A fast, low memory cost, Krylov-space-based algorithm is proposed for the diagonalization of large Hamiltonian matrices required in time-dependent Hartree–Fock (TDHF) and adiabatic time-dependent density-functional theory (TDDFT) computations of electronic excitations. A deflection procedure based on the symplectic structure of the TDHF equations is introduced and its capability to find higher eigenmodes of the linearized TDHF operator for a given numerical accuracy is demonstrated. The algorithm may be immediately applied to the formally-identical adiabatic TDDFT equations.
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Chernyak et al. (2000) studied this question.
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