Sparse Matrix Algebra for Quantum Modeling of Large Systems

  • Emanuel H. Rubensson
  • Elias Rudberg
  • Paweł Sałek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4699)


Matrices appearing in Hartree–Fock or density functional theory coming from discretization with help of atom–centered local basis sets become sparse when the separation between atoms exceeds some system–dependent threshold value. Efficient implementation of sparse matrix algebra is therefore essential in large–scale quantum calculations. We describe a unique combination of algorithms and data representation that provides high performance and strict error control in blocked sparse matrix algebra. This has applications to matrix–matrix multiplication, the Trace–Correcting Purification algorithm and the entire self–consistent field calculation.


Block Size Sparse Matrice Diagonalization Method Hierarchic Data Structure Truncation Threshold 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Emanuel H. Rubensson
    • 1
    • 2
  • Elias Rudberg
    • 1
    • 3
  • Paweł Sałek
    • 1
  1. 1.Department of Theoretical Chemistry, Royal Institute of Technology, SE-10691 StockholmSweden
  2. 2.Department of Physics and Chemistry, University of Southern Denmark, DK-5230 Odense MDenmark
  3. 3.Department of Chemistry, University of Warwick, Coventry CV4 7ALUK

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