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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…

In this paper we present a variational technique that handles coarse-graining and passing to a limit in a unified manner. The technique is based on a duality structure, which is present in many gradient flows and other variational…

Analysis of PDEs · Mathematics 2017-03-06 Manh Hong Duong , Agnes Lamacz , Mark A. Peletier , Upanshu Sharma

Granular systems are not always homogeneous and can be composed of grains with very different mechanical properties. To improve our understanding of the behavior of real granular systems, in this experimental study, we compress 2D…

Soft Condensed Matter · Physics 2021-07-14 Jonathan Barés , Manuel Cárdenas-Barrantes , David Cantor , Émilien Azéma , Mathieu Renouf

Coarse-graining or model reduction is a term describing a range of approaches used to extend the time-scale of molecular simulations by reducing the number of degrees of freedom. In the context of molecular simulation, standard…

Dynamical Systems · Mathematics 2023-11-14 Thomas Hudson , Xingjie Helen Li

A coarse-grained water model is developed using multistate iterative Boltzmann inversion. Following previous work, the k-means algorithm is used to dynamically map multiple water molecules to a single coarse-grained bead, allowing the use…

Chemical Physics · Physics 2015-09-29 Timothy C. Moore , Christopher R. Iacovella , Clare McCabe

We develop a computational method based on Dissipative Particle Dynamics (DPD) that introduces solvent hydrodynamic interactions to coarse-grained models of solutes, such as ions, molecules, or polymers. DPD-solvent (DPDS) is a fully…

Soft Condensed Matter · Physics 2024-05-24 Tine Curk

We propose a data-driven, coarse-graining formulation in the context of equilibrium statistical mechanics. In contrast to existing techniques which are based on a fine-to-coarse map, we adopt the opposite strategy by prescribing a…

Machine Learning · Statistics 2017-02-01 Markus Schöberl , Nicholas Zabaras , Phaedon-Stelios Koutsourelakis

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

In recent papers, we have argued that kinetically constrained coarse grained models can be applied to understand dynamic properties of glass forming materials, and we have used this approach in various applications that appear to validate…

Statistical Mechanics · Physics 2009-11-11 David Chandler , Juan P. Garrahan

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

We conduct molecular dynamics simulations of a bidisperse Kob-Andersen (KA) glass former, modified to add in additional polydispersity. The original KA system is known to exhibit dynamical heterogeneity. Prior work defined propensity, the…

Soft Condensed Matter · Physics 2021-05-11 Cordell J. Donofrio , Eric R. Weeks

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

Coarse graining (CG) is an important task for efficient modeling and simulation of complex multi-scale systems, such as the conformational dynamics of biomolecules. This work presents a projection-based coarse-graining formalism for general…

Computational Physics · Physics 2026-05-28 Vahid Nateghi , Lara Neureither , Selma Moqvist , Carsten Hartmann , Simon Olsson , Feliks Nüske

Coarse-graining is central to reducing dimensionality in molecular dynamics, and is typically characterized by a mapping which projects the full state of the system to a smaller class of variables. While extensive literature has been…

Probability · Mathematics 2020-01-08 Frédéric Legoll , Tony Lelièvre , Upanshu Sharma

We critically discuss and review the general ideas behind single- and multi-site coarse-grained (CG) models as applied to macromolecular solutions in the dilute and semi-dilute regime. We first consider single-site models with zero-density…

Soft Condensed Matter · Physics 2015-10-28 Giuseppe D'Adamo , Roberto Menichetti , Andrea Pelissetto , Carlo Pierleoni

We introduce Coarse-Grained Nonlinear Dynamics, an efficient and universal parameterization of nonlinear system dynamics based on the Volterra series expansion. These models require a number of parameters only quasilinear in the system's…

Signal Processing · Electrical Eng. & Systems 2020-10-15 Span Spanbauer , Ian Hunter

We present a coarse-graining method applicable to dry scalar active matter with motility regulation. Our approach, based on a multiscale perturbative expansion of the backward Kolmogorov equation, does not rely on any specific microscopic…

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

The prediction of the equation of state and the phase behavior of simple fluids (noble gases, carbon dioxide, benzene, methane, short alkane chains) and their mixtures by Monte Carlo computer simulation and analytic approximations based on…

Statistical Mechanics · Physics 2009-11-13 B. M. Mognetti , P. Virnau , L. Yelash , W. Paul , K. Binder , M. Mueller , L. G. MacDowell

In this paper, a statistical physical derivation of thermodynamically consistent fluid mechanical equations is presented for non-isothermal viscous molecular fluids. The coarse-graining process is based on (i) the adiabatic expansion of the…

Statistical Mechanics · Physics 2024-04-18 Gyula I. Tóth

We present several numerical results on granular mixtures. In particular, we examine the efficiency of diffusion as a mixing mechanism in these systems. The collisions are inelastic and to compensate the energy loss, we thermalize the…

Statistical Mechanics · Physics 2009-10-31 C. Henrique , G. Batrouni , D. Bideau