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Title: Structure preserving parallel algorithms for solving the Bethe–Salpeter eigenvalue problem

The Bethe–Salpeter eigenvalue problem is a dense structured eigenvalue problem arising from discretized Bethe–Salpeter equation in the context of computing exciton energies and states. A computational challenge is that at least half of the eigenvalues and the associated eigenvectors are desired in practice. In this paper, we establish the equivalence between Bethe–Salpeter eigenvalue problems and real Hamiltonian eigenvalue problems. Based on theoretical analysis, structure preserving algorithms for a class of Bethe–Salpeter eigenvalue problems are proposed. We also show that for this class of problems all eigenvalues obtained from the Tamm–Dancoff approximation are overestimated. In order to solve large scale problems of practical interest, we discuss parallel implementations of our algorithms targeting distributed memory systems. Finally, several numerical examples are presented to demonstrate the efficiency and accuracy of our algorithms.
ORCiD logo [1] ;  [2] ;  [1] ;  [1] ;  [2]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Univ. of California, Berkeley, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Linear Algebra and Its Applications
Additional Journal Information:
Journal Volume: 488; Journal ID: ISSN 0024-3795
Research Org:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21); USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
Contributing Orgs:
Univ. of California, Berkeley, CA (United States)
Country of Publication:
United States
97 MATHEMATICS AND COMPUTING; Bethe–Salpeter equation; Tamm–Dancoff approximation; Hamiltonian eigenvalue problems; Structure preserving algorithms; Parallel algorithms
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1359511