4.6 Article

Time-dependent orbital-free density functional theory: Background and Pauli kernel approximations

Journal

PHYSICAL REVIEW B
Volume 103, Issue 24, Pages -

Publisher

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevB.103.245102

Keywords

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Funding

  1. US Department of Energy, Office of Basic Energy Sciences [DE-SC0018343]
  2. U.S. Department of Energy (DOE) [DE-SC0018343] Funding Source: U.S. Department of Energy (DOE)

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Time-dependent orbital-free density functional theory is an efficient method for calculating dynamic properties of large-scale quantum systems. The method involves mapping the real system of interacting fermions onto a fictitious system of noninteracting bosons, with key ingredients being the dynamic Pauli potential and associated kernel. The proposed frequency-dependent Pauli kernel shows promising results for improving the accuracy of orbital-free DFT simulations for nanoscale systems.
Time-dependent orbital-free density functional theory (DFT) is an efficient method for calculating the dynamic properties of large-scale quantum systems due to the low computational cost compared to standard time-dependent DFT. We formalize this method by mapping the real system of interacting fermions onto a fictitious system of noninteracting bosons. The dynamic Pauli potential and associated kernel emerge as key ingredients of time-dependent orbital-free DFT. Using the uniform electron gas as a model system, we derive an approximate frequency-dependent Pauli kernel. Pilot calculations suggest that space nonlocality is a key feature for this kernel. Nonlocal terms arise already in the second-order expansion with respect to unitless frequency and reciprocal space variable (omega/q k(F) and q/2 k(F), respectively). Given the encouraging performance of the proposed kernel, we expect it will lead to more accurate orbital-free DFT simulations of nanoscale systems out of equilibrium. Additionally, the proposed path to formulate nonadiabatic Pauli kernels presents several avenues for further improvements which can be exploited in future work to improve the results.

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