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Title: Bethe-Salpeter Eigenvalue Solver Package (BSEPACK) v0.1

Abstract

The BSEPACK contains a set of subroutines for solving the Bethe-Salpeter Eigenvalue (BSE) problem. This type of problem arises in this study of optical excitation of nanoscale materials. The BSE problem is a structured non-Hermitian eigenvalue problem. The BSEPACK software can be used to compute all or subset of eigenpairs of a BSE Hamiltonian. It can also be used to compute the optical absorption spectrum without computing BSE eigenvalues and eigenvectors explicitly. The package makes use of the ScaLAPACK, LAPACK and BLAS.

Authors:
;
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE
Contributing Org.:
LAWRENCE BERKELEY NATIONAL LAB
OSTI Identifier:
1352907
Report Number(s):
BSEPACK; 005241WKSTN00
R&D Project: KJ0403000; 2017-032
DOE Contract Number:
AC02-05CH11231
Resource Type:
Software
Software Revision:
00
Software Package Number:
005241
Software CPU:
WKSTN
Open Source:
Yes
Source Code Available:
Yes
Country of Publication:
United States

Citation Formats

SHAO, MEIYEU, and YANG, CHAO. Bethe-Salpeter Eigenvalue Solver Package (BSEPACK) v0.1. Computer software. https://www.osti.gov//servlets/purl/1352907. Vers. 00. USDOE. 25 Apr. 2017. Web.
SHAO, MEIYEU, & YANG, CHAO. (2017, April 25). Bethe-Salpeter Eigenvalue Solver Package (BSEPACK) v0.1 (Version 00) [Computer software]. https://www.osti.gov//servlets/purl/1352907.
SHAO, MEIYEU, and YANG, CHAO. Bethe-Salpeter Eigenvalue Solver Package (BSEPACK) v0.1. Computer software. Version 00. April 25, 2017. https://www.osti.gov//servlets/purl/1352907.
@misc{osti_1352907,
title = {Bethe-Salpeter Eigenvalue Solver Package (BSEPACK) v0.1, Version 00},
author = {SHAO, MEIYEU and YANG, CHAO},
abstractNote = {The BSEPACK contains a set of subroutines for solving the Bethe-Salpeter Eigenvalue (BSE) problem. This type of problem arises in this study of optical excitation of nanoscale materials. The BSE problem is a structured non-Hermitian eigenvalue problem. The BSEPACK software can be used to compute all or subset of eigenpairs of a BSE Hamiltonian. It can also be used to compute the optical absorption spectrum without computing BSE eigenvalues and eigenvectors explicitly. The package makes use of the ScaLAPACK, LAPACK and BLAS.},
url = {https://www.osti.gov//servlets/purl/1352907},
doi = {},
year = {Tue Apr 25 00:00:00 EDT 2017},
month = {Tue Apr 25 00:00:00 EDT 2017},
note =
}

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  • Cited by 9
  • 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 problemsmore » 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.« less
  • The original software package TRLan, [TRLan User Guide], page 24, implements the thick restart Lanczos method, [Wu and Simon 2001], page 24, for computing eigenvalues {lambda} and their corresponding eigenvectors v of a symmetric matrix A: Av = {lambda}v. Its effectiveness in computing the exterior eigenvalues of a large matrix has been demonstrated, [LBNL-42982], page 24. However, its performance strongly depends on the user-specified dimension of a projection subspace. If the dimension is too small, TRLan suffers from slow convergence. If it is too large, the computational and memory costs become expensive. Therefore, to balance the solution convergence and costs,more » users must select an appropriate subspace dimension for each eigenvalue problem at hand. To free users from this difficult task, nu-TRLan, [LNBL-1059E], page 23, adjusts the subspace dimension at every restart such that optimal performance in solving the eigenvalue problem is automatically obtained. This document provides a user guide to the nu-TRLan software package. The original TRLan software package was implemented in Fortran 90 to solve symmetric eigenvalue problems using static projection subspace dimensions. nu-TRLan was developed in C and extended to solve Hermitian eigenvalue problems. It can be invoked using either a static or an adaptive subspace dimension. In order to simplify its use for TRLan users, nu-TRLan has interfaces and features similar to those of TRLan: (1) Solver parameters are stored in a single data structure called trl-info, Chapter 4 [trl-info structure], page 7. (2) Most of the numerical computations are performed by BLAS, [BLAS], page 23, and LAPACK, [LAPACK], page 23, subroutines, which allow nu-TRLan to achieve optimized performance across a wide range of platforms. (3) To solve eigenvalue problems on distributed memory systems, the message passing interface (MPI), [MPI forum], page 23, is used. The rest of this document is organized as follows. In Chapter 2 [Installation], page 2, we provide an installation guide of the nu-TRLan software package. In Chapter 3 [Example], page 3, we present a simple nu-TRLan example program. In Chapter 4 [trl-info structure], page 7, and Chapter 5 [trlan subroutine], page 14, we describe the solver parameters and interfaces in detail. In Chapter 6 [Solver parameters], page 21, we discuss the selection of the user-specified parameters. In Chapter 7 [Contact information], page 22, we give the acknowledgements and contact information of the authors. In Chapter 8 [References], page 23, we list reference to related works.« less

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