Exploiting the hessian for a better convergence of the SCF RDMFT procedure

Abstract

One-body reduced density matrix functional theory (RDMFT) provides an alternative to Density Functional Theory (DFT), able to treat static correlation while keeping a relatively low computation scaling. Its disadvantageous cost comes mainly from a slow convergence of the self-consistent energy optimisation. To improve on that problem, we propose in this work to use the hessian of the energy, including the coupling term. We show that using the exact hessian is very effective in reducing the number of iterations. However, since the exact hessian is too expensive to use in practice, we test different approximations based on an inexpensive exact part and/or BFGS updates.

21 pages, 12 figures, published in JCTC, GitHub code: https://github.com/NGCartier/SCF-RDMFT_Hess_investigation/

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Cited by in corpus (8)

• Softmax parameterization of the occupation numbers for natural orbital functionals based on electron pairing approaches
• Variational minimization scheme for the one-particle reduced density matrix functional theory in the ensemble N-representability domain
• Impact of Parametrizations of the One-Body Reduced Density Matrix on the Energy Landscape
• A toolbox of spin-adapted generalized Pauli constraints
• Time-Reversal Symmetry in RDMFT and pCCD with Complex-Valued Orbitals
• Refining ensemble $N$-representability of one-body density matrices from partial information
• Spin adaptation of the cumulant expansions of reduced density matrices
• Capturing electron correlation at mean-field cost: Assessment of i-DMFT and the underlying correlation conjecture