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Non-spherical particles transported by an anisotropic turbulent flow preferentially align with the mean shear and intermittently tumble when the local strain fluctuates. Such an intricate behaviour is here studied for inertialess,…

Soft Condensed Matter · Physics 2022-12-27 Lorenzo Campana , Mireille Bossy , Jeremie Bec

To investigate the impact of non-linear interactions on dynamic coarse graining, we study a simplified model system, featuring a tracer particle in a complex environment. Using a projection operator formalism and computer simulations, we…

Soft Condensed Matter · Physics 2023-07-18 Bernd Jung , Gerhard Jung

We describe in detail how to implement a coarse-grained hybrid Molecular Dynamics and Stochastic Rotation Dynamics simulation technique that captures the combined effects of Brownian and hydrodynamic forces in colloidal suspensions. The…

Soft Condensed Matter · Physics 2007-05-23 J. T. Padding , A. A. Louis

A wide variety of different (fixed-point) iterative methods for the solution of nonlinear equations exists. In this work we will revisit a unified iteration scheme in Hilbert spaces from our previous work that covers some prominent…

Numerical Analysis · Mathematics 2019-05-17 Pascal Heid , Thomas P. Wihler

In statistical physics, the Nakajima-Mori-Zwanzig projection operator formalism is used to derive an integro-differential equation for observables in a Hilbert space, the generalized Langevin equation (GLE). This technique relies on the…

Mathematical Physics · Physics 2026-04-27 Christoph Widder , Johannes Zimmer , Tanja Schilling

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

Constrained quantum dynamics is used to propose a nonlinear dynamical equation for pure states of a generalized coarse-grained system. The relevant constraint is given either by the generalized purity or by the generalized invariant…

Quantum Physics · Physics 2015-05-19 Nikola Buric

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems…

Machine Learning · Computer Science 2025-12-30 Quercus Hernandez , Max Win , Thomas C. O'Connor , Paulo E. Arratia , Nathaniel Trask

Generalized estimating equation (GEE) is widely adopted for regression modeling for longitudinal data, taking account of potential correlations within the same subjects. Although the standard GEE assumes common regression coefficients among…

Methodology · Statistics 2022-07-11 Tsubasa Ito , Shonosuke Sugasawa

For a given thermodynamic system, and a given choice of coarse-grained state variables, the knowledge of a force-flux constitutive law is the basis for any nonequilibrium modeling. In the first paper of this series we established how, by a…

Statistical Mechanics · Physics 2021-02-03 Alberto Montefusco , Mark A. Peletier , Hans Christian Öttinger

By applying a hybrid Molecular dynamics and mesoscopic simulation technique, we study the classic convection-diffusion problem of Taylor dispersion for colloidal discs in confined flow. We carefully consider the time and length-scales of…

Soft Condensed Matter · Physics 2009-03-23 Jimaan Sané , Ard A. Louis , Johan Padding

We systematically derive an exact coarse-grained description for interacting particles with thermodynamically consistent stochastic dynamics, applicable across different observation scales, the mesoscopic and the macroscopic. We implement…

Statistical Mechanics · Physics 2026-03-05 Atul Tanaji Mohite , Heiko Rieger

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

It is commonly assumed that the ability to track the frequencies of a set of schemata in the evolving population of an infinite population genetic algorithm (IPGA) under different fitness functions will advance efforts to obtain a theory of…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Keki Burjorjee

In this paper, we discuss information-theoretic tools for obtaining optimized coarse-grained molecular models for both equilibrium and non-equilibrium molecular dynamics. The latter are ubiquitous in physicochemical and biological…

Numerical Analysis · Mathematics 2016-04-20 Vagelis Harmandaris , Evangelia Kalligiannaki , Markos A. Katsoulakis , Petr Plecháč

We establish, through coarse-grained computation, a connection between traditional, continuum numerical algorithms (initial value problems as well as fixed point algorithms) and atomistic simulations of the Larson model of micelle…

Soft Condensed Matter · Physics 2009-11-10 Dmitry I. Kopelevich , Athanassios Z. Panagiotopoulos , Ioannis G. Kevrekidis

Cellular regulatory dynamics is driven by large and intricate networks of interactions at the molecular scale, whose sheer size obfuscates understanding. In light of limited experimental data, many parameters of such dynamics are unknown,…

Quantitative Methods · Quantitative Biology 2014-04-30 Bryan C. Daniels , Ilya Nemenman

We study numerical methods for the generalized Langevin equation (GLE) with a positive Prony series memory kernel, in which case the GLE can be written in an extended variable Markovian formalism. We propose a new splitting method that is…

Computational Physics · Physics 2022-05-31 Manh Hong Duong , Xiaocheng Shang

We study the Langevin dynamics of a heteropolymer by means of a mode-coupling approximation scheme, giving rise to a set of coupled integro-differential equations relating the response and correlation functions. The analysis shows that…

Disordered Systems and Neural Networks · Physics 2007-05-23 Estelle Pitard , Eugene I. Shakhnovich

While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and their applicability over macroscopic time scales of physical…

Machine Learning · Statistics 2016-09-08 P. S. Koutsourelakis , Elias Bilionis
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