Automatic Differentiation for the Direct Minimization Approach to the Hartree–Fock Method

  • Naruki Yoshikawa
    Department of Computer Science, University of Toronto, 40 St. George Street, Toronto, Ontario M5S 2E4, Canada
  • Masato Sumita
    Center for Advanced Intelligence Project, RIKEN, 1-4-1 Nihombashi, Chuo-ku, Tokyo 103-0027, Japan

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Automatic differentiation has become an important tool for optimization problems in computational science, and it has been applied to the Hartree-Fock method. Although the reverse-mode automatic differentiation is more efficient than the forward-mode, eigenvalue calculation in the self-consistent field method has impeded the use of the reverse-mode automatic differentiation. Here, we propose a method to directly minimize Hartree-Fock energy under the orthonormality constraint of the molecular orbitals using reverse-mode automatic differentiation by avoiding eigenvalue calculation. According to our validation, the proposed method was more stable than the conventional self-consistent field method and achieved comparable accuracy.

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