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For many macromolecular systems the accurate sampling of the relevant regions on the potential energy surface cannot be obtained by a single, long Molecular Dynamics (MD) trajectory. New approaches are required to promote more efficient…

Computational Engineering, Finance, and Science · Computer Science 2016-06-02 Vivekanandan Balasubramanian , Iain Bethune , Ardita Shkurti , Elena Breitmoser , Eugen Hruska , Cecilia Clementi , Charles Laughton , Shantenu Jha

This work introduces ParAMS -- a versatile Python package that aims to make parameterization workflows in computational chemistry and physics more accessible, transparent and reproducible. We demonstrate how ParAMS facilitates the parameter…

Chemical Physics · Physics 2021-05-18 Leonid Komissarov , Robert Rüger , Matti Hellström , Toon Verstraelen

Large-scale molecular dynamics simulations with high accuracy have been increasingly popular for their capability to bridge the gap between atomistic modeling and mesoscale phenomena. Both machine learning potentials and enhanced sampling…

Computational Physics · Physics 2026-03-24 Haoting Zhang , Qiuhan Jia , Zhennan Zhang , Yijie Zhu , Zhongwei Zhang , Junjie Wang , Jiuyang Shi , Zheyong Fan , Jian Sun

ESPResSo 4.0 is an extensible simulation package for research on soft matter. This versatile molecular dynamics program was originally developed for coarse-grained simulations of charged systems Limbach et al., Comput. Phys. Commun. 174,…

Particle accelerator modeling is an important field of research and development, essential to investigating, designing and operating some of the most complex scientific devices ever built. Kinetic simulations of relativistic, charged…

Accelerator Physics · Physics 2024-05-02 Ryan T. Sandberg , Remi Lehe , Chad E. Mitchell , Marco Garten , Andrew Myers , Ji Qiang , Jean-Luc Vay , Axel Huebl

MADNESS (multiresolution adaptive numerical environment for scientific simulation) is a high-level software environment for solving integral and differential equations in many dimensions that uses adaptive and fast harmonic analysis methods…

We present NuMagSANS, a GPU-accelerated software package for calculating nuclear and magnetic small-angle neutron scattering (SANS) cross sections and correlation functions. The program allows users to import position-dependent nuclear…

Materials Science · Physics 2026-01-27 Michael P. Adams , Andreas Michels

We describe our contribution as industrial stakeholders to the existing open-source GPU4PySCF project (https: //github.com/pyscf/gpu4pyscf), a GPU-accelerated Python quantum chemistry package. We have integrated GPU acceleration into other…

Molecular dynamics (MD) simulations are useful in obtaining thermodynamic and kinetic properties of bio-molecules but are limited by the timescale barrier, i.e., we may be unable to efficiently obtain properties because we need to run…

Chemical Physics · Physics 2017-08-23 Surl-Hee Ahn , Jay W. Grate , Eric F. Darve

Determining molecular abundances in astrophysical environments is crucial for interpreting observational data and constraining physical conditions in these regions. Chemical modelling tools are essential for simulating the complex processes…

Instrumentation and Methods for Astrophysics · Physics 2025-09-17 Luke Keyte , Jason Ran

A family of fast sampling methods is introduced here for molecular simulations of systems having rugged free energy landscapes. The methods represent a generalization of a strategy consisting of adjusting a model for the free energy as a…

Computational Physics · Physics 2022-02-07 Pablo F. Zubieta Rico , Juan J. de Pablo

High-fidelity simulations and physical experiments are essential for engineering analysis and design, yet their high cost often makes two critical tasks--global sensitivity analysis (GSA) and optimization--prohibitively expensive. This…

Machine Learning · Computer Science 2026-01-01 Bach Do , Nafeezat A. Ajenifuja , Taiwo A. Adebiyi , Ruda Zhang

PyMembrane is a software package for simulating liquid and elastic membranes using a discretisation of the continuum description based on unstructured triangulated two-dimensional meshes embedded in three-dimensional space. The package is…

Soft Condensed Matter · Physics 2023-08-25 D. A. Matoz-Fernandez , Siyu Li , Monica Olvera de la Cruz , Rastko Sknepnek

Bayesian Networks (BNs) are used in various fields for modeling, prediction, and decision making. pgmpy is a python package that provides a collection of algorithms and tools to work with BNs and related models. It implements algorithms for…

Machine Learning · Computer Science 2023-04-19 Ankur Ankan , Johannes Textor

We present the open-source image processing software package PySAP (Python Sparse data Analysis Package) developed for the COmpressed Sensing for Magnetic resonance Imaging and Cosmology (COSMIC) project. This package provides a set of…

Instrumentation and Methods for Astrophysics · Physics 2020-07-03 S. Farrens , A. Grigis , L. El Gueddari , Z. Ramzi , Chaithya G. R. , S. Starck , B. Sarthou , H. Cherkaoui , P. Ciuciu , J. -L. Starck

PySEMTools is a Python-based library for post-processing simulation data produced with high-order hexahedral elements in the context of the spectral element method in computational fluid dynamics. It aims to minimize intermediate steps…

Computational Physics · Physics 2025-04-18 Adalberto Perez , Siavash Toosi , Tim Felle Olsen , Stefano Markidis , Philipp Schlatter

PySPH is an open-source, Python-based, framework for particle methods in general and Smoothed Particle Hydrodynamics (SPH) in particular. PySPH allows a user to define a complete SPH simulation using pure Python. High-performance code is…

We present an open-source, performant, pure-python molecular dynamics (MD) suite for non-ideal plasmas. The code, Sarkas, aims to accelerate the research process by providing an MD code but also pre- and post-processing tools. Sarkas offers…

Polarized Resonant Soft X-ray scattering (P-RSoXS) has emerged as a powerful synchrotron-based tool that combines principles of X-ray scattering and X-ray spectroscopy. P-RSoXS provides unique sensitivity to molecular orientation and…

Probabilistic Circuits (PCs) are a general framework for tractable deep generative models, which support exact and efficient probabilistic inference on their learned distributions. Recent modeling and training advancements have enabled…

Machine Learning · Computer Science 2025-11-03 Anji Liu , Kareem Ahmed , Guy Van den Broeck