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相关论文: Accelerating self-consistent field iterations in K…

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We present a computationally efficient approach to solve the time-dependent Kohn-Sham equations in real-time using higher-order finite-element spatial discretization, applicable to both pseudopotential and all-electron calculations. To this…

计算物理 · 物理学 2019-10-02 Bikash Kanungo , Vikram Gavini

Linear-response time-dependent Density Functional Theory (LR-TDDFT) is a widely used method for accurately predicting the excited-state properties of physical systems. Previous works have attempted to accelerate LR-TDDFT using heterogeneous…

硬件体系结构 · 计算机科学 2025-04-07 Qingcai Jiang , Buxin Tu , Xiaoyu Hao , Junshi Chen , Hong An

Density Functional Theory (DFT) allows for predicting all the chemical and physical properties of molecular systems from first principles by finding an approximate solution to the many-body Schr\"odinger equation. However, the cost of these…

机器学习 · 计算机科学 2025-06-03 Majdi Hassan , Cristian Gabellini , Hatem Helal , Dominique Beaini , Kirill Neklyudov

We present the Tucker tensor DFT (TTDFT) code which uses a tensor-structured algorithm with graphic processing unit (GPU) acceleration for conducting ground-state DFT calculations on large-scale systems. The Tucker tensor DFT algorithm uses…

计算物理 · 物理学 2021-11-01 Chih-Chuen Lin , Vikram Gavini

We introduce an efficient finite-element approach for large-scale real-space pseudopotential density functional theory (DFT) calculations incorporating noncollinear magnetism and spin-orbit coupling. The approach, implemented within the…

材料科学 · 物理学 2025-06-11 Nikhil Kodali , Phani Motamarri

DFT calculations have become widespread in both chemistry and materials, because they usually provide useful accuracy at much lower computational cost than wavefunction-based methods. All practical DFT calculations require an approximation…

化学物理 · 物理学 2022-03-15 Eunji Sim , Suhwan Song , Stefan Vuckovic , Kieron Burke

Density functional theory (DFT) has emerged as one of the most versatile and lucrative approaches in electronic structure calculations of many-electron systems in past four decades. Here we give an account of the development of a…

化学物理 · 物理学 2019-04-19 Abhisek Ghosal , Amlan K. Roy

We develop a method in which the electronic densities of small fragments determined by Kohn-Sham density functional theory (DFT) are embedded using stochastic DFT to form the exact density of the full system. The new method preserves the…

化学物理 · 物理学 2015-06-19 Daniel Neuhauser , Roi Baer , Eran Rabani

This work presents a theory to unify the two independent theoretical frameworks of Kohn-Sham (KS) density functional theory (DFT) and reduced density matrix functional theory (RDMFT). The generalization of the KS orbitals to hypercomplex…

化学物理 · 物理学 2021-11-18 Neil Qiang Su

Two of the most widely used electronic structure theory methods, namely Hartree-Fock and Kohn-Sham density functional theory, both requires the iterative solution of a set of Schr\"odinger-like equations. The speed of convergence of such…

化学物理 · 物理学 2024-06-06 S. Hazra , U. Patil , S. Sanvito

We introduce a practical hybrid approach that combines orbital-free density functional theory (DFT) with Kohn-Sham DFT for speeding up first-principles molecular dynamics simulations. Equilibrated ionic configurations are generated using…

Kerker preconditioner, based on the dielectric function of homogeneous electron gas, is designed to accelerate the self-consistent field (SCF) iteration in the density functional theory (DFT) calculations. However, question still remains…

材料科学 · 物理学 2018-03-14 Yuzhi Zhou , Han Wang , Yu Liu , Xingyu Gao , Haifeng Song

We present a real-space formulation and higher-order finite-difference implementation of periodic Orbital-free Density Functional Theory (OF-DFT). Specifically, utilizing a local reformulation of the electrostatic and kernel terms, we…

计算物理 · 物理学 2015-12-23 Swarnava Ghosh , Phanish Suryanarayana

Low-rank optimization has emerged as a promising direction in training large language models (LLMs) to improve running time and reduce the memory usage of adaptive optimizers by constraining learning to a lower-dimensional space. Prior work…

机器学习 · 计算机科学 2025-10-09 Ionut-Vlad Modoranu , Mher Safaryan , Erik Schultheis , Max Ryabinin , Artem Chumachenko , Dan Alistarh

We present \textsc{dm-PhiSNet}, a physically constrained \textsc{PhiSNet}-based equivariant model that predicts one-electron reduced density matrices (1-RDMs) directly from molecular geometries in an atomic-orbital (AO) basis for…

化学物理 · 物理学 2026-05-01 Zuriel Y. Yescas-Ramos , Andrés Álvarez-García , Huziel E. Sauceda

We present an accurate, efficient and massively parallel finite-element code, DFT-FE, for large-scale ab-initio calculations (reaching $\sim 100,000$ electrons) using Kohn-Sham density functional theory (DFT). DFT-FE is based on a local…

In a recent paper we presented a linear scaling Kohn-Sham density functional theory (DFT) code based on Daubechies wavelets, where a minimal set of localized support functions is optimized in situ and therefore adapted to the chemical…

材料科学 · 物理学 2015-10-08 Laura E. Ratcliff , Luigi Genovese , Stephan Mohr , Thierry Deutsch

The kernel-independent fast multipole method (KIFMM) proposed in [1] is of almost linear complexity. In the original KIFMM the time-consuming M2L translations are accelerated by FFT. However, when more equivalent points are used to achieve…

数值分析 · 计算机科学 2015-03-19 Yanchuang Cao , Lihua Wen , Junjie Rong

Linear-scaling techniques for Kohn-Sham density functional theory (KS-DFT) are essential to describe the ground state properties of extended systems. Still, these techniques often rely on the locality of the density matrix or on accurate…

化学物理 · 物理学 2023-01-25 Ming Chen , Roi Baer , Eran Rabani

Density matrix embedding theory (DMET) is a powerful quantum embedding method for solving strongly correlated quantum systems. Theoretically, the performance of a quantum embedding method should be limited by the computational cost of the…

计算物理 · 物理学 2020-08-19 Xiaojie Wu , Michael Lindsey , Tiangang Zhou , Yu Tong , Lin Lin