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Several recently proposed semi--automatic and fully--automatic coarse--graining schemes for polymer simulations are discussed. All these techniques derive effective potentials for multi--atom units or super--atoms from atomistic…

Soft Condensed Matter · Physics 2007-05-23 Roland Faller

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

In this paper we investigate the approximation properties of the coarse-graining procedure applied to kinetic Monte Carlo simulations of lattice stochastic dynamics. We provide both analytical and numerical evidence that the hierarchy of…

Numerical Analysis · Mathematics 2007-05-23 Markos A Katsoulakis , Petr Plechac , Alexandros Sopasakis

Stochastic modelling of complex systems plays an essential, yet often computationally intensive role across the quantitative sciences. Recent advances in quantum information processing have elucidated the potential for quantum simulators to…

Quantum Physics · Physics 2021-06-22 Thomas J. Elliott

In recent years, it has become increasingly popular to construct coarse-grained models with non-Markovian dynamics to account for an incomplete separation of time scales. One challenge of a systematic coarse-graining procedure is the…

Soft Condensed Matter · Physics 2017-09-25 Gerhard Jung , Martin Hanke , Friederike Schmid

In this paper we focus on the development of new methods suitable for efficient and reliable coarse-graining of {\it non-equilibrium} molecular systems. In this context, we propose error estimation and controlled-fidelity model reduction…

Computational Physics · Physics 2015-06-15 Markos A. Katsoulakis , Petr Plechac

Mathematical approaches from dynamical systems theory are used in a range of fields. This includes biology where they are used to describe processes such as protein-protein interaction and gene regulatory networks. As such networks increase…

Numerical Analysis · Mathematics 2020-11-05 Edgar Herrera-Delgado , James Briscoe , Peter Sollich

Efficient sampling of the Boltzmann distribution of molecular systems is a long-standing challenge. Recently, instead of generating long molecular dynamics simulations, generative machine learning methods such as normalizing flows have been…

Machine Learning · Computer Science 2024-08-06 Henrik Schopmans , Pascal Friederich

Atomistic simulations with methods such as molecular dynamics are extremely powerful tools to understand nanoscale dynamical behavior. The resulting trajectories, by the virtue of being embedded in a high-dimensional configuration space,…

Statistical Mechanics · Physics 2020-08-27 Animesh Agarwal , Sandrasegaram Gnanakaran , Nicholas Hengartner , Arthur F. Voter , Danny Perez

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 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

Significant efforts have been devoted in the last decade towards improving the predictivity of coarse-grained models in molecular dynamics simulations and providing a rigorous justification of their use, through a combination of theoretical…

Chemical Physics · Physics 2019-01-16 Nicodemo Di Pasquale , Thomas Hudson , Matteo Icardi

We present a first-principles derivation of the Markovian semi-group master equation without invoking the rotating wave approximation (RWA). Instead we use a time coarse-graining approach which leaves us with a free timescale parameter,…

Quantum Physics · Physics 2013-07-09 Christian Majenz , Tameem Albash , Heinz-Peter Breuer , Daniel A. Lidar

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

The dynamics of real magnets is often governed by several interacting processes taking place simultaneously at different length scales. For dynamical simulations the relevant length scales should be coupled, and the energy transfer…

Materials Science · Physics 2007-05-23 V. V. Dobrovitski , M. I. Katsnelson , B. N. Harmon

A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships that govern essential biological processes. Here, we approach…

Algebraic multigrid (AMG) methods derive their optimal efficiency from the interplay between a relaxation process and a corresponding coarse grid correction. In many standard formulations, relaxation and coarse-graining are analyzed and…

Numerical Analysis · Mathematics 2026-03-30 Rayan Moussa , Karsten Kahl

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

Coarse-graining offers a means to extend the achievable time and length scales of molecular dynamics simulations beyond what is practically possible in the atomistic regime. Sampling molecular configurations of interest can be done…

Computational Physics · Physics 2022-11-30 Kirill Shmilovich , Marc Stieffenhofer , Nicholas E. Charron , Moritz Hoffmann

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