English
Related papers

Related papers: Coarse-graining two-dimensional turbulence via dyn…

200 papers

We formulate a coarse-graining approach to the dynamics of magnetohydrodynamic (MHD) fluids at a continuum of length-scales. In this methodology, effective equations are derived for the observable velocity and magnetic fields…

Solar and Stellar Astrophysics · Physics 2017-04-05 Hussein Aluie

Molecular dynamics simulations provide theoretical insight into the microscopic behavior of materials in condensed phase and, as a predictive tool, enable computational design of new compounds. However, because of the large temporal and…

Chemical Physics · Physics 2020-06-18 Wujie Wang , Rafael Gómez-Bombarelli

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

This work presents a rigorous framework based on coarse-graining to analyze highly compressible turbulence. We show how the requirement that viscous effects on the dynamics of large-scale momentum and kinetic energy be negligible ---an…

Fluid Dynamics · Physics 2012-12-27 Hussein Aluie

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 review some recent coarse-graining and multi-scale methods, but also put forward some new ideas for addressing such issues. We find that, if one is guided by nonequilibrium statistical mechanics and thermodynamics, it is possible to…

Soft Condensed Matter · Physics 2009-11-06 Patrick Ilg , Vlasis Mavrantzas , Hans Christian Öttinger

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

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

The large deviation principle is proved for a class of $L^2$-valued processes that arise from the coarse-graining of a random field. Coarse-grained processes of this kind form the basis of the analysis of local mean-field models in…

Mathematical Physics · Physics 2007-05-23 R. S. Ellis , K. Haven , B. Turkington

Understanding the emergence of macroscopic irreversible hydrodynamics from the reversible unitary dynamics of isolated quantum many-body systems remains a fundamental challenge. Conventional approaches often force spin density dynamics into…

Quantum Physics · Physics 2026-05-08 Seiki Saito

In this paper we explore a possibility that all transport turbulent models are contained in a coarse-grained kinetic equation. Building on a recent work by H.Chen et al (2004), we account for fluctuations of a single -point probability…

Cellular Automata and Lattice Gases · Physics 2007-07-05 Victor Yakhot

Coarse-graining techniques play a central role in reducing the complexity of stochastic models, and are typically characterised by a mapping which projects the full state of the system onto a smaller set of variables which captures the…

Probability · Mathematics 2023-09-28 Bastian Hilder , Upanshu Sharma

We present a method to derive macroscopic fluid-dynamic models from microscopic car-following models via a coarse-graining procedure. The method is first demonstrated for the optimal velocity model. The derived macroscopic model consists of…

Statistical Mechanics · Physics 2009-11-07 H. K. Lee , H. -W. Lee , D. Kim

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

Nonequilibrium statistical models of point vortex systems are constructed using an optimal closure method, and these models are employed to approximate the relaxation toward equilibrium of systems governed by the two-dimensional Euler…

Fluid Dynamics · Physics 2018-12-26 Jonathan Maack , Bruce Turkington

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

We demonstrate how the dynamical coarse-graining approach can be systematically extended to higher orders in the coupling between system and reservoir. Up to second order in the coupling constant we explicitly show that dynamical…

Quantum Physics · Physics 2009-03-23 Gernot Schaller , Philipp Zedler , Tobias Brandes

In this paper, we examine how to build coarse-grain transport models consistently from the kinetic to fluid regimes. The internal energy of the gas particles is described through a state-to-state approach. A kinetic equation allows us to…

Fluid Dynamics · Physics 2021-03-15 Erik Torres , Georgios Bellas-Chatzigeorgis , Thierry E. Magin

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

Many biological systems can be described by finite Markov models. A general method for simplifying master equations is presented that is based on merging adjacent states. The approach preserves the steady-state probability distribution and…

Biological Physics · Physics 2021-03-01 David Seiferth , Peter Sollich , Stefan Klumpp
‹ Prev 1 2 3 10 Next ›