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Capturing the correct dynamics at the Coarse-Grained (CG) scale remains a central challenge in the advancement of systematic CG models for soft matter simulations. The Generalized Langevin Equation (GLE), rooted in the Mori-Zwanzig…

Soft Condensed Matter · Physics 2024-10-14 Jinu Jeong , Ishan Nadkarni , Narayana. R. Aluru

We introduce the spatial disorder-generalized Langevin equation (SD-GLE), a data-driven method for constructing coarse-grained (CG) dynamics in heterogeneous systems. Unlike conventional CG approaches that rely on a mean-field potential,…

Computational Physics · Physics 2026-04-21 Chuyi Liu , Yifeng Guan , Jingyuan Li , Mao Su

Coarse-grained molecular dynamics (CGMD) is a technique developed as a concurrent multiscale model that couples conventional molecular dynamics (MD) to a more coarse-grained description of the periphery. The coarse-grained regions are…

Materials Science · Physics 2009-11-11 Robert E. Rudd , Jeremy Q. Broughton

Equilibrium formally can be represented as an ensemble of uncoupled systems undergoing unbiased dynamics in which detailed balance is maintained. Many non-equilibrium processes can be described by suitable subsets of the equilibrium…

Conjugated organic molecules play a central role in a wide range of optoelectronic devices, including organic light-emitting diodes, organic field-effect transistors, and organic solar cells. A major bottleneck in the computational design…

Causal emergence (CE) based on effective information (EI) demonstrates that macro-states can exhibit stronger causal effects than micro-states in dynamics. However, the identification of CE and the maximization of EI both rely on…

Chaotic Dynamics · Physics 2025-11-25 Kaiwei Liu , Linli Pan , Zhipeng Wang , Mingzhe Yang , Bing Yuan , Jiang Zhang

The primary objective of this work is to develop coarse-graining schemes for stochastic many-body microscopic models and quantify their effectiveness in terms of a priori and a posteriori error analysis. In this paper we focus on stochastic…

Numerical Analysis · Mathematics 2007-05-23 Markos A. Katsoulakis , Petr Plechac , Luc Rey-Bellet , Dimitrios K. Tsagkarogiannis

Coarse-grained (CG) force field methods for molecular systems are a crucial tool to simulate large biological macromolecules and are therefore essential for characterisations of biomolecular systems. While state-of-the-art deep learning…

In computational materials science, coarse-graining approaches often lack a priori uncertainty quantification (UQ) tools that estimate the accuracy of a reduced-order model before it is calibrated or deployed. This is especially the case in…

Computational Physics · Physics 2018-12-11 Paul N. Patrone , Andrew M. Dienstfrey , Geoffrey B. McFadden

Coarse-graining is a molecular modeling technique in which an atomistic system is represented in a simplified fashion that retains the most significant system features that contribute to a target output, while removing the degrees of…

Cellular automata and other discrete dynamical systems have long been studied as models of emergent complexity. Recently, neural cellular automata have been proposed as models to investigate the emerge of a more general artificial…

Cellular Automata and Lattice Gases · Physics 2025-07-28 Sanyam Jain , Stefano Nichele

In this paper, we examine how to build coarse-grain transport models consistently from the kinetic to fluid regimes. The internal energy of the gas particles is described through a state-to-state approach. A kinetic equation allows us to…

Fluid Dynamics · Physics 2021-03-15 Erik Torres , Georgios Bellas-Chatzigeorgis , Thierry E. Magin

Coarse-graining is central to reducing dimensionality in molecular dynamics, and is typically characterized by a mapping which projects the full state of the system to a smaller class of variables. While extensive literature has been…

Probability · Mathematics 2020-01-08 Frédéric Legoll , Tony Lelièvre , Upanshu Sharma

We discuss a Bayesian formulation to coarse-graining (CG) of PDEs where the coefficients (e.g. material parameters) exhibit random, fine scale variability. The direct solution to such problems requires grids that are small enough to resolve…

Machine Learning · Statistics 2019-09-10 Constantin Grigo , Phaedon-Stelios Koutsourelakis

An issue for molecular dynamics simulations is that events of interest often involve timescales that are much longer than the simulation time step, which is set by the fastest timescales of the model. Because of this timescale separation,…

Statistical Mechanics · Physics 2024-08-15 John Strahan , Chatipat Lorpaiboon , Jonathan Weare , Aaron R. Dinner

Molecular dynamics (MD) simulation is essential for various scientific domains but computationally expensive. Learning-based force fields have made significant progress in accelerating ab-initio MD simulation but are not fast enough for…

Machine Learning · Computer Science 2023-08-29 Xiang Fu , Tian Xie , Nathan J. Rebello , Bradley D. Olsen , Tommi Jaakkola

This work presents a novel framework governing the development of an efficient, accurate, and transferable coarse-grained (CG) model of a polyether material. The proposed framework combines the two fundamentally different classical…

Coarse-grained (CG) models are often parametrized to reproduce one-dimensional structural correlation functions of an atomically-detailed model along the degrees of freedom governing each interaction potential. While cross correlations…

Soft Condensed Matter · Physics 2019-12-02 Svenja J. Woerner , Tristan Bereau , Kurt Kremer , Joseph F. Rudzinski

In a recent paper, J. Chem. Phys. 162, 214101 (2025), a novel approach for the rigidification of a molecular cluster was proposed, in which starting with an all-atom (AA) potential, a coarse-grained (CG) potential for the associated cluster…

Chemical Physics · Physics 2025-09-08 João V. M. Pimentel , Vladimir A. Mandelshtam

Incorporating atomistic and molecular information into models of cellular behaviour is challenging because of a vast separation of spatial and temporal scales between processes happening at the atomic and cellular levels. Multiscale or…

Computational Physics · Physics 2019-08-28 Radek Erban