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Pseudodiagonalization Method for Accelerating Nonlinear Subspace Diagonalization in Density Functional Theory

Journal Article · · Journal of Chemical Theory and Computation
 [1];  [2];  [2]
  1. Georgia Institute of Technology, Atlanta, GA (United States); Georgia Institute of Technology
  2. Georgia Institute of Technology, Atlanta, GA (United States)
In density functional theory, each self-consistent field (SCF) nonlinear step updates the discretized Kohn-Sham orbitals by solving a linear eigenvalue problem. The concept of pseudodiagonalization is to solve this linear eigenvalue problem approximately, and specifically utilizing a method involving a small number of Jacobi rotations that takes advantage of the good initial guess to the solution given by the approximation to the orbitals from the previous SCF iteration. The approximate solution to the linear eigenvalue problem can be very rapid, particularly for those steps near SCF convergence. Here, we adapt pseudodiagonalization to finite-temperature and metallic systems, where partially-occupied orbitals must be individually resolved with some accuracy. We apply pseudodiagonalization to the subspace eigenvalue problem that arises in Chebyshev-filtered subspace iteration. In tests on metallic and other systems for a range of temperatures, we show that pseudodiagonalization achieves similar rates of SCF convergence to exact diagonalization.
Research Organization:
Georgia Institute of Technology, Atlanta, GA (United States). Georgia Tech Research Institute
Sponsoring Organization:
National Science Foundation (NSF); USDOE Office of Science (SC), Basic Energy Sciences (BES)
Grant/Contract Number:
SC0019410
OSTI ID:
1988390
Alternate ID(s):
OSTI ID: 1977928
Journal Information:
Journal of Chemical Theory and Computation, Journal Name: Journal of Chemical Theory and Computation Journal Issue: 6 Vol. 18; ISSN 1549-9618
Publisher:
American Chemical SocietyCopyright Statement
Country of Publication:
United States
Language:
English

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