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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 2020-08-26 Sebastian Kaltenbach , Phaedon-Stelios Koutsourelakis

The coarse-graining approach to deriving the quantum Markovian master equation is revisited, with close attention given to the underlying approximations. It is further argued that the time interval over which the coarse-graining is…

Quantum Physics · Physics 2017-12-05 J D Cresser , C Facer

We systematically derive an exact coarse-grained description for interacting particles with thermodynamically consistent stochastic dynamics, applicable across different observation scales, the mesoscopic and the macroscopic. We implement…

Statistical Mechanics · Physics 2026-03-05 Atul Tanaji Mohite , Heiko Rieger

The integral equation coarse-graining (IECG) approach is a promising high-level coarse-graining (CG) method for polymer melts, with variable resolution from soft spheres to multi CG sites, which preserves the structural and thermodynamical…

Soft Condensed Matter · Physics 2018-07-24 Mohammadhasan Dinpajooh , Marina G. Guenza

Coarse-grained (CG) conformational surface hopping (SH) adapts the concept of multisurface dynamics, initially developed to describe electronic transitions in chemical reactions, to accurately describe classical molecular dynamics at a…

Soft Condensed Matter · Physics 2021-02-03 Joseph F. Rudzinski , Tristan Bereau

We describe a general simulation scheme for assessing the thermodynamic consequences of neglecting many-body effects in coarse-grained models of complex fluids. The method exploits the fact that the asymptote of a simple-to-measure…

Soft Condensed Matter · Physics 2014-03-19 Douglas J. Ashton , Nigel B. Wilding

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

We present a method that exploits self-consistent simulation of coarse-grained and fine-grained models, in order to analyse properties of physical systems. The method uses the coarse-grained model to obtain a first estimate of the quantity…

Statistical Mechanics · Physics 2020-01-08 Hideki Kobayashi , Paul B. Rohrbach , Robert Scheichl , Nigel B. Wilding , Robert L. Jack

Bottom-up coarse-grained (CG) modeling expands the spatial and temporal scales of molecular simulation by seeking a reduced, thermodynamically consistent representation of an atomistic model. Developments in CG theory have largely focused…

Chemical Physics · Physics 2025-03-28 Patrick G. Sahrmann , Gregory A. Voth

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…

Coarse-grained (CG) models can provide computationally efficient and conceptually simple characterizations of soft matter systems. While generic models probe the underlying physics governing an entire family of free-energy landscapes,…

Soft Condensed Matter · Physics 2019-08-15 Joseph F. Rudzinski

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

Even though atomistic and coarse-grained (CG) models have been used to simulate liquid nanodroplets in vapor, very few rigorous studies of the liquid-liquid interface structure are available, and most of them are limited to planar…

Chemical Physics · Physics 2019-07-16 Peiyuan Gao , Xiu Yang , Alexandre M. Tartakovsky

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

We introduce a general framework for constructing coarse-grained potential models without ad hoc approximations such as limiting the potential to two- and/or three-body contributions. The scheme, called Deep Coarse-Grained Potential…

Chemical Physics · Physics 2018-08-15 Linfeng Zhang , Jiequn Han , Han Wang , Roberto Car , Weinan E

Machine-learned (ML) coarse-grained (CG) models are a promising tool for significantly enhancing the efficiency of molecular simulations by systematically removing degrees of freedom while retaining fidelity to the underlying fine-grained…

Chemical Physics · Physics 2026-02-27 Patrick G. Sahrmann , Benjamin T. Nebgen , Kipton Barros , Brenden W. Hamilton

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…

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

Coarse-graining (CG) of molecular simulations simplifies the particle representation by grouping selected atoms into pseudo-beads and drastically accelerates simulation. However, such CG procedure induces information losses, which makes…

Machine Learning · Computer Science 2022-06-20 Wujie Wang , Minkai Xu , Chen Cai , Benjamin Kurt Miller , Tess Smidt , Yusu Wang , Jian Tang , Rafael Gómez-Bombarelli

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