English
Related papers

Related papers: Bottom-up transient time models in coarse-graining…

200 papers

Coarse-grained (CG) force field methods for molecular systems are a crucial tool to simulate large biological macromolecules and are therefore essential for characterisations of biomolecular systems. While state-of-the-art deep learning…

Coarse-graining complex molecular systems to lower-dimensional reaction coordinates is a powerful approach for capturing their effective dynamics. The generalized Langevin equation (GLE) provides an exact framework for modeling…

Chemical Physics · Physics 2025-06-09 Henrik Kiefer , Cihan Ayaz , Benjamin A. Dalton , Roland R. Netz

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

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

We describe a systematic approach to construct coarse-grained Markov state models from molecular dynamics data of systems driven into a non-equilibrium steady state. We apply this method to study the globule-stretch transition of a single…

Soft Condensed Matter · Physics 2017-02-28 Fabian Knoch , Thomas Speck

Many recent advancements in quantum computing leverage strong drives on nonlinear systems for state preparation, signal amplification, or gate operation. However, the interplay within such strongly driven system introduces multi-scale…

Quantum Physics · Physics 2024-08-02 Leon Bello , Wentao Fan , Aditya Gandotra , Hakan E. Türeci

Active matter, responsive ("smart") materials and materials under time-dependent load are systems out of thermal equilibrium. To construct coarse-grained models for such systems, one needs to integrate out a distribution of microstates that…

Statistical Mechanics · Physics 2022-05-17 Tanja Schilling

We explore a systematic approach to studying the dynamics of evolving networks at a coarse-grained, system level. We emphasize the importance of finding good observables (network properties) in terms of which coarse grained models can be…

A systematic procedure for optimising the friction coefficient in underdamped Langevin dynamics as a sampling tool is given by taking the gradient of the associated asymptotic variance with respect to friction. We give an expression for…

Computation · Statistics 2023-11-01 Martin Chak , Nikolas Kantas , Tony Lelièvre , Grigorios A. Pavliotis

We present a new method of conducting molecular dynamics simulation in isothermal-isobaric ensemble based on Langevin equations of motion. The stochastic coupling to all particle and cell degrees of freedoms is introduced in a correct way,…

Statistical Mechanics · Physics 2016-04-28 Xingyu Gao , Jun Fang , Han Wang

Learning accurate dynamics models is necessary for optimal, compliant control of robotic systems. Current approaches to white-box modeling using analytic parameterizations, or black-box modeling using neural networks, can suffer from high…

Robotics · Computer Science 2019-03-05 Jayesh K. Gupta , Kunal Menda , Zachary Manchester , Mykel J. Kochenderfer

The deformability of soft condensed matter often requires modelling of hydrodynamical aspects to gain quantitative understanding. This, however, requires specialised methods that can resolve the multiscale nature of soft matter systems. We…

Soft Condensed Matter · Physics 2017-12-22 Ulf D. Schiller , Timm Krüger , Oliver Henrich

A novel scheme to simulate the evolution of a restricted set of observables of a quantum system is proposed. The set comprises the spectrum-generating algebra of the Hamiltonian. The idea is to consider a certain open-system evolution,…

Quantum Physics · Physics 2009-11-13 M. Khasin , R. Kosloff

Stochastic Langevin dynamics has been traditionally used as a tool to describe non-equilibrium processes. When utilized in systems with collective modes, traditional Langevin dynamics relaxes all modes indiscriminately, regardless of their…

Statistical Mechanics · Physics 2018-06-06 A. Tamm , M. Caro , A. Caro , G. Samolyuk , M. Klintenberg , A. A. Correa

Spatial multiscale methods have established themselves as useful tools for extending the length scales accessible by conventional statics (i.e., zero temperature molecular dynamics). Recently, extensions of these methods, such as the…

Numerical Analysis · Mathematics 2014-09-23 Andrew Binder , Mitchell Luskin , Danny Perez , Arthur F. Voter

The transient dynamics of quantum coherence of Gaussian states are investigated. The state is coupled to an external environment which can be described by a Fano-Anderson type Hamiltonian. Solving the quantum Langevin equation, we obtain…

Quantum Physics · Physics 2022-01-20 Md. Manirul Ali , Chandrashekar Radhakrishnan

We study the Langevin dynamics of diffusive particles with regular pairwise interactions under mean-field scaling. By approximating empirical distributions with conditional distributions, we establish coercive and contractive properties for…

Probability · Mathematics 2026-05-28 Songbo Wang

Advanced thermostats for molecular dynamics are proposed on the base of the rigorous Langevin dynamics. Because the latter accounts for the subsystem-bath interactions in details, the bath anisotropy and nonuniformity are described via the…

Statistical Mechanics · Physics 2023-10-03 Roumen Tsekov

In molecular dynamics simulations and single molecule experiments, observables are usually measured along dynamic trajectories and then averaged over an ensemble ("bundle") of trajectories. Under stationary conditions, the time-evolution of…

Statistical Mechanics · Physics 2018-01-17 Hugues Meyer , Thomas Voigtmann , Tanja Schilling

How can we learn the laws underlying the dynamics of stochastic systems when their trajectories are sampled sparsely in time? Existing methods either require temporally resolved high-frequency observations, or rely on geometric arguments…

Dynamical Systems · Mathematics 2025-12-30 Dimitra Maoutsa