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<p>We introduce a general class of orbital-free density functionals (OF-DFT) decomposed into a local part in coordinate space and a local part in reciprocal space. As a demonstration of principle, we choose for the former the Thomas-Fermi-von Weizsäcker (TFW) kinetic energy density functional (KEDF) and for the latter a form derived from the Lindhard function, but with the two system-dependent adjustable parameters. These parameters are machine-learned from Kohn-Sham data using Bayesian linear regression with a kernel method, which employs moments of the Fourier components of the electronic density as the descriptor. Through a number of representative cases, we demonstrate that our machine-learned model provides more than an order-of-magnitude improvement in the accuracy of the frozen-phonon energies compared to the TFW KEDF, with negligible increase in the computational cost. Overall, this work opens an avenue for the construction of accurate KEDFs for OF-DFT.</p>

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Orbital-free density functionals based on real and reciprocal space separation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月24日

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  • Bishal Thapa,
  • Tracey G. Oellerich,
  • Maria Emelianenko,
  • Phanish Suryanarayana,
  • Igor I. Mazin

摘要

We introduce a general class of orbital-free density functionals (OF-DFT) decomposed into a local part in coordinate space and a local part in reciprocal space. As a demonstration of principle, we choose for the former the Thomas-Fermi-von Weizsäcker (TFW) kinetic energy density functional (KEDF) and for the latter a form derived from the Lindhard function, but with the two system-dependent adjustable parameters. These parameters are machine-learned from Kohn-Sham data using Bayesian linear regression with a kernel method, which employs moments of the Fourier components of the electronic density as the descriptor. Through a number of representative cases, we demonstrate that our machine-learned model provides more than an order-of-magnitude improvement in the accuracy of the frozen-phonon energies compared to the TFW KEDF, with negligible increase in the computational cost. Overall, this work opens an avenue for the construction of accurate KEDFs for OF-DFT.