Unconstrained and Constrained Minimization, Linear Scaling, and the Grassmann Manifold: Theory and Applications
An unconstrained minimization algorithm for electronic structure calculations using density functional for systems with a gap is developed to solve for nonorthogonal Wannier-like orbitals in the spirit of E. B. Stechel, A. R. Williams, and P. J. Feibelman, Phys. Rev. B 49, 10,008 (1994). The search for the occupied sub-space is a Grassmann conjugate gradient algorithm generalized from the algorithm of A. Edelman, T.A. Arias, and S. T. Smith, SIAM J. on Matrix Anal. Appl. 20, 303 (1998). The gradient takes into account the nonorthogonality of a local atom-centered basis, gaussian in their implementation. With a localization constraint on the Wannier-like orbitals, well-constructed sparse matrix multiplies lead to O(N) scaling of the computationally intensive parts of the algorithm. Using silicon carbide as a test system, the accuracy, convergence, and implementation of this algorithm as a quantitative alternative to diagonalization are investigated. Results up to 1,458 atoms on a single processor are presented.
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States)
- Sponsoring Organization:
- US Department of Energy (US)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 759995
- Report Number(s):
- SAND2000-1909J; TRN: AH200032%%57
- Journal Information:
- Physical Review B, Other Information: Submitted to Physical Review B; PBD: 19 Jul 2000
- Country of Publication:
- United States
- Language:
- English
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