden behind well-known libraries that have been optimized over decades. Attempting to improve on those basic routines would be highly time-consuming. We aim in this article to review those basic routines and provide a knowledge foundation for how to perform basic operations on a computer that would be inaccessible with pen and paper. Elementary details on the solutions to linear algebra problems and computational complexity are reviewed. The focus is on solving eigenvalue problems for quantum systems, but the discussion is generic to many other applications. Common matrix forms relevant to quantum systems and their solution strategies are covered. The discussion extends to computational numerical methods for which the most efficient functions exist in freely available libraries. These include eigenvalue, Schur, QR, LU, LDL, Cholesky, and singular value decompositions. The algorithms for obtaining some of these decompositions are discussed, with focus being placed on those used in modern libraries.
format Preprint
id arxiv_https___arxiv_org_abs_2604_25625
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Basic linear algebra methods for quantum problems
Dayton, Aaron
Gallagher, Kiana
Huber, Sarah E.
Baker, Thomas E.
Computational Physics
Making new methods for quantum problems often relies on using basic operations in linear algebra. Often these routines are hidden behind well-known libraries that have been optimized over decades. Attempting to improve on those basic routines would be highly time-consuming. We aim in this article to review those basic routines and provide a knowledge foundation for how to perform basic operations on a computer that would be inaccessible with pen and paper. Elementary details on the solutions to linear algebra problems and computational complexity are reviewed. The focus is on solving eigenvalue problems for quantum systems, but the discussion is generic to many other applications. Common matrix forms relevant to quantum systems and their solution strategies are covered. The discussion extends to computational numerical methods for which the most efficient functions exist in freely available libraries. These include eigenvalue, Schur, QR, LU, LDL, Cholesky, and singular value decompositions. The algorithms for obtaining some of these decompositions are discussed, with focus being placed on those used in modern libraries.
title Basic linear algebra methods for quantum problems
topic Computational Physics
url https://arxiv.org/abs/2604.25625