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The QMol-grid package provides a suite of routines for performing quantum-mechanical simulations in atomic and molecular systems, currently implemented in one spatial dimension. It supports ground- and excited-state calculations for the…

Computational Physics · Physics 2024-11-19 Francois Mauger , Cristel Chandre

We introduce a variational approximation to the microscopic dynamics of rare conformational transitions of macromolecules. Within this framework it is possible to simulate on a small computer cluster reactions as complex as protein folding,…

Soft Condensed Matter · Physics 2015-02-19 S. a Beccara , L. Fant , P. Faccioli

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

A set of Mathematica functions is presented to model classically two of the most important processes in strong field physics, namely high-order harmonic generation (HHG) and above-threshold ionization (ATI). Our approach is based on the…

Optics · Physics 2015-06-16 M. F. Ciappina , J. A. Pérez-Hernández , M. Lewenstein

Atomistic foundation models (AFMs) have great promise as accurate interatomic potentials, and have enabled data-efficient molecular dynamics simulations with near quantum mechanical accuracy. However, AFMs remain markedly slower at…

Materials Science · Physics 2025-09-29 Lingyu Kong , Jaeheon Shim , Guoxiang Hu , Victor Fung

This paper documents package for the particle level fast simulation. The package is designed to complete the AcerMC generator framework with the easy-to-use simulation and reconstruction algorithms. The package provides, starting from list…

High Energy Physics - Phenomenology · Physics 2007-05-23 E. Richter-Was

Simulations of quantum chemistry and quantum materials are believed to be among the most important potential applications of quantum information processors, but realizing practical quantum advantage for such problems is challenging. Here,…

Atomistic simulations using accurate energy functions can provide molecular-level insight into functional motions of molecules in the gas- and in the condensed phase. Together with recently developed and currently pursued efforts in…

Chemical Physics · Physics 2022-01-12 M. Meuwly

This work describes extensions to existing level-set algorithms developed for application within the field of Atom Probe Tomography (APT). We present a new simulation tool for the simulation of 3D tomographic volumes, using advanced level…

Computational Physics · Physics 2018-02-28 Daniel Haley , Paul A. J. Bagot , Michael P. Moody

We present the Python Tree Tensor Network package (pyTTN) for the evaluation of dynamical properties of closed and open quantum systems that makes use of Tree Tensor Network (TTN), or equivalently the multi-layer multiconfiguration…

Quantum Physics · Physics 2025-03-20 Lachlan P Lindoy , Daniel Rodrigo-Albert , Yannic Rath , Ivan Rungger

As AI agents move from demos into enterprise deployments, their failure modes become consequential: a misinterpreted tool argument can corrupt production data, a silent reasoning error can go undetected until damage is done, and outputs…

Machine learning has become ubiquitous in materials modelling and now routinely enables large-scale atomistic simulations with quantum-mechanical accuracy. However, developing machine-learned interatomic potentials requires high-quality…

Two of the most challenging tasks in molecular simulation consist in capturing the properties of systems with long-range interactions (e.g. electrolyte solutions) as well as systems containing large molecules such as hydrogels. For the…

Chemical Physics · Physics 2011-07-26 Jonathan Walter , Stephan Deublein , Steffen Reiser , Martin Horsch , Jadran Vrabec , Hans Hasse

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely…

ARC 3.0 is a modular, object-oriented Python library combining data and algorithms to enable the calculation of a range of properties of alkali and divalent atoms. Building on the initial version of the ARC library [N. \v{S}ibali\'c et al,…

Recent advances in both theory and methods have created opportunities to simulate biomolecular processes more efficiently using adaptive ensemble simulations. Ensemble-based simulations are used widely to compute a number of individual…

Computational Engineering, Finance, and Science · Computer Science 2020-09-14 Vivek Balasubramanian , Travis Jensen , Matteo Turilli , Peter Kasson , Michael Shirts , Shantenu Jha

The MeMC is an open-source software package for monte-carlo simulation of elastic shells. It is designed as a tool to interpret the force-distance data generated by indentation of biological nano-vesicles by atomic force microscopes. The…

Computational Physics · Physics 2022-06-28 Vipin Agrawal , Vikash Pandey , Hanna Kylhammar , Apurba Dev , Dhrubaditya Mitra

AMDAT (Amorphous Molecular Dynamics Analysis Toolkit) is an open-source C++ toolkit for post-processing molecular dynamics trajectories, focused on high-performance static and dynamic analyses of amorphous, glassy, and polymer materials,…

Materials Science · Physics 2026-02-06 Pierre Kawak , William F. Drayer , David S. Simmons

Molecular Dynamics simulations are becoming a powerful tool for examining and predicting atomic and molecular processes in various environment. The present review shows how, in the fields of plasma physics, chemistry and interactions with…

Plasma Physics · Physics 2023-12-14 Pascal Brault