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Recently a number of approaches has been developed to connect the microscopic dynamics of particle systems to the macroscopic properties of systems in nonequilibrium stationary states, via the theory of dynamical systems. This way a direct…

Statistical Mechanics · Physics 2009-10-31 L. Rondoni , E. G. D. Cohen

Coarse-grained (CG) modeling has gained significant attention in recent years due to its wide applicability in enhancing the spatiotemporal scales of molecular simulations. While CG simulations, often performed with Hamiltonian mechanics,…

Chemical Physics · Physics 2025-04-01 Jaehyeok Jin , Gregory A. Voth

We study coarse-graining methods for stochastic differential equations. In particular we consider averaging and a type of projection operator method, sometimes referred to as effective dynamic via conditional expectations. The projection…

Probability · Mathematics 2025-06-19 Manh Hong Duong , Carsten Hartmann , Michela Ottobre

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

Coarse graining techniques play an essential role in accelerating molecular simulations of systems with large length and time scales. Theoretically grounded bottom-up models are appealing due to their thermodynamic consistency with the…

Computational Physics · Physics 2022-11-01 Blake R. Duschatko , Jonathan Vandermause , Nicola Molinari , Boris Kozinsky

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

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

We investigate nonequilibrium steady-state dynamics in both continuous- and discrete-state stochastic processes. Our analysis focuses on planar diffusion dynamics and their coarse-grained approximations by discrete-state Markov chains.…

Statistical Mechanics · Physics 2026-05-12 Ramón Nartallo-Kaluarachchi , Renaud Lambiotte , Alain Goriely

A binary fluid mixture in contact with lateral particle reservoirs is considered. By imposing different particle concentrations in these reservoirs, the system can be maintained under controlled non-equilibrium conditions. Previous…

Statistical Mechanics · Physics 2026-04-01 O. Politano , Alejandro L. Garcia , F. Baras , M. Malek Mansour

Fluctuating hydrodynamics provides a quantitative, large-scale description of many-body systems in terms of smooth variables, with microscopic details entering only through a small set of transport coefficients. Although this framework has…

Statistical Mechanics · Physics 2026-01-06 Soumyabrata Saha , Sandeep Jangid , Thibaut Arnoulx de Pirey , Juliane U. Klamser , Tridib Sadhu

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 the context of the recently developed "equation-free" approach to the computer-assisted analysis of complex systems, we illustrate the computation of coarsely self-similar solutions. Dynamic renormalization and fixed point algorithms for…

Computational Physics · Physics 2007-05-23 L. Chen , P. G. Debenedetti , C. W. Gear , I. G. Kevrekidis

Coarse-grained (CG) models provide an effective route to reducing the complexity of molecular simulations (MD), but conventional approaches depend heavily on long all-atom MD trajectories to adequately sample configurational space. This…

Chemical Physics · Physics 2025-10-28 Maximilian Stupp , P. S. Koutsourelakis

Constructing atom-resolved states from low-resolution data is of practical importance in many areas of science and engineering. This problem is addressed in this paper in the context of multiscale factorization methods for molecular…

Computational Physics · Physics 2016-04-14 Andrew Abi Mansour , Peter J. Ortoleva

Coarse-grained (CG) models facilitate an efficient exploration of complex systems by reducing the unnecessary degrees of freedom of the fine-grained (FG) system while recapitulating major structural correlations. Unlike structural…

Chemical Physics · Physics 2023-01-18 Jaehyeok Jin , Kenneth S. Schweizer , Gregory A. Voth

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

The emergence of macroscopic variables can be effected through {\it coarse graining}. Despite practical and fundamental benefits conveyed by this partitioning of state space, the apparently subjective nature of the selection of coarse…

Statistical Mechanics · Physics 2016-08-31 L. S. Schulman , B. Gaveau

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

We present general results on fluctuations and spatial correlations of the coarse-grained empirical density and current of Markovian diffusion in equilibrium or non-equilibrium steady states on all time scales. We unravel a deep connection…

Statistical Mechanics · Physics 2023-04-06 Cai Dieball , Aljaž Godec

We investigate two different types of non-Markovian coarse-grained models extracted from a linear, non-equilibrium microscopic system, featuring a tagged particle coupled to underdamped oscillators. The first model is obtained by…

Statistical Mechanics · Physics 2023-10-06 Gerhard Jung
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