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Extended Lagrangian molecular dynamics (XLMD) is a general method for performing molecular dynamics simulations using quantum and classical many-body potentials. Recently several new XLMD schemes have been proposed and tested on several…

Numerical Analysis · Mathematics 2020-02-28 Dong An , Sara Y. Cheng , Teresa Head-Gordon , Lin Lin , Jianfeng Lu

Quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations have been developed to simulate molecular systems, where an explicit description of changes in the electronic structure is necessary. However, QM/MM MD…

Chemical Physics · Physics 2021-04-15 Lennard Böselt , Moritz Thürlemann , Sereina Riniker

The inherently high computational cost of iterative self-consistent-field (SCF) methods proves to be a critical issue delaying visual and haptic feedback in real-time quantum chemistry. In this work, we introduce two schemes for SCF…

Chemical Physics · Physics 2016-03-10 Adrian H. Mühlbach , Alain C. Vaucher , Markus Reiher

The weighted ensemble (WE) simulation strategy provides unbiased sampling of non-equilibrium processes, such as molecular folding or binding, but the extraction of rate constants relies on characterizing steady state behavior.…

Statistical Mechanics · Physics 2020-10-02 Jeremy Copperman , Daniel Zuckerman

The Method of Moments (MOM) has largely been applied to investigate sooting laminar and turbulent flames. However, the classical MOM is not able to characterize a continuous particle size distribution (PSD). Without access to information on…

Fluid Dynamics · Physics 2022-10-20 Federica Ferraro , Sandro Gierth , Steffen Salenbauch , Wang Han , Christian Hasse

Wave packet molecular dynamics (WPMD) has recently received a lot of attention as a computationally fast tool to study dynamical processes in warm dense matter beyond the Born-Oppenheimer approximation. These techniques, typically, employ…

Plasma Physics · Physics 2021-04-09 William A. Angermeier , Thomas G. White

An extended first-principles molecular dynamics (FPMD) method based on Kohn-Sham scheme is proposed to elevate the temperature limit of the FPMD method in the calculation of dense plasmas. The extended method treats the wave functions of…

Plasma Physics · Physics 2016-09-08 Shen Zhang , Hongwei Wang , Wei Kang , Ping Zhang , Xian-Tu He

Accurate modelling of electrostatic interactions and charge transfer is fundamental to computational chemistry, yet most machine learning interatomic potentials (MLIPs) rely on local atomic descriptors that cannot capture long-range…

Most atomistic machine learning (ML) models rely on a locality ansatz, and decompose the energy into a sum of short-ranged, atom-centered contributions. This leads to clear limitations when trying to describe problems that are dominated by…

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

To address the computational challenges of ab initio molecular dynamics and the accuracy limitations of empirical force fields, the introduction of machine learning force fields has proven effective in various systems including metals and…

Soft Condensed Matter · Physics 2023-12-18 Junbao Hu , Liyang Zhou , Jian Jiang

A kernel-based method (kernelized minimal distributed charge model - kMDCM) to represent the molecular electrostatic potential (ESP) in terms of off-center point charges whose positions adapts to the molecular geometry. Using Gaussian…

Chemical Physics · Physics 2024-06-04 Eric Boittier , Kai Töpfer , Mike Devereux , Markus Meuwly

Computer simulation is an important tool for scientific progress, especially when lab experiments are either extremely costly and difficult or lack the required resolution. However, all of the simulation methods come with limitations. In…

Fluid Dynamics · Physics 2023-08-04 Edward R. Smith , Panagiotis E. Theodorakis

Endoscopic Submucosal Dissection (ESD) is a minimally invasive procedure initially developed for early gastric cancer treatment and has expanded to address diverse gastrointestinal lesions. While computer-assisted surgery (CAS) systems…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Xiangning Zhang , Qingwei Zhang , Jinnan Chen , Chengfeng Zhou , Yaqi Wang , Zhengjie Zhang , Xiaobo Li , Dahong Qian

We present an accelerated ``on-the-fly'' coupled-cluster path-integral molecular dynamics (PIMD) method for finite-temperature simulations in which electron correlation and nuclear quantum effects are treated simultaneously. The approach is…

Chemical Physics · Physics 2026-05-20 Thomas Spura , Hossam Elgabarty , Thomas D. Kühne

Towards the efficient simulation of near-term quantum devices using tensor network states, we introduce an improved real-space parallelizable matrix-product state (MPS) compression method. This method enables efficient compression of all…

Quantum Physics · Physics 2024-09-02 Rong-Yang Sun , Tomonori Shirakawa , Seiji Yunoki

A computer adapted fluctuation formula for the calculation of the wavevector- and frequency-dependent dielectric permittivity for interaction site models of polar fluids within the Ewald summation technique is proposed and applied to…

Computational Physics · Physics 2009-10-31 Igor P. Omelyan

The non-orthogonal local submatrix method applied to electronic-structure based molecular dynamics simulations is shown to exceed 1.1 EFLOP/s in FP16/FP32 mixed floating-point arithmetic when using 4,400 NVIDIA A100 GPUs of the Perlmutter…

Computational Physics · Physics 2022-06-08 Robert Schade , Tobias Kenter , Hossam Elgabarty , Michael Lass , Thomas D. Kühne , Christian Plessl

Previous partial permutation synchronization (PPS) algorithms, which are commonly used for multi-object matching, often involve computation-intensive and memory-demanding matrix operations. These operations become intractable for large…

Computer Vision and Pattern Recognition · Computer Science 2022-04-01 Shaohan Li , Yunpeng Shi , Gilad Lerman

The rapid advancement of large language models (LLMs) has led to architectures with billions to trillions of parameters, posing significant deployment challenges due to their substantial demands on memory, processing power, and energy…

Machine Learning · Computer Science 2024-07-02 Enshu Liu , Junyi Zhu , Zinan Lin , Xuefei Ning , Matthew B. Blaschko , Shengen Yan , Guohao Dai , Huazhong Yang , Yu Wang