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As the most important solvent, water has been at the center of interest since the advent of computer simulations. While early molecular dynamics and Monte Carlo simulations had to make use of simple model potentials to describe the atomic…

Soft Condensed Matter · Physics 2024-02-01 Amir Omranpour , Pablo Montero De Hijes , Jörg Behler , Christoph Dellago

Markov decision processes (MDPs) are known to be sensitive to parameter specification. Distributionally robust MDPs alleviate this issue by allowing for \emph{ambiguity sets} which give a set of possible distributions over parameter sets.…

Optimization and Control · Mathematics 2021-05-05 Julien Grand-Clément , Christian Kroer

By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semi-local density functional theory (DFT), and thereby furnish a more accurate and reliable description of the electronic structure in…

Computational Physics · Physics 2021-05-10 Hsin-Yu Ko , Junteng Jia , Biswajit Santra , Xifan Wu , Roberto Car , Robert A. DiStasio

This paper presents a new code for performing multidimensional radiation hydrodynamic (RHD) simulations on parallel computers involving anisotropic radiation fields and nonequilibrium effects. The radiation evolution modules described here…

Astrophysics · Physics 2009-11-07 John C. Hayes , Michael L. Norman

We present a new adaptive resolution technique for efficient particle-based multiscale molecular dynamics (MD) simulations. The presented approach is tailor-made for molecular systems where atomistic resolution is required only in spatially…

Soft Condensed Matter · Physics 2007-05-23 Matej Praprotnik , Luigi Delle Site , Kurt Kremer

We propose a new, nonparametric approach to learning and representing transition dynamics in Markov decision processes (MDPs), which can be combined easily with dynamic programming methods for policy optimisation and value estimation. This…

Machine Learning · Computer Science 2012-06-22 Steffen Grunewalder , Guy Lever , Luca Baldassarre , Massi Pontil , Arthur Gretton

Explicit simulations of fluid mixtures of highly size-dispersed particles are constrained by numerical challenges associated with identifying pair-interaction neighbors. Recent algorithmic developments have ameliorated these difficulties to…

Soft Condensed Matter · Physics 2022-12-07 Joseph M. Monti , Gary S. Grest

Three dimensional implementations of liquid state theories offer an efficient alternative to computer simulations for the atomic-level description of aqueous solutions in complex environments. In this context, we present a (classical)…

Chemical Physics · Physics 2013-02-13 Guillaume Jeanmairet , Maximilien Levesque , Rodolphe Vuilleumier , Daniel Borgis

Aqueous solid-liquid interfaces (SLI) are ubiquitous in nature and technology, often hosting molecular-level processes with macroscopic consequences. Molecular dynamics (MD) simulations offer a tool of choice to investigate interfacial…

Soft Condensed Matter · Physics 2025-08-12 Mahdi Tavakol , Kislon Voïtchovsky

An accurate algorithm is proposed to improve the prediction of a particle in collision with a moving wall within the direct simulation Monte Carlo (DSMC) framework for the simulation of unsteady rarefied flows. This algorithm is able to…

Computational Physics · Physics 2021-09-29 He Zhang , Fanli Shan , Hong Fang , Xing Zhang , Jun Zhang , Jinghua Sun

Theoretical and experimental investigations of water vapor interaction with porous materials are very needful for various fields of science and technology. Not only studies of the interaction of water vapor and porous material as a…

Computational Physics · Physics 2018-12-20 V. V. Korenkov , E. G. Nikonov , M. Popovičová

Multi-particle collision dynamics is an appealing numerical technique aiming at simulating fluids at the mesoscopic scale. It considers molecular details in a coarse-grained fashion and reproduces hydrodynamic phenomena. Here, the…

Soft Condensed Matter · Physics 2019-03-28 H. Híjar

We report a novel hybrid method of simultaneous atomistic simulation of solids in critical regions (contacts surfaces, cracks areas, etc.), along with continuum modeling of other parts. The continuum is treated in terms of quasi-atoms of…

Materials Science · Physics 2026-02-17 Artem Chuprov , Egor E. Nuzhin , Alexey A. Tsukanov , Nikolay V. Brilliantov

Atomistic simulations of the experimental W L$_3$-edge extended X-ray absorption fine structure (EXAFS) of bcc tungsten at T = 300 K were performed using classical molecular dynamics (MD) and reverse Monte Carlo (RMC) methods. The MD-EXAFS…

Materials Science · Physics 2018-02-27 Inga Jonane , Andris Anspoks , Alexei Kuzmin

It was recently demonstrated that a simple Monte Carlo (MC) algorithm involving the swap of particle pairs dramatically accelerates the equilibrium sampling of simulated supercooled liquids. We propose two numerical schemes integrating the…

Statistical Mechanics · Physics 2019-06-24 Ludovic Berthier , Elijah Flenner , Christopher J. Fullerton , Camille Scalliet , Murari Singh

Accurately simulating the properties of liquid water remains a central challenge in molecular simulations. In this work, we use machine learning potentials to investigate how the convergence settings of electronic structure calculations…

Chemical Physics · Physics 2026-03-24 Hubert Beck , Ondrej Marsalek

The field of complex networks studies a wide variety of interacting systems by representing them as networks. To understand their properties and mutual relations, the randomisation of network connections is a commonly used tool. However,…

Statistical Mechanics · Physics 2024-10-18 Noam Abadi , Franco Ruzzenenti

Quantum mechanics based ab-initio molecular dynamics (MD) simulation schemes offer an accurate and direct means to monitor the time-evolution of materials. Nevertheless, the expensive and repetitive energy and force computations required in…

Materials Science · Physics 2014-10-14 Venkatesh Botu , Rampi Ramprasad

The principle of maximum entropy is a broadly applicable technique for computing a distribution with the least amount of information possible while constrained to match empirically estimated feature expectations. However, in many real-world…

Machine Learning · Computer Science 2022-08-16 Kenneth Bogert , Yikang Gui , Prashant Doshi

Simulating the dynamics of ions near polarizable nanoparticles (NPs) using coarse-grained models is extremely challenging due to the need to solve the Poisson equation at every simulation timestep. Recently, a molecular dynamics (MD) method…

Computational Physics · Physics 2019-11-01 JCS Kadupitiya , Geoffrey C. Fox , Vikram Jadhao