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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

We present a computer-assisted approach to coarse-graining the evolutionary dynamics of a system of nonidentical oscillators coupled through a (fixed) network structure. The existence of a spectral gap for the coupling network graph…

Statistical Mechanics · Physics 2015-05-28 Karthikeyan Rajendran , Ioannis G. Kevrekidis

Mathematical modelling of biological population dynamics often involves proposing high fidelity discrete agent-based models that capture stochasticity and individual-level processes. These models are often considered in conjunction with an…

Dynamical Systems · Mathematics 2023-12-20 Daniel J. VandenHeuvel , Pascal R. Buenzli , Matthew J. Simpson

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

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

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

A dynamical atomistic chain to simulate mechanical properties of a one-dimensional material with zero temperature may be modelled by the molecular dynamics (MD) model. Because the number of particles (atoms) is huge for a MD model, in…

Numerical Analysis · Mathematics 2019-02-22 Mingjie Liao , Ping Lin

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

The large time and length scales and, not least, the vast number of particles involved in industrial-scale simulations inflate the computational costs of the Discrete Element Method (DEM) excessively. Coarse grain models can help to lower…

Computational Physics · Physics 2017-05-11 Daniel Queteschiner , Thomas Lichtenegger , Simon Schneiderbauer , Stefan Pirker

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

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

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

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

An algorithm for simulation of quantum many-body dynamics having su(2) spectrum-generating algebra is developed. The algorithm is based on the idea of dynamical coarse-graining. The original unitary dynamics of the target observables, the…

Quantum Physics · Physics 2009-12-03 M. Khasin , R. Kosloff

We show how the Equation-Free approach for mutliscale computations can be exploited to extract, in a computational strict and systematic way the emergent dynamical attributes, from detailed large-scale microscopic stochastic models, of…

Social and Information Networks · Computer Science 2013-10-02 Konstantinos G. Spiliotis , Constantinos I. Siettos

Emergent processes in complex systems such as cellular automata can perform computations of increasing complexity, and could possibly lead to artificial evolution. Such a feat would require scaling up current simulation sizes to allow for…

Cellular Automata and Lattice Gases · Physics 2021-04-05 Hugo Cisneros , Josef Sivic , Tomas Mikolov

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

Atomistic simulations of the molecular dynamics/statics kind are regularly used to study small scale plasticity. Contemporary simulations are performed with tens to hundreds of millions of atoms, with snapshots of these configurations…

Materials Science · Physics 2022-06-17 Aruna Prakash , Stefan Sandfeld

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

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