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Related papers: Coarse-graining molecular dynamics models using an…

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In this study, a coarse-graining framework for discrete models is formulated on the basis of multiscale homogenization. The discrete model considered in this paper is the Lattice Discrete Particle Model (LDPM), which simulates concrete at…

Materials Science · Physics 2018-04-24 Erol Lale , Roozbeh Rezakhani , Mohammed Alnaggar , Gianluca Cusatis

The integral equation coarse-graining (IECG) approach is a promising high-level coarse-graining (CG) method for polymer melts, with variable resolution from soft spheres to multi CG sites, which preserves the structural and thermodynamical…

Soft Condensed Matter · Physics 2018-07-24 Mohammadhasan Dinpajooh , Marina G. Guenza

Functional connectivity estimates are highly sensitive to analysis choices and can be dominated by noise when the number of sampled time points is small relative to network dimensionality. This issue is particularly acute in fMRI, where…

Disordered Systems and Neural Networks · Physics 2026-02-10 Izaro Fernandez-Iriondo , Antonio Jimenez-Marin , Jesus Cortes , Pablo Villegas

Transient bonds between fast linkers and slower particles are widespread in physical and biological systems. In spite of their diverse structure and function, a commonality is that the linkers diffuse on timescales much faster compared to…

Soft Condensed Matter · Physics 2023-06-06 Sophie Marbach , Christopher E. Miles

We present a simple model which allows to investigate equilibrium aspects of molecular recognition between rigid biomolecules on a generic level. Using a two-stage approach, which consists of a design and a testing step, the role of…

Biological Physics · Physics 2009-11-13 Hans Behringer , Andreas Degenhard , Friederike Schmid

The recently developed generalized Fourier-Galerkin method is complemented by a numerical continuation with respect to the kinetic energy, which extends the framework to the investigation of modal interactions resulting in folds of the…

Numerical Analysis · Mathematics 2021-01-07 Malte Krack , Lars Panning-von Scheidt , Jörg Wallaschek

We investigate numerical behaviour of a convection diffusion equation with random coefficients by approximating statistical moments of the solution. Stochastic Galerkin approach, turning the original stochastic problem to a system of…

Numerical Analysis · Mathematics 2021-10-19 Pelin Çiloğlu , Hamdullah Yücel

Developing physics-based models for molecular simulation requires fitting many unknown parameters to diverse experimental datasets. Traditionally, this process is piecemeal and difficult to reproduce, leading to a fragmented landscape of…

Biological Physics · Physics 2025-04-10 Ryan K. Krueger , Megan C. Engel , Ryan Hausen , Michael P. Brenner

This paper presents a reduced order approach for transient modeling of multiple moving objects in nonlinear crossflows. The Proper Orthogonal Decomposition method and the Galerkin projection are used to construct a reduced version of the…

Fluid Dynamics · Physics 2021-06-07 My Ha Dao

The most popular and universally predictive protein simulation models employ all-atom molecular dynamics (MD), but they come at extreme computational cost. The development of a universal, computationally efficient coarse-grained (CG) model…

A major current challenge poses the systematic construction of coarse-grained models that are dynamically consistent, and, moreover, might be used for systems driven out of thermal equilibrium. Here we present a novel prescription that…

Statistical Mechanics · Physics 2016-08-05 Fabian Knoch , Thomas Speck

Training nonlinear parametrizations such as deep neural networks to numerically approximate solutions of partial differential equations is often based on minimizing a loss that includes the residual, which is analytically available in…

Numerical Analysis · Mathematics 2023-06-28 Yuxiao Wen , Eric Vanden-Eijnden , Benjamin Peherstorfer

A brief review of modeling and simulation methods for a study of polymers at interfaces is provided. When studying truly multiscale problems as provided by realistic polymer systems, coarse graining is practically unavoidable. In this…

Soft Condensed Matter · Physics 2009-10-19 Fathollah Varnik , Kurt Binder

In this paper, we develop sparse grid central discontinuous Galerkin (CDG) scheme for linear hyperbolic systems with variable coefficients in high dimensions. The scheme combines the CDG framework with the sparse grid approach, with the aim…

Numerical Analysis · Mathematics 2019-01-16 Zhanjing Tao , Anqi Chen , Mengping Zhang , Yingda Cheng

The automated construction of coarse-grained models represents a pivotal component in computer simulation of physical systems and is a key enabler in various analysis and design tasks related to uncertainty quantification. Pertinent methods…

Machine Learning · Statistics 2019-09-11 Constantin Grigo , Phaedon-Stelios Koutsourelakis

We coarse-grain a model of closely-packed ellipses that can vary their aspect ratio to derive continuum equations for materials comprising confluent deformable particles such as epithelial cell layers. We show that contractile nearest…

Soft Condensed Matter · Physics 2025-01-14 Mehrana R. Nejad , Julia M Yeomans

In this work, we develop a two-component coarse-grained molecular dynamics (CGMD) model for simulating the erythrocyte membrane. This proposed model possesses the key feature of combing the lipid bilayer and the erythrocyte cytoskeleton,…

Biological Physics · Physics 2017-07-25 He Li

Coarse-grained (CG) molecular dynamics enables the study of biological processes at temporal and spatial scales that would be intractable at an atomistic resolution. However, accurately learning a CG force field remains a challenge. In this…

We present a dynamic coarse-graining technique that allows to simulate the mechanical unfolding of biomolecules or molecular complexes on experimentally relevant time scales. It is based on Markov state models (MSM), which we construct from…

Soft Condensed Matter · Physics 2018-08-17 Fabian Knoch , Ken Schäfer , Gregor Diezemann , Thomas Speck

Bottom-up coarse-grained molecular dynamics models are parameterized using complex effective Hamiltonians. These models are typically optimized to approximate high dimensional data from atomistic simulations. In contrast, human validation…

Chemical Physics · Physics 2021-09-16 Aleksander Evren Paetzold Durumeric , Gregory A. Voth