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Knowledge of a protein's atomic conformational ensemble is critical to determining its function, yet state-of-the-art ensemble prediction models are limited by lack of high-quality conformational data from simulation or experiment. Recent…

Machine Learning · Computer Science 2026-05-12 Jay Shenoy , Miro Astore , Axel Levy , Frédéric Poitevin , Sonya M. Hanson , Gordon Wetzstein

In this paper we propose an ab initio method to solve quantum many-body problems of molecular dynamics where both the electronic and the nuclear degrees are represented by ensembles of trajectories and guiding waves in physical space. Both…

Atomic Physics · Physics 2025-01-28 Ivan P. Christov

We present a new and improved method for simultaneous control of temperature and pressure in molecular dynamics simulations with periodic boundary conditions. The thermostat-barostat equations are build on our previously developed…

Statistical Mechanics · Physics 2014-11-20 Niels Grønbech-Jensen , Oded Farago

We study kinetic Monte-Carlo (KMC) descriptions of active particles. By relying on large discrete time steps, KMC algorithms accelerate the relaxational dynamics of active systems towards their steady-state. We show, however, that their…

Statistical Mechanics · Physics 2021-12-30 Juliane U. Klamser , Olivier Dauchot , Julien Tailleur

Continuum solvent models have become a standard technique in the context of electronic structure calculations, yet, no implementations have been reported capable to perform molecular dynamics at solid-liquid interfaces. We propose here such…

Chemical Physics · Physics 2015-05-13 Veronica M. Sanchez , Mariela Sued , Damian A. Scherlis

We examine the formulation and numerical treatment of dissipative particle dynamics (DPD) and momentum-conserving molecular dynamics. We show that it is possible to improve both the accuracy and the stability of DPD by employing a pairwise…

Computational Physics · Physics 2020-02-14 Benedict Leimkuhler , Xiaocheng Shang

We present the results of a classical molecular dynamic simulation as well as of an ab initio molecular dynamic simulation of an amorphous silica surface. In the case of the classical simulation we use the potential proposed by van Beest et…

Statistical Mechanics · Physics 2009-11-07 Claus Mischler , Walter Kob , Kurt Binder

Distributed model training suffers from communication bottlenecks due to frequent model updates transmitted across compute nodes. To alleviate these bottlenecks, practitioners use gradient compression techniques like sparsification,…

Machine Learning · Computer Science 2020-11-02 Saurabh Agarwal , Hongyi Wang , Kangwook Lee , Shivaram Venkataraman , Dimitris Papailiopoulos

Progress in the atomic-scale modelling of matter over the past decade has been tremendous. This progress has been brought about by improvements in methods for evaluating interatomic forces that work by either solving the electronic…

Langevin sampling from distributions of the form $p(x) \propto \exp(-\Psi(x))$ faces two major challenges: (global) mode coverage and (local) mode exploration. The first challenge is particularly relevant for multi-modal distributions with…

Statistics Theory · Mathematics 2026-05-08 Alexander Falk , Laurenz Nagler , Andreas Habring , Thomas Pock

A generalization of the Wasserstein metric, the integrated transportation distance, establishes a novel distance between probability kernels of Markov systems. This metric serves as the foundation for an efficient approximation technique,…

Machine Learning · Computer Science 2023-12-07 Zhengqi Lin , Andrzej Ruszczynski

Interacting-Particle Reaction Dynamics (iPRD) simulates the spatiotemporal evolution of particles that experience interaction forces and can react with one another. The combination of interaction forces and reactions enable a wide range of…

Chemical Physics · Physics 2018-07-20 Christoph Fröhner , Frank Noé

Unbiased stochastic sampling of the one- and two-body reduced density matrices is achieved in full configuration interaction quantum Monte Carlo with the introduction of a second, "replica" ensemble of walkers, whose population evolves in…

Computational Physics · Physics 2015-09-02 Robert E. Thomas , Daniel Opalka , Catherine Overy , Peter J. Knowles , Ali Alavi , George H. Booth

There are several approaches to describe flows with particles e.g. Lattice-Gas Automata (LGA), Lattice-Boltzmann method (LBM) or smoothed particle hydrodynamics (SPH). These approaches do not use fixed grids on which the Navier-Stokes…

Fluid Dynamics · Physics 2008-02-27 B. Ivancic

Deep learning applications require global optimization of non-convex objective functions, which have multiple local minima. The same problem is often found in physical simulations and may be resolved by the methods of Langevin dynamics with…

Machine Learning · Statistics 2021-05-24 Oleksandr Borysenko , Maksym Byshkin

We introduce CO2, an efficient algorithm to produce convexly-weighted coresets with respect to generic smooth divergences. By employing a functional Taylor expansion, we show a local equivalence between sufficiently regular losses and their…

Machine Learning · Statistics 2025-05-21 Alex Kokot , Alex Luedtke

We numerically investigate an adaptive version of the parareal algorithm in the context of molecular dynamics. This adaptive variant has been originally introduced in [F. Legoll, T. Lelievre and U. Sharma, SISC 2022]. We focus here on test…

Numerical Analysis · Mathematics 2022-12-21 Olga Gorynina , Frederic Legoll , Tony Lelievre , Danny Perez

While Born-Oppenheimer molecular dynamics (BOMD) has been widely studied by resorting to powerful methods in mathematical analysis, this paper presents a geometric formulation in terms of Hamilton's variational principle and…

Mathematical Physics · Physics 2023-07-20 Paul Bergold , Cesare Tronci

This article is concerned with a new filtered two-step variational integrator for solving the charged-particle dynamics in a mildly non-uniform moderate or strong magnetic field with a dimensionless parameter $\varepsilon$ inversely…

Numerical Analysis · Mathematics 2026-03-05 Ting Li , Bin Wang

New hybrid Molecular Dynamics-Monte Carlo methods are proposed to increase the efficiency of constant-pressure simulations. Two variations of the isobaric Molecular Dynamics component of the algorithms are considered. In the first, we use…

Soft Condensed Matter · Physics 2009-11-07 Roland Faller , Juan J. de Pablo
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