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Intracellular protein patterns govern essential cellular functions by dynamically redistributing proteins between membrane-bound and cytosolic states, conserving their total numbers. This review presents a theoretical framework for…

Biological Physics · Physics 2025-12-16 Erwin Frey , Henrik Weyer

Coarse-graining has become an area of tremendous importance within many different research fields. For molecular simulation, coarse-graining bears the promise of finding simplified models such that long-time simulations of large-scale…

Chemical Physics · Physics 2019-09-04 Feliks Nüske , Lorenzo Boninsegna , Cecilia Clementi

Coarse graining enables the investigation of molecular dynamics for larger systems and at longer timescales than is possible at atomic resolution. However, a coarse graining model must be formulated such that the conclusions we draw from it…

Understanding the structure and dynamics of liquids is pivotal for the study of larger spatiotemporal processes, especially in glass-forming materials at low temperatures. Density scaling, observed in many molecular systems through…

Soft Condensed Matter · Physics 2024-10-29 Jaehyeok Jin , David R. Reichman , Jeppe C. Dyre , Ulf R. Pedersen

Structure-based coarse graining of molecular systems offers a systematic route to reproduce the many-body potential of mean force. Unfortunately, common strategies are inherently limited by the molecular mechanics force field employed.…

Soft Condensed Matter · Physics 2018-12-27 Tristan Bereau , Joseph F. Rudzinski

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems…

Machine Learning · Computer Science 2025-12-30 Quercus Hernandez , Max Win , Thomas C. O'Connor , Paulo E. Arratia , Nathaniel Trask

Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insight by isolating the essential degrees of freedom that dictate the…

Statistical Mechanics · Physics 2023-04-12 Shriram Chennakesavalu , David J. Toomer , Grant M. Rotskoff

In many far-from-equilibrium biological systems, energy injected by irreversible processes at microscopic scales propagates to larger scales to fulfill important biological functions. But given dissipative dynamics at the microscale, how…

Statistical Mechanics · Physics 2025-06-03 Qiwei Yu , Matthew P. Leighton , Christopher W. Lynn

Simulations of condensed matter systems often focus on the dynamics of a few distinguished components but require integrating the dynamics of the full system. A prime example is a molecular dynamics simulation of a (macro)molecule in…

Computational Physics · Physics 2024-03-12 Mauricio J. del Razo , Daan Crommelin , Peter G. Bolhuis

In this paper, a methodology for fine scale modeling of large scale structures is proposed, which combines the variational multiscale method, domain decomposition and model order reduction. The influence of the fine scale on the coarse…

Computational Engineering, Finance, and Science · Computer Science 2023-07-06 Philipp Diercks , Karen Veroy , Annika Robens-Radermacher , Jörg F. Unger

Structural and thermodynamic consistency of coarse-graining models across multiple length scales is essential for the predictive role of multi-scale modeling and molecular dynamic simulations that use mesoscale descriptions. Our approach is…

Soft Condensed Matter · Physics 2014-07-04 J. McCarty , A. J. Clark , J. Copperman , M. G. Guenza

Spatial fields in the Earth and environmental sciences are often available at multiple scales or resolutions. While coarse-scale data (e.g., from global circulation models) are often abundant, they lack the local detail provided by…

Methodology · Statistics 2026-04-01 Alejandro Calle-Saldarriaga , Paul F. V. Wiemann , Matthias Katzfuss

Coarse-graining techniques play a central role in reducing the complexity of stochastic models, and are typically characterised by a mapping which projects the full state of the system onto a smaller set of variables which captures the…

Probability · Mathematics 2023-09-28 Bastian Hilder , Upanshu Sharma

Making sense of complex inhomogeneous systems composed of many interacting species is a grand challenge that pervades basically all natural sciences. Phase separation and pattern formation in reaction-diffusion systems have been largely…

Soft Condensed Matter · Physics 2025-06-04 Joshua F. Robinson , Thomas Machon , Thomas Speck

Developing physics-based models for molecular simulation requires fitting many unknown parameters to diverse experimental datasets. Traditionally, this process is piecemeal and difficult to reproduce, leading to a fragmented landscape of…

Biological Physics · Physics 2025-04-10 Ryan K. Krueger , Megan C. Engel , Ryan Hausen , Michael P. Brenner

Multiscale molecular modeling is widely applied in scientific research of molecular properties over large time and length scales. Two specific challenges are commonly present in multiscale modeling, provided that information between the…

Computational Physics · Physics 2024-07-23 Jun Zhang , Xiaohan Lin , Weinan E , Yi Qin Gao

Hybrid multiscale modelling has emerged as a useful framework for modelling complex biological phenomena. However, when accounting for stochasticity in the internal dynamics of agents, these models frequently become computationally…

Quantitative Methods · Quantitative Biology 2021-05-11 Daria Stepanova , Helen M. Byrne , Philip K. Maini , Tomás Alarcón

We review some recent coarse-graining and multi-scale methods, but also put forward some new ideas for addressing such issues. We find that, if one is guided by nonequilibrium statistical mechanics and thermodynamics, it is possible to…

Soft Condensed Matter · Physics 2009-11-06 Patrick Ilg , Vlasis Mavrantzas , Hans Christian Öttinger

Due to the wide range of timescales that are present in macromolecular systems, hierarchical multiscale strategies are necessary for their computational study. Coarse-graining (CG) allows to establish a link between different system…

High-dimensional recordings of dynamical processes are often characterized by a much smaller set of effective variables, evolving on low-dimensional manifolds. Identifying these latent dynamics requires solving two intertwined problems:…

Machine Learning · Computer Science 2026-01-21 Manuel Hinz , Maximilian Mauel , Patrick Seifner , David Berghaus , Kostadin Cvejoski , Ramses J. Sanchez
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