Neural network-based pseudopotential: development of a transferable local pseudopotential

Woo, Jeheon; Kim, Hyeonsu; Kim, Woo Youn

doi:10.1039/d2cp01810a

Cited by 8 publications

(8 citation statements)

References 58 publications

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“…and R a denote the total contributions of LPPs of ions in simulated cell, the LPP of ath ion, and ath ionic positions, respectively. As shown in Figure 5, various LPPs are available, including empirical/ model, 31,32,131,135,[156][157][158] first-principles, 29,[38][39][40] and ML 30,162,163 LPPs. Some of these has been demonstrated excellent accuracy and transferability.…”

Section: Local Pseudopotentialsmentioning

confidence: 99%

Recent advancements and challenges in orbital‐free density functional theory

Xu,

Ma,

et al. 2024

WIREs Comput Mol Sci

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Orbital‐free density functional theory (OFDFT) stands out as a many‐body electronic structure approach with a low computational cost that scales linearly with system size, making it well suitable for large‐scale simulations. The past decades have witnessed impressive progress in OFDFT, which opens a new avenue to capture the complexity of realistic systems (e.g., solids, liquids, and warm dense matters) and provide a complete description of some complicated physical phenomena under realistic conditions (e.g., dislocation mobility, ductile processes, and vacancy diffusion). In this review, we first present a concise summary of the major methodological advances in OFDFT, placing particular emphasis on kinetic energy density functional and the schemes to evaluate the electron–ion interaction energy. We then give a brief overview of the current status of OFDFT developments in finite‐temperature and time‐dependent regimes, as well as our developed OFDFT‐based software package, named by ATLAS. Finally, we highlight perspectives for further development in this fascinating field, including the major outstanding issues to be solved and forthcoming opportunities to explore large‐scale materials.This article is categorized under: Electronic Structure Theory > Density Functional Theory Software > Simulation Methods Quantum Computing > Theory Development

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Section: Local Pseudopotentialsmentioning

confidence: 99%

Recent advancements and challenges in orbital‐free density functional theory

Xu,

Ma,

et al. 2024

WIREs Comput Mol Sci

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“…Thus, the requirement for LPPs is still very much an open problem for OFDFT and perhaps may be its Achilles' heel. New approaches, such as the one based on model 1-rdms summarized in Subsection 2.7, and very recent efforts involving machine-learning pseudopotentials 480 might prove to be breakthroughs for extending the applicability of OFDFT to a wide selection of elements in the periodic table.…”

Section: Nlmentioning

confidence: 99%

Orbital-Free Density Functional Theory: An Attractive Electronic Structure Method for Large-Scale First-Principles Simulations

Mi,

Luo,

Trickey

et al. 2023

Chem. Rev.

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Kohn−Sham Density Functional Theory (KSDFT) is the most widely used electronic structure method in chemistry, physics, and materials science, with thousands of calculations cited annually. This ubiquity is rooted in the favorable accuracy vs cost balance of KSDFT. Nonetheless, the ambitions and expectations of researchers for use of KSDFT in predictive simulations of large, complicated molecular systems are confronted with an intrinsic computational cost-scaling challenge. Particularly evident in the context of firstprinciples molecular dynamics, the challenge is the high cost-scaling associated with the computation of the Kohn−Sham orbitals. Orbital-free DFT (OFDFT), as the name suggests, circumvents entirely the explicit use of those orbitals. Without them, the structural and algorithmic complexity of KSDFT simplifies dramatically and near-linear scaling with system size irrespective of system state is achievable. Thus, much larger system sizes and longer simulation time scales (compared to conventional KSDFT) become accessible; hence, new chemical phenomena and new materials can be explored. In this review, we introduce the historical contexts of OFDFT, its theoretical basis, and the challenge of realizing its promise via approximate kinetic energy density functionals (KEDFs). We review recent progress on that challenge for an array of KEDFs, such as one-point, twopoint, and machine-learnt, as well as some less explored forms. We emphasize use of exact constraints and the inevitability of design choices. Then, we survey the associated numerical techniques and implemented algorithms specific to OFDFT. We conclude with an illustrative sample of applications to showcase the power of OFDFT in materials science, chemistry, and physics.

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“…Electronic structure calculations were performed using the GOSPEL package, which is a grid-based KS solver written in Python. For all calculations, we used the PBE exchange-correlation functional and the norm-conserving pseudopotentials. − An equidistant grid with a grid spacing of 0.2 Å was used. We employed the 7-point finite-difference method to represent the Laplacian operator.…”

Section: Implementation and Computational Detailsmentioning

confidence: 99%

Dynamic Precision Approach for Accelerating Large-Scale Eigenvalue Solvers in Electronic Structure Calculations on Graphics Processing Units

Woo

Kim

2023

J. Chem. Theory Comput.

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Single precision (SP) arithmetic can be greatly accelerated as compared to double precision (DP) arithmetic on graphics processing units (GPUs). However, the use of SP in the whole process of electronic structure calculations is inappropriate for the required accuracy. We propose a 3-fold dynamic precision approach for accelerated calculations but still with the accuracy of DP. Here, SP, DP, and mixed precision are dynamically switched during an iterative diagonalization process. We applied this approach to the locally optimal block preconditioned conjugate gradient method to accelerate a large-scale eigenvalue solver for the Kohn–Sham equation. We determined a proper threshold for switching each precision scheme by examining the convergence pattern on the eigenvalue solver only with the kinetic energy operator of the Kohn–Sham Hamiltonian. As a result, we achieved up to 8.53× and 6.60× speedups for band structure and self-consistent field calculations, respectively, for test systems under various boundary conditions on NVIDIA GPUs.

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Neural network-based pseudopotential: development of a transferable local pseudopotential

Abstract: Transferable local pseudopotentials (LPPs) are essential for fast quantum simulations of materials. However, various types of LPPs suffer from low transferability, especially since they do not consider the norm-conserving condition....

Cited by 8 publications

References 58 publications

Recent advancements and challenges in orbital‐free density functional theory

Recent advancements and challenges in orbital‐free density functional theory

Orbital-Free Density Functional Theory: An Attractive Electronic Structure Method for Large-Scale First-Principles Simulations

Dynamic Precision Approach for Accelerating Large-Scale Eigenvalue Solvers in Electronic Structure Calculations on Graphics Processing Units

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