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State-space smoothing has found many applications in science and engineering. Under linear and Gaussian assumptions, smoothed estimates can be obtained using efficient recursions, for example Rauch-Tung-Striebel and Mayne-Fraser algorithms.…

Optimization and Control · Mathematics 2016-09-27 A. Y. Aravkin , J. V. Burke , L. Ljung , A. Lozano , G. Pillonetto

Molecular dynamics (MD) simulation is a widely used technique to simulate molecular systems, most commonly at the all-atom resolution where equations of motion are integrated with timesteps on the order of femtoseconds…

We propose a novel computational strategy to study the glass transition of molecular fluids. Our approach combines the construction of simple yet realistic models with the development of Monte Carlo algorithms to accelerate equilibration…

Statistical Mechanics · Physics 2026-03-31 Romain Simon , Jean-Louis Barrat , Ludovic Berthier

We present simulations of causal dynamical collapse models of field theories on a 1+1 null lattice. We use our simulations to compare and contrast two possible interpretations of the models, one in which the field values are real and the…

Quantum Physics · Physics 2009-11-10 Fay Dowker , Isabelle Herbauts

We study coarse-graining methods for stochastic differential equations. In particular we consider averaging and a type of projection operator method, sometimes referred to as effective dynamic via conditional expectations. The projection…

Probability · Mathematics 2025-06-19 Manh Hong Duong , Carsten Hartmann , Michela Ottobre

Coarse-grained (CG) molecular dynamics enables simulations of atomic systems such as biomolecules at timescales inaccessible to all-atom (AA) methods, but existing CG neural potentials trained via force matching capture only the gradient of…

Machine Learning · Computer Science 2026-05-14 Sanya Murdeshwar , Sanjit Shashi , Kevin Bachelor , William Noid , Ashwin Lokapally , Razvan Marinescu

We use computer simulations to test a simple idea for mapping between long-time self diffusivities obtained from molecular and Brownian dynamics. The strategy we explore is motivated by the behavior of fluids comprising particles that…

Soft Condensed Matter · Physics 2011-10-25 Mark J. Pond , Jeffrey R. Errington , Thomas M. Truskett

We present general results on fluctuations and spatial correlations of the coarse-grained empirical density and current of Markovian diffusion in equilibrium or non-equilibrium steady states on all time scales. We unravel a deep connection…

Statistical Mechanics · Physics 2023-04-06 Cai Dieball , Aljaž Godec

Molecular dynamics algorithms are subject to some amount of error dependent on the size of the time step that is used. This error can be corrected by periodically updating the system with a Metropolis criteria, where the integration step is…

Computational Physics · Physics 2015-06-11 Jason A. Wagoner , Vijay S. Pande

We derive a coarse-grained description of the dynamics of a nanoparticle immersed in an isothermal simple fluid by performing a systematic coarse graining of the underlying microscopic dynamics. As coarse-grained or relevant variables we…

Mesoscale and Nanoscale Physics · Physics 2016-01-20 Pep Español , Aleksandar Donev

A simple stochastic model of solute drag by moving grain boundaries (GBs) is presented. Using a small number of parameters, the model describes solute interactions with GBs and captures nonlinear GB dynamics, solute saturation in the…

Materials Science · Physics 2023-07-03 Y. Mishin

In typical single-molecule force spectroscopy experiments the mechanical unfolding of molecular complexes or biomolecules is studied applying a force ramp to one end of the system while the other end is kept fixed in space. The…

Soft Condensed Matter · Physics 2026-05-18 Marco Oestereich , Jürgen Gauss , Gregor Diezemann

Normalizing flows are a promising tool for modeling probability distributions in physical systems. While state-of-the-art flows accurately approximate distributions and energies, applications in physics additionally require smooth energies…

Machine Learning · Statistics 2021-12-01 Jonas Köhler , Andreas Krämer , Frank Noé

We show that the coarse-grained dynamics model with the time-dependent and fluctuating potential (transient potential) can be derived from the microscopic Hamiltonian dynamics. The concept of the transient potential was first introduced…

Soft Condensed Matter · Physics 2022-04-18 Takashi Uneyama

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

We explore a computational approach to coarse graining the evolution of the large-scale features of a randomly forced Burgers equation in one spatial dimension. The long term evolution of the solution energy spectrum appears self-similar in…

Computational Physics · Physics 2009-11-13 S. Ahuja , V. Yakhot , I. G. Kevrekidis

We apply the functional Renormalisation Group (fRG) to study relaxation in a stochastic process governed by an overdamped Langevin equation with one degree of freedom, exploiting the connection with supersymmetric quantum mechanics in…

Statistical Mechanics · Physics 2023-06-06 Ashley Wilkins , Gerasimos Rigopoulos , Enrico Masoero

We present a detailed derivation and testing of our approach to rescale the dynamics of mesoscale simulations of coarse-grained polymer melts (I. Y. Lyubimov et al. J. Chem. Phys. \textbf{132}, 11876, 2010). Starting from the…

Soft Condensed Matter · Physics 2015-05-27 I. Y. Lyubimov , M. G. Guenza

Molecular dynamics simulations are typically constrained to have a fixed number of particles, which limits our capability to simulate chemical and physical processes where the composition of the system changes during the simulation time.…

Chemical Physics · Physics 2025-08-06 Blake I. Armstrong , Aaron D. Copeland , Davide Donadio , Paolo Raiteri

We derive a microscopic theory for the structural dynamics in the vicinity of the glass transition for a liquid exposed to a one-dimensional periodic potential. The periodic potential breaks translational invariance, in particular, the…

Soft Condensed Matter · Physics 2025-09-10 Abolfazl Ahmadirahmat , Michele Caraglio , Vincent Krakoviack , Thomas Franosch