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Machine learning interatomic potentials (MLIPs) have become powerful tools to extend molecular simulations beyond the limits of quantum methods, offering near-quantum accuracy at much lower computational cost. Yet, developing reliable MLIPs…

Materials Science · Physics 2025-12-30 Adam Lahouari , Jutta Rogal , Mark E. Tuckerman

Machine learning potentials have achieved great success in accelerating atomistic simulations. Many of them relying on atom-centered local descriptors are natural for parallelization. More recent message passing neural network (MPNN) models…

Chemical Physics · Physics 2025-06-10 Junfan Xia , Bin Jiang

We investigate a hybrid numerical algorithm aimed at the large-scale cosmological N-body simulation for the on-going and the future high precious sky surveys. It makes use of a truncated Fast Multiple Method (FMM) for short-range gravity,…

Computational Physics · Physics 2021-01-13 Qiao Wang

The parallel full approximation scheme in space and time (PFASST) is a parallel-in-time integrator that allows to integrate multiple time-steps simultaneously. It has been shown to extend scaling limits of spatial parallelization strategies…

Numerical Analysis · Mathematics 2021-03-18 Oliver Sander , Ruth Schöbel , Robert Speck

We consider the coupled system of equations that describe flow in fractured porous media. To describe such types of problems, multicontinuum and multiscale approaches are used. Because in multicontinuum models, the permeability of each…

Numerical Analysis · Mathematics 2023-05-31 Maria Vasilyeva

Molecular simulations in an open environment, involving ion exchange, are necessary to study various systems, from biosystems to confined electrolytes. However, grand-canonical simulations are often computationally demanding in condensed…

Chemical Physics · Physics 2023-11-13 Jeongmi Kim , Luc Belloni , Benjamin Rotenberg

Many natural phenomena involve processes that happen simultaneously at different characteristic length- and timescales. Typically, the region where the process of interest happens is affected by fluctuations in its surroundings. Modeling…

Materials Science · Physics 2026-04-24 Hari Haran Sudhakar , Alessandra Serva , Rocio Semino

High power lasers are used for a variety of manufacturing processes on time and length scales that cover many orders of magnitude and on different materials. The variety of processes achievable through laser-material interaction results…

Combining the time-dependent variational principle (TDVP) algorithm with the parallelization scheme introduced by Stoudenmire and White for the density matrix renormalization group (DMRG), we present the first parallel matrix product state…

The molecular dynamics simulation code ls1 mardyn is presented. It is a highly scalable code, optimized for massively parallel execution on supercomputing architectures, and currently holds the world record for the largest molecular…

We present a computational framework for modeling large-scale particle-laden flows in complex domains with the goal of enabling simulations in medical-image derived patient specific geometries. The framework is based on a volume-filtered…

Fluid Dynamics · Physics 2023-11-28 Abhilash Reddy Malipeddi , C. Alberto Figueroa , Jesse Capecelatro

Despite the enormous success of Hamiltonian Monte Carlo and related Markov Chain Monte Carlo (MCMC) methods, sampling often still represents the computational bottleneck in scientific applications. Availability of parallel resources can…

Computation · Statistics 2026-01-26 Jakob Robnik , Uroš Seljak

Molecular dynamics simulations are an invaluable tool in numerous scientific fields. However, the ubiquitous classical force fields cannot describe reactive systems, and quantum molecular dynamics are too computationally demanding to treat…

Chemical Physics · Physics 2022-08-09 Xiangyun Lei , Andrew J. Medford

We present a new method to couple the Direct Simulation Monte Carlo (DSMC) algorithm with molecular dynamics (MD). The coupling approach generalizes prior coupling methods using a cell-based decision. The approach is supported by a lifting…

Computational Physics · Physics 2025-06-03 Tim Linke , Dane Sterbentz , Niels Grønbech-Jensen , Jean-Pierre Delplanque , Jonathan Belof

A novel finite element framework is proposed for the numerical simulation of two phase flows with surface tension. The Level-Set (LS) method with piece-wise quadratic (P2) interpolation for the liquid-gas interface is used in order to reach…

Computational Engineering, Finance, and Science · Computer Science 2020-10-27 Modesar Shakoor , Chung Hae Park

The EHP and the MCAP provide new rigorous weak variational formalism for a broad range of initial boundary value problems in mathematical physics and mechanics. Both approaches utilize the mixed formulation and lead to the development of…

Dynamical Systems · Mathematics 2013-11-19 Jinkyu Kim

This paper presents the Parallel Coupler for Multimodel Simulations (PCMS), a new GPU accelerated generalized coupling framework for coupling simulation codes on leadership class supercomputers. PCMS includes distributed control and field…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-22 Jacob S. Merson , Cameron W. Smith , Mark S. Shephard , Fuad Hasan , Abhiyan Paudel , Angel Castillo-Crooke , Joyal Mathew , Mohammad Elahi

A multi-scale framework was recently proposed for more realistic molecular dynamics simulations in continuum solvent models by coupling a molecular mechanics treatment of solute with a fluid mechanics treatment of solvent, where we…

Biological Physics · Physics 2018-01-17 Li Xiao , Ray Luo

The use of nonlinear PDEs has led to significant advancements in various fields, such as physics, biology, ecology, and quantum mechanics. However, finding multiple solutions for nonlinear PDEs can be a challenging task, especially when…

Numerical Analysis · Mathematics 2025-04-11 Wenrui Hao , Sun Lee , Young Ju Lee

The definition of a Neural Network architecture is one of the most critical and challenging tasks to perform. In this paper, we propose ParallelMLPs. ParallelMLPs is a procedure to enable the training of several independent Multilayer…

Machine Learning · Computer Science 2022-06-20 Felipe Costa Farias , Teresa Bernarda Ludermir , Carmelo Jose Albanez Bastos-Filho