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Predicting the molecular friction and energy landscapes under nonequilibrium conditions is key to coarse-graining the dynamics of selective solute transport through complex, fluctuating and responsive media, e.g., polymeric materials such…

Soft Condensed Matter · Physics 2025-07-03 Sebastian Milster , Joachim Dzubiella , Gerhard Stock , Steffen Wolf

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

In this paper, we discuss information-theoretic tools for obtaining optimized coarse-grained molecular models for both equilibrium and non-equilibrium molecular dynamics. The latter are ubiquitous in physicochemical and biological…

Numerical Analysis · Mathematics 2016-04-20 Vagelis Harmandaris , Evangelia Kalligiannaki , Markos A. Katsoulakis , Petr Plecháč

We derive a mesoscopic modeling and simulation technique that is very close to the technique known as dissipative particle dynamics. The model is derived from molecular dynamics by means of a systematic coarse-graining procedure. Thus the…

Soft Condensed Matter · Physics 2009-10-31 Eirik G. Flekkoy , Peter V. Coveney , Gianni De Fabritiis

To study materials phenomena simultaneously at various length scales, descriptions in which matter can be coarse grained to arbitrary levels, are necessary. Attempts to do this in the static regime (i.e. zero temperature) have already been…

Materials Science · Physics 2009-11-07 Stefano Curtarolo , Gerbrand Ceder

In recent years, simulation methods based on the scaling of atomic potential functions, such as quasi-coarse-grained dynamics and coarse-grained dynamics, have shown promising results for modeling crystalline systems at multiple scales.…

Mesoscale and Nanoscale Physics · Physics 2024-09-11 Dong-Dong Jiang , Jian-Li Shao

Active matter physics and swarm robotics have provided powerful tools for the study and control of ensembles driven by internal sources. At the macroscale, controlling swarms typically utilizes significant memory, processing power, and…

We present an effective evolution equation for a coarse-grained distribution function of a long-range-interacting system preserving the symplectic structure of the non-collisional Boltzmann, or Vlasov, equation. We first derive a general…

Statistical Mechanics · Physics 2020-07-01 Guido Giachetti , Alessandro Santini , Lapo Casetti

This work presents a rigorous framework based on coarse-graining to analyze highly compressible turbulence. We show how the requirement that viscous effects on the dynamics of large-scale momentum and kinetic energy be negligible ---an…

Fluid Dynamics · Physics 2012-12-27 Hussein Aluie

Coarse-grained (CG) models are simplified representations of soft matter systems that are commonly employed to overcome size and time limitations in computational studies. Many approaches have been developed to construct and parametrise…

Statistical Mechanics · Physics 2022-09-27 Piero Luchi , Roberto Menichetti , Gianluca Lattanzi , Raffaello Potestio

Dynamical systems with large state-spaces are often expensive to thoroughly explore experimentally. Coarse-graining methods aim to define simpler systems which are more amenable to analysis and exploration; most current methods, however,…

Systems and Control · Computer Science 2016-11-01 Michalis Michaelides , Dimitrios Milios , Jane Hillston , Guido Sanguinetti

I briefly review some concepts related to coarse-graining methods for the dynamics of soft matter systems and argue that such schemes will almost always need to telescope down the physical hierarchy of time-scales to a more compressed, but…

Soft Condensed Matter · Physics 2010-01-11 Ard A. Louis

Self-organized pattern formation is vital for many biological processes. Reaction-diffusion models have advanced our understanding of how biological systems develop spatial structures, starting from homogeneity. However, biological…

Modelling micro- and meso-scopic scale thermodynamic and transport properties of soft condensed matter hinges upon its representation. This is especially relevant for polar solvents such as water, since these require effective…

Soft Condensed Matter · Physics 2026-04-17 Michael A. Seaton , Benjamin T. Speake , Ilian T. Todorov

A computational tool for coarse-graining nonlinear systems of ordinary differential equations in time is discussed. Three illustrative model examples are worked out that demonstrate the range of capability of the method. This includes the…

Numerical Analysis · Mathematics 2017-11-23 Sabyasachi Chatterjee , Amit Acharya , Zvi Artstein

Statistical (machine learning) tools for equation discovery require large amounts of data that are typically computer generated rather than experimentally observed. Multiscale modeling and stochastic simulations are two areas where learning…

Machine Learning · Statistics 2021-03-17 Joseph Bakarji , Daniel M. Tartakovsky

Understanding how microscopic motility shapes emergent collective behaviors is a challenging task in active matter, especially when self-propulsion is regulated by external cues or via quorum-sensing interactions. To address this problem,…

Statistical Mechanics · Physics 2026-04-13 Alberto Dinelli , Pietro Luigi Muzzeddu

In soft matter systems the local displacement field can be accessed directly by video microscopy enabling one to compute local strain fields and hence the elastic moduli using a coarse-graining procedure. We study this process for a simple…

Soft Condensed Matter · Physics 2015-05-14 K. Franzrahe , P. Nielaba , S. Sengupta

We present a novel thermodynamically guided, low-noise, time-scale bridging, and pertinently efficient strategy for the dynamic simulation of microscopic models for complex fluids. The systematic coarse-graining method is exemplified for…

Soft Condensed Matter · Physics 2010-11-12 Patrick Ilg , Hans Christian Öttinger , Martin Kröger

The data-based discovery of effective, coarse-grained (CG) models of high-dimensional dynamical systems presents a unique challenge in computational physics and particularly in the context of multiscale problems. The present paper offers a…

Computational Physics · Physics 2021-02-10 Sebastian Kaltenbach , Phaedon-Stelios Koutsourelakis