title: Bringing about matrix sparsity in linear-scaling electronic structure calculations.
abstract: The performance of linear-scaling electronic structure calculations depends critically on matrix sparsity. This article gives an overview of different strategies for removal of small matrix elements, with emphasis on schemes that allow for rigorous control of errors. In particular, a novel scheme is proposed that has significantly smaller computational overhead compared with the Euclidean norm-based truncation scheme of Rubensson et al. (J Comput Chem 2009, 30, 974) while still achieving the desired asymptotic behavior required for linear scaling. Small matrix elements are removed while ensuring that the Euclidean norm of the error matrix stays below a desired value, so that the resulting error in the occupied subspace can be controlled. The efficiency of the new scheme is investigated in benchmark calculations for water clusters including up to 6523 water molecules. Furthermore, the foundation of matrix sparsity is investigated. This includes a study of the decay of matrix element magnitude with distance between basis function centers for different molecular systems and different methods. The studied methods include Hartree–Fock and density functional theory using both pure and hybrid functionals. The relation between band gap and decay properties of the density matrix is also discussed.
authors.affiliation: Division of Scientific Computing, Department of Information Technology, Uppsala University, Uppsala, Sweden. emanuel.rubensson@it.uu.se
authors.forename: Emanuel H
authors.initials: EH
authors.lastname: Rubensson
authors.forename: Elias
authors.initials: E
authors.lastname: Rudberg
mesh_terms: D000465:Algorithms; D004583:Electrons; D015394:Molecular Structure; D011789:Quantum Theory