Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
522771 | Journal of Computational Physics | 2006 | 13 Pages |
Abstract
A new direct constrained optimization algorithm for minimizing the Kohn–Sham (KS) total energy functional is presented in this paper. The key ingredients of this algorithm involve projecting the total energy functional into a sequence of subspaces of small dimensions and seeking the minimizer of total energy functional within each subspace. The minimizer of a subspace energy functional not only provides a search direction along which the KS total energy functional decreases but also gives an optimal “step-length” to move along this search direction. Numerical examples are provided to demonstrate that this new direct constrained optimization algorithm can be more efficient than the self-consistent field (SCF) iteration.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Chao Yang, Juan C. Meza, Lin-Wang Wang,