225 research outputs found
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
On the Convergence of the Self-Consistent Field Iteration in Kohn-Sham Density Functional Theory
It is well known that the self-consistent field (SCF) iteration for solving
the Kohn-Sham (KS) equation often fails to converge, yet there is no clear
explanation. In this paper, we investigate the SCF iteration from the
perspective of minimizing the corresponding KS total energy functional. By
analyzing the second-order Taylor expansion of the KS total energy functional
and estimating the relationship between the Hamiltonian and the part of the
Hessian which is not used in the SCF iteration, we are able to prove global
convergence from an arbitrary initial point and local linear convergence from
an initial point sufficiently close to the solution of the KS equation under
assumptions that the gap between the occupied states and unoccupied states is
sufficiently large and the second-order derivatives of the exchange correlation
functional are uniformly bounded from above. Although these conditions are very
stringent and are almost never satisfied in reality, our analysis is
interesting in the sense that it provides a qualitative prediction of the
behavior of the SCF iteration
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