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Related papers: Recent progress towards chemically-specific coarse…

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Coarse-graining (CG) reduces molecular details to extend the time and length scales of molecular dynamics simulations to microseconds and micrometers. However, the CG approaches have long been limited by the difficulty of constructing both…

Chemical Physics · Physics 2026-05-06 Kevin V. Bigting , Shubhadeep Nag , Yaxin An

In this work, we review previously developed coarse-grained (CG) particle models for biological membrane and red blood cells (RBCs) and discuss the advantages of the CG particle method over the continuum and atomic simulations on modeling…

Soft Condensed Matter · Physics 2017-07-18 He Li , Hung-yu Chang , Jun Yang , Lu Lu , George Lykotrafitis

This work explores the trade-off between the number of samples required to accurately build models of dynamical systems and the degradation of performance in various control objectives due to a coarse approximation. In particular, we show…

Optimization and Control · Mathematics 2017-12-01 Stephen Tu , Ross Boczar , Andrew Packard , Benjamin Recht

For optimal processing and design of entangled polymeric materials it is important to establish a rigorous link between the detailed molecular composition of the polymer and the viscoelastic properties of the macroscopic melt. We review…

Soft Condensed Matter · Physics 2015-05-27 J. T. Padding , W. J. Briels

We formulate an effective-description framework for the dynamics of open quantum systems by extending the time-coarse-graining formalism to open systems. Our coarse-graining procedure efficiently removes high-frequency processes which are…

Quantum Physics · Physics 2018-01-17 Chang-Woo Lee , Changsuk Noh , Jaewan Kim

An important challenge in robotics is understanding the interactions between robots and deformable terrains that consist of granular material. Granular flows and their interactions with rigid bodies still pose several open questions. A…

Machine Learning · Computer Science 2021-11-22 Amin Haeri , Krzysztof Skonieczny

Differentiable physics modeling combines physics models with gradient-based learning to provide model explicability and data efficiency. It has been used to learn dynamics, solve inverse problems and facilitate design, and is at its…

Machine Learning · Computer Science 2022-02-02 Deshan Gong , Zhanxing Zhu , Andrew J. Bulpitt , He Wang

Data-driven emulation of nonlinear dynamics is challenging due to long-range skill decay that often produces physically unrealistic outputs. Recent advances in generative modeling aim to address these issues by providing uncertainty…

Machine Learning · Computer Science 2025-10-28 Juan Nathaniel , Pierre Gentine

Soft Glassy Materials (SGM) consist in dense amorphous assemblies of colloidal particles of multiple shapes, elasticity, and interactions, which confer upon them solid-like properties at rest. They are ubiquitously encountered in modern…

A valuable step in the modeling of multiscale dynamical systems in fields such as computational chemistry, biology, materials science and more, is the representative sampling of the phase space over long timescales of interest; this task is…

Machine Learning · Computer Science 2023-12-29 Ellis R. Crabtree , Juan M. Bello-Rivas , Ioannis G. Kevrekidis

Mathematical modelling of biological population dynamics often involves proposing high fidelity discrete agent-based models that capture stochasticity and individual-level processes. These models are often considered in conjunction with an…

Dynamical Systems · Mathematics 2023-12-20 Daniel J. VandenHeuvel , Pascal R. Buenzli , Matthew J. Simpson

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

A coarse-grained simulation model eliminates microscopic degrees of freedom and represents a polymer by a simplified structure. A priori, two classes of coarse-grained models may be distinguished: those which are designed for a specific…

Soft Condensed Matter · Physics 2007-05-23 J. Baschnagel , J. P. Wittmer , H. Meyer

Molecular Dynamics (MD) simulations are essential for accurately predicting the physical and chemical properties of large molecular systems across various pressure and temperature ensembles. However, the high computational costs associated…

We present recent results on coarse-graining techniques for thermodynamic quantities (canonical averages) and dynamical quantities (averages of path functionals over solutions of overdamped Langevin equations). The question is how to obtain…

Probability · Mathematics 2010-08-24 Frederic Legoll , Tony Lelievre

A brief review of modeling and simulation methods for a study of polymers at interfaces is provided. When studying truly multiscale problems as provided by realistic polymer systems, coarse graining is practically unavoidable. In this…

Soft Condensed Matter · Physics 2009-10-19 Fathollah Varnik , Kurt Binder

We propose a highly coarse-grained simulation model for crystalline polymer solids with crystalline lamellar structures. The mechanical properties of a crystalline polymer solid are mainly determined by the crystalline lamellar structures.…

Soft Condensed Matter · Physics 2025-01-13 Takashi Uneyama

Coarse-grained (CG) models parameterized using atomistic reference data, i.e., 'bottom up' CG models, have proven useful in the study of biomolecules and other soft matter. However, the construction of highly accurate, low resolution CG…

Applying an excess entropy scaling formalism to the coarse-grained (CG) dynamics of liquids, we discovered that missing rotational motions during the CG process are responsible for artificially accelerated CG dynamics. In the context of the…

Chemical Physics · Physics 2024-09-27 Jaehyeok Jin , Gregory A. Voth

With increasing interest in the use of glassy carbon (GC) for a wide variety of application areas, the need for developing fundamental understanding of its mechanical properties has come to the forefront. Further, recent theoretical and…

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