754 research outputs found
Adaptive Finite Element Approximations for Kohn-Sham Models
The Kohn-Sham equation is a powerful, widely used approach for computation of
ground state electronic energies and densities in chemistry, materials science,
biology, and nanosciences. In this paper, we study the adaptive finite element
approximations for the Kohn-Sham model. Based on the residual type a posteriori
error estimators proposed in this paper, we introduce an adaptive finite
element algorithm with a quite general marking strategy and prove the
convergence of the adaptive finite element approximations. Using D{\" o}rfler's
marking strategy, we then get the convergence rate and quasi-optimal
complexity. We also carry out several typical numerical experiments that not
only support our theory,but also show the robustness and efficiency of the
adaptive finite element computations in electronic structure calculations.Comment: 38pages, 7figure
Gradient type optimization methods for electronic structure calculations
The density functional theory (DFT) in electronic structure calculations can
be formulated as either a nonlinear eigenvalue or direct minimization problem.
The most widely used approach for solving the former is the so-called
self-consistent field (SCF) iteration. A common observation is that the
convergence of SCF is not clear theoretically while approaches with convergence
guarantee for solving the latter are often not competitive to SCF numerically.
In this paper, we study gradient type methods for solving the direct
minimization problem by constructing new iterations along the gradient on the
Stiefel manifold. Global convergence (i.e., convergence to a stationary point
from any initial solution) as well as local convergence rate follows from the
standard theory for optimization on manifold directly. A major computational
advantage is that the computation of linear eigenvalue problems is no longer
needed. The main costs of our approaches arise from the assembling of the total
energy functional and its gradient and the projection onto the manifold. These
tasks are cheaper than eigenvalue computation and they are often more suitable
for parallelization as long as the evaluation of the total energy functional
and its gradient is efficient. Numerical results show that they can outperform
SCF consistently on many practically large systems.Comment: 24 pages, 11 figures, 59 references, and 1 acknowledgement
- …