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We present a spectrum-splitting approach to conduct all-electron Kohn-Sham density functional theory (DFT) calculations by employing Fermi-operator expansion of the Kohn-Sham Hamiltonian. The proposed approach splits the subspace containing…

Computational Physics · Physics 2017-02-01 Phani Motamarri , Vikram Gavini , Kaushik Bhattacharya , Michael Ortiz

Density functional theory (DFT) is an incredible success story. The low computational cost, combined with useful (but not yet chemical) accuracy, has made DFT a standard technique in most branches of chemistry and materials science.…

Chemical Physics · Physics 2015-06-03 Kieron Burke

Density functional theory (DFT) is a powerful theoretical tool widely used in such diverse fields as computational condensed matter physics, atomic physics, and quantum chemistry. DFT establishes that a system of $N$ interacting electrons…

Plasma Physics · Physics 2020-04-29 Giovanni Manfredi

Large-scale simulations of plastic deformation and phase transformations in alloys require reliable classical interatomic potentials. We construct an embedded-atom method potential for niobium as the first step in alloy potential…

Materials Science · Physics 2010-04-27 Michael R. Fellinger , Hyoungki Park , John W. Wilkins

We show that classical molecular density functional theory (MDFT), here in the homogeneous reference fluid approximation in which the functional is inferred from the properties of the bulk solvent, is a powerful new tool to study, at a…

The $N$-point discrete Fourier transform (DFT) is a cornerstone for several signal processing applications. Many of these applications operate in real-time, making the computational complexity of the DFT a critical performance indicator to…

Data Structures and Algorithms · Computer Science 2024-12-18 Saulo Queiroz , João P. Vilela , Edmundo Monteiro

Kohn-Sham density functional theory is the base of modern computational approaches to electronic structures. Their accuracy vitally relies on the exchange-correlation energy functional, which encapsulates electron-electron interaction…

Computational Physics · Physics 2019-11-04 Ryo Nagai , Ryosuke Akashi , Osamu Sugino

This study benchmarks the GFN family of semiempirical methods (GFN1-xTB, GFN2-xTB, GFN0-xTB, and GFN-FF) against density functional theory (DFT) for the evaluation of optimized molecular geometries and electronic properties of small organic…

The matrix expressions for every parts of a transformer are firstly described. Based on semi-tensor product (STP) of matrices the hypervectors are reconsidered and the linear transformation over hypervectors is constructed by using…

Machine Learning · Computer Science 2025-04-22 Daizhan Cheng

This paper presents a Python software package, Ph3pyWF, providing a more convenient platform to realize high-throughput analysis of lattice thermal conductivity for ceramic materials. The interface of Ph3pyWF is friendly for users with…

Materials Science · Physics 2023-02-24 Kerui Lai , Yuxuan Wang

Perdew et al. [Phys. Rev. Lett 49, 1691 (1982)] discovered and proved two different properties of exact Kohn-Sham density functional theory (DFT): (i) The exact total energy versus particle number is a series of linear segments between…

Other Condensed Matter · Physics 2015-03-13 Tamar Stein , Jochen Autschbach , Niranjan Govind , Leeor Kronik , Roi Baer

Linear-response time-dependent (TD) density-functional theory (DFT) has been implemented in the pseudopotential wavelet-based electronic structure program BigDFT and results are compared against those obtained with the all-electron…

The fast Fourier transform (FFT) is a primitive kernel in numerous fields of science and engineering. OpenFFT is an open-source parallel package for 3-D FFTs, built on a communication-optimal domain decomposition method for achieving…

Mathematical Software · Computer Science 2015-08-27 Truong Vinh Truong Duy , Taisuke Ozaki

Multi-dimensional Fourier transforms are key mathematical building blocks that appear in a wide range of applications from materials science, physics, chemistry and even machine learning. Over the past years, a multitude of software…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-11 Doru Thom Popovici , Mauro del Ben , Osni Marques , Andrew Canning

High performance computing (HPC) is a powerful tool to accelerate the Kohn-Sham density functional theory (KS-DFT) calculations on modern heterogeneous supercomputers. Here, we describe a massively extreme-scale parallel and portable…

Computational Physics · Physics 2020-04-20 Wei Hu , Xinming Qin , Caiqing Jiang , Junshi Chen , Hong An , Weile Jia , Fang Li , Xin Liu , Dexun Chen , Jinlong Yang

An overview of the Conquest linear scaling density functional theory (DFT) code is given, focussing particularly on the scaling behaviour on modern high- performance computing (HPC) platforms. We demonstrate that essentially perfect linear…

Materials Science · Physics 2010-02-03 D. R. Bowler , T. Miyazaki

Given a partition of a large system into an active quantum mechanical (QM) region and its environment, we present a simple way of embedding the QM region into an effective electrostatic potential representing the environment. This potential…

Chemical Physics · Physics 2017-07-20 Stephan Mohr , Michel Masella , Laura E. Ratcliff , Luigi Genovese

Despite a large number of nonlocal kinetic energy density functionals (KEDFs) available for large-scale calculations, most of those nonlocal KEDFs designed for the extended systems cannot be directly applied to isolated systems. In this…

Materials Science · Physics 2020-05-29 Qiang Xu , Jian Lv , Yanchao Wang , Yanming Ma

Electronic structure calculations based on density-functional theory (DFT) represent a significant part of today's HPC workloads and pose high demands on high-performance computing resources. To perform these quantum-mechanical DFT…

Computational Physics · Physics 2021-04-28 Michael Lass , Robert Schade , Thomas D. Kühne , Christian Plessl

We introduce an efficient open-source python package for the inverse design of three-dimensional photonic nanostructures using the Finite-Difference Time-Domain (FDTD) method. Leveraging a flexible reverse-mode automatic differentiation…

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