Kernel polynomial approximations for densities of states and spectral functions
- Los Alamos National Laboratory, NM (United States)
- Universitaet Bayreuth (Germany)
Chebyshev polynomial approximations are an efficient and numerically stable way to calculate properties of the very large Hamiltonians important in computational condensed matter physics. The present paper derives an optimal kernal polynomial which enforces positivity of density of states and spectral estimates, achieves the best energy resolution, and preserves normalization. This kernel polynomial method (KPM) is demonstrated for electronic structure and dynamic magnetic susceptibility calculations. For tight binding Hamiltonians of Si, we show how to achieve high precision and rapid convergence of the cohesive energy and vacancy formation energy by careful attention to the order of approximation. For disordered XXZ-magnets, we show that the KPM provides a simpler and more reliable procedure for calculating spectral functions than Lanczos recursion methods. Polynomial approximations to Fermi projection operators are also proposed. 26 refs., 10 figs.
- OSTI ID:
- 274228
- Journal Information:
- Journal of Computational Physics, Vol. 124, Issue 1; Other Information: PBD: 1 Mar 1996
- Country of Publication:
- United States
- Language:
- English
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