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The interaction of condensed phase systems with external electric fields is crucial in myriad processes in nature and technology ranging from the field-directed motion of cells (galvanotaxis), to energy storage and conversion systems…

Chemical Physics · Physics 2024-09-25 Kit Joll , Philipp Schienbein , Kevin M. Rosso , Jochen Blumberger

Ab-initio molecular dynamics (AIMD) is a powerful tool to simulate physical movements of molecules for investigating properties of materials. While AIMD is successful in some applications, circumventing its high computational costs is…

Quantum Physics · Physics 2024-06-28 Honomi Kashihara , Yudai Suzuki , Kenji Yasuoka

Molecular dynamics simulations are an important tool for describing the evolution of a chemical system with time. However, these simulations are inherently held back either by the prohibitive cost of accurate electronic structure theory…

Chemical Physics · Physics 2018-12-20 Michael Gastegger , Philipp Marquetand

Path Integral Molecular Dynamics (PIMD) is a well established simulation technique to compute exact equilibrium properties for a quantum system using classical trajectories in an extended phase space. Standard PIMD simulations are…

Chemical Physics · Physics 2024-11-20 Britta A. Johnson , Siyu Bu , Christopher J. Mundy , Nandini Ananth

Path integral molecular dynamics simulations, combined with an ab initio evaluation of interactions using electronic structure theory, incorporate the quantum mechanical nature of both the electrons and nuclei, which are essential to…

Chemical Physics · Physics 2016-02-15 Ondrej Marsalek , Thomas E. Markland

Path integral molecular dynamics (PIMD) has been successfully applied to perform simulations of large bosonic systems in a recent work (Hirshberg et al., PNAS, 116, 21445 (2019)). In this work we extend PIMD techniques to study Green's…

Quantum Physics · Physics 2022-04-22 Xiong Yunuo , Xiong Hongwei

To take into account nuclear quantum effects on the dynamics of atoms, the path integral molecular dynamics (PIMD) method used since 1980s is based on the formalism developed by R. P. Feynman. However, the huge computation time required for…

Computational Physics · Physics 2019-05-08 H. Dammak , M. Hayoun , F Brieuc , G. Geneste

The convergence of statistical learning and molecular physics is transforming our approach to modeling biomolecular systems. Physics-informed machine learning (PIML) offers a systematic framework that integrates data-driven inference with…

Biomolecules · Quantitative Biology 2025-11-11 Aaryesh Deshpande

An exact approach to compute physical properties for general multi-electronic-state (MES) systems in thermal equilibrium is presented. The approach is extended from our recent progress on path integral molecular dynamics (PIMD) [J. Chem.…

Chemical Physics · Physics 2017-11-22 Xinzijian Liu , Jian Liu

Recent developments in many-body potential energy representation via deep learning have brought new hopes to addressing the accuracy-versus-efficiency dilemma in molecular simulations. Here we describe DeePMD-kit, a package written in…

Computational Physics · Physics 2018-05-23 Han Wang , Linfeng Zhang , Jiequn Han , Weinan E

Massively parallel computer architectures create new opportunities for the performance of long-timescale molecular dynamics (MD) simulations. Here, we introduce the path-accelerated molecular dynamics (PAMD) method that takes advantage of…

Computational Physics · Physics 2021-01-11 Jorge L. Rosa-Raíces , Bin Zhang , Thomas F. Miller

We report the implementation of a multi-CPU and multi-GPU massively parallel platform dedicated to the explicit inclusion of nuclear quantum effects (NQEs) in the Tinker-HP molecular dynamics (MD) package. The platform, denoted Quantum-HP,…

The precise description of quantum nuclear fluctuations in atomistic modelling is possible by employing path integral techniques, which involve a considerable computational overhead due to the need of simulating multiple replicas of the…

Chemical Physics · Physics 2017-03-23 Venkat Kapil , Jörg Behler , Michele Ceriotti

Exascale computing holds great opportunities for molecular dynamics (MD) simulations. However, to take full advantage of the new possibilities, we must learn how to focus computational power on the discovery of complex molecular mechanisms,…

Chemical Physics · Physics 2019-01-16 Hendrik Jung , Roberto Covino , Gerhard Hummer

This paper reviews Irradiation Driven Molecular Dynamics (IDMD) - a novel computational methodology for atomistic simulations of the irradiation driven transformations of complex molecular systems implemented in the MBN Explorer software…

Chemical Physics · Physics 2023-09-06 Alexey V. Verkhovtsev , Ilia A. Solov'yov , Andrey V. Solov'yov

Recent developments in path integral methodology have significantly reduced the computational expense of including quantum mechanical effects in the nuclear motion in ab initio molecular dynamics simulations. However, the implementation of…

Computational Physics · Physics 2014-02-06 Michele Ceriotti , Joshua More , David E. Manolopoulos

We present a method for performing path integral molecular dynamics (PIMD) simulations for fermions and address its sign problem. PIMD simulations are widely used for studying many-body quantum systems at thermal equilibrium. However, they…

Chemical Physics · Physics 2020-05-07 Barak Hirshberg , Michele Invernizzi , Michele Parrinello

Bosonic exchange symmetry leads to fascinating quantum phenomena, from exciton condensation in quantum materials to the superfluidity of liquid Helium-4. Unfortunately, path integral molecular dynamics (PIMD) simulations of bosons are…

Computational Physics · Physics 2025-02-18 Yotam M. Y. Feldman , Barak Hirshberg

Simulations of biological macromolecules play an important role in understanding the physical basis of a number of complex processes such as protein folding. Even with increasing computational power and evolution of specialized…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-09-18 Hyungro Lee , Heng Ma , Matteo Turilli , Debsindhu Bhowmik , Shantenu Jha , Arvind Ramanathan

Machine learning has emerged as an invaluable tool in many research areas. In the present work, we harness this power to predict highly accurate molecular infrared spectra with unprecedented computational efficiency. To account for…

Chemical Physics · Physics 2021-03-16 Michael Gastegger , Jörg Behler , Philipp Marquetand