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Large-scale first principles molecular dynamics are crucial for simulating complex processes in chemical, biomedical, and materials sciences. However, the unfavorable time complexity with respect to system sizes leads to prohibitive…

This article proposes a so-called Quasi Time-Reversible (QTR G-Ext) scheme based on Grassmann extrapolation of density matrices for an accurate calculation of initial guesses in Born-Oppenheimer Molecular Dynamics simulations. The method…

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

To explore the applicability of orbital-free density functional theory (OF-DFT) in nuclear physics, we perform a systematic benchmark of 36 one-point kinetic energy density functionals, which are originally developed for electron systems in…

Nuclear Theory · Physics 2026-05-20 Tian Shuai Shang , Jian Li , Haozhao Liang , Xinhui Wu , Cheng Ma , Wenhui Mi , Xuecheng Shao , Yanchao Wang

We have developed molecular dynamics codes for a short-range interaction potential that adopt both the flat-MPI and MPI/OpenMP hybrid parallelizations on the basis of a full domain decomposition strategy. Benchmark simulations involving up…

Computational Physics · Physics 2013-11-28 Hiroshi Watanabe , Masaru Suzuki , Nobuyasu Ito

Proton transfer is central to many processes of chemical interest. The simulation of proton transfer dynamics requires the inclusion of nuclear quantum effects, such as zero-point energy, nuclear delocalization, and tunneling. Herein, we…

Chemical Physics · Physics 2026-03-19 Joseph A. Dickinson , Mathew Chow , Eno Paenurk , Sharon Hammes-Schiffer

Orbital-free density functional theory (OF-DFT) for real-space systems has historically depended on Lagrange optimization techniques, primarily due to the inability of previously proposed electron density approaches to ensure the…

Chemical Physics · Physics 2024-11-08 Alexandre de Camargo , Ricky T. Q. Chen , Rodrigo A. Vargas-Hernández

This study employed an artificial intelligence-enhanced molecular simulation framework to enable efficient Path Integral Molecular Dynamics (PIMD) simulations. Owing to its modular architecture and high-throughput capabilities, the…

Chemical Physics · Physics 2025-04-01 Cheng Fan , Maodong Li , Sihao Yuan , Zhaoxin Xie , Dechin Chen , Yi Isaac Yang , Yi Qin Gao

Electronic structure calculation of atoms and molecules, in the past few decades has largely been dominated by density functional methods. This is primarily due to the fact that this can account for electron correlation effects in a…

Chemical Physics · Physics 2013-07-12 Amlan K. Roy

Tensor cores, along with tensor processing units, represent a new form of hardware acceleration specifically designed for deep neural network calculations in artificial intelligence applications. Tensor cores provide extraordinary…

Within the framework of linear-scaling Kohn-Sham density functional theory, a robust method for maintaining compact localized orbitals close to the ground state is coupled with nuclear dynamics. This allows to obviate the commonly employed…

Computational Physics · Physics 2018-08-01 Hayden Scheiber , Yifei Shi , Rustam Z. Khaliullin

Large language models have revolutionized artificial intelligence by enabling large, generalizable models trained through self-supervision. This paradigm has inspired the development of scientific foundation models (FMs). However, applying…

Fast and accurate molecular force field (FF) parameterization is still an unsolved problem. Accurate FFs are not generally available for all molecules, like novel druglike molecules. While methods based on quantum mechanics (QM) exist to…

Chemical Physics · Physics 2019-08-06 Raimondas Galvelis , Stefan Doerr , Joao M. Damas , Matt J. Harvey , Gianni De Fabritiis

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…

Modeling nuclear quantum effects is required for accurate molecular dynamics (MD) simulations of molecules. The community has paid special attention to water and other biomolecules that show hydrogen bonding. Standard methods of modeling…

Chemical Physics · Physics 2020-07-06 Vikram Sundar , David Gelbwaser-Klimovsky , Alan Aspuru-Guzik

Density Functional Theory (DFT) accurately predicts the quantum chemical properties of molecules, but scales as $O(N_{\text{electrons}}^3)$. Sch\"utt et al. (2019) successfully approximate DFT 1000x faster with Neural Networks (NN).…

An accelerated polynomial expansion scheme to construct the density matrix in quantum mechanical molecular dynamics simulations is proposed. The scheme is based on recursive density matrix expansions, e.g. [Phys. Rev. B. 66 (2002), p.…

Computational Physics · Physics 2013-03-01 Emanuel H. Rubensson , Anders M. N. Niklasson

Simulating the dynamics of ions near polarizable nanoparticles (NPs) using coarse-grained models is extremely challenging due to the need to solve the Poisson equation at every simulation timestep. Recently, a molecular dynamics (MD) method…

Computational Physics · Physics 2019-11-01 JCS Kadupitiya , Geoffrey C. Fox , Vikram Jadhao

Extended Lagrangian Born-Oppenheimer molecular dynamics [Phys. Rev. Lett., ${\bf 100}$, 123004 (2008)] is formulated for general Hohenberg-Kohn density functional theory and compared to the extended Lagrangian framework of first principles…

Materials Science · Physics 2017-09-13 Anders M. N. Niklasson

Density-potential functional theory (DPFT) is an alternative formulation of orbital-free density functional theory that may be suitable for modeling the electronic structure of large systems. To date, DPFT has been applied mainly to quantum…

Materials Science · Physics 2023-04-21 Martin-Isbjörn Trappe , William C. Witt , Sergei Manzhos