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Simulations of condensed matter systems often focus on the dynamics of a few distinguished components but require integrating the dynamics of the full system. A prime example is a molecular dynamics simulation of a (macro)molecule in…

Computational Physics · Physics 2024-03-12 Mauricio J. del Razo , Daan Crommelin , Peter G. Bolhuis

Dissipative particle dynamics (DPD) is now a well-established method for simulating soft matter systems. However, its applicability was recently questioned because some investigations showed an upper coarse-graining limit that would prevent…

Soft Condensed Matter · Physics 2011-11-09 Rudolf M. Füchslin , Harold Fellermann , Anders Eriksson , Hans-Joachim Ziock

We discuss the methods to calculate the roughness exponent alpha and the dynamic exponent z from the scaling properties of the local roughness, which is frequently used in the analysis of experimental data. Through numerical simulations, we…

Statistical Mechanics · Physics 2009-11-10 Anna Chame , F. D. A. Aarão Reis

We extend our 2+1 dimensional discrete growth model (PRE 79, 021125 (2009)) with conserved, local exchange dynamics of octahedra, describing surface diffusion. A roughening process was realized by uphill diffusion and curvature dependence.…

Statistical Mechanics · Physics 2010-05-14 Geza Odor , Bartosz Liedke , Karl-Heinz Heinig

Identification of nonlinear dynamical systems is crucial across various fields, facilitating tasks such as control, prediction, optimization, and fault detection. Many applications require methods capable of handling complex systems while…

Machine Learning · Statistics 2024-11-05 Luc Brogat-Motte , Riccardo Bonalli , Alessandro Rudi

We introduce Coarse-Grained Nonlinear Dynamics, an efficient and universal parameterization of nonlinear system dynamics based on the Volterra series expansion. These models require a number of parameters only quasilinear in the system's…

Signal Processing · Electrical Eng. & Systems 2020-10-15 Span Spanbauer , Ian Hunter

We introduce an RG-inspired coarse-graining for extracting the collective features of data. The key to successful coarse-graining lies in finding appropriate pairs of data sets. We coarse-grain the two closest data in a regular real-space…

Data Analysis, Statistics and Probability · Physics 2023-07-19 Jonathan Landy , Tsvi Tlusty , YeongKyu Lee , YongSeok Jho

We perform a systematic study of several models that have been proposed for the purpose of understanding the motion of driven interfaces in disordered media. We identify two distinct universality classes: (i) One of these, referred to as…

Condensed Matter · Physics 2009-10-28 L. A. N. Amaral , A. -L. Barabasi , H. A. Makse , H. E. Stanley

Wave-like dark matter described by a high-occupancy self-gravitating bosonic field provides a microscopic setting in which both amplitude and phase are dynamical. We study a one-dimensional Gross--Pitaevskii--Poisson toy model and ask which…

Statistical Mechanics · Physics 2026-03-31 Rin Takada

We present several approaches for deriving the coarse-grained continuous Langevin equation (or Edwards-Wilkinson equation) from a random deposition with surface relaxation (RDSR) model. First we introduce a novel procedure to divide the…

Statistical Mechanics · Physics 2014-12-24 R. C. Buceta , D. Hansmann , B. von Haeften

The aim of this paper is to obtain convergence in mean in the uniform topology of piecewise linear approximations of Stochastic Differential Equations (SDEs) with $C^1$ drift and $C^2$ diffusion coefficients with uniformly bounded…

Probability · Mathematics 2025-03-13 Sahani Pathiraja

We present an algebraic method for constructing a highly effective coarse grid correction to accelerate domain decomposition. The coarse problem is constructed from the original matrix and a small set of input vectors that span a low-degree…

Numerical Analysis · Computer Science 2015-04-06 Essex Edwards , Robert Bridson

We carried out a finite-size scaling analysis of the restricted solid-on-solid version of a recently introduced growth model that exhibits a roughening transition accompanied by spontaneous symmetry breaking. The dynamic critical exponent…

Statistical Mechanics · Physics 2009-10-31 J. Ricardo G. de Mendonca

We propose a data-driven, coarse-graining formulation in the context of equilibrium statistical mechanics. In contrast to existing techniques which are based on a fine-to-coarse map, we adopt the opposite strategy by prescribing a…

Machine Learning · Statistics 2017-02-01 Markus Schöberl , Nicholas Zabaras , Phaedon-Stelios Koutsourelakis

We explore linear control of the one-dimensional non-linear Kardar--Parisi--Zhang (KPZ) equation with the goal to understand the effects the control process has on the dynamics and on the stationary state of the resulting stochastic growth…

Statistical Mechanics · Physics 2021-05-11 Priyanka , Uwe C Tauber , Michel Pleimling

This Letter reports on how the interfaces in the (1+1)-dimensional Kardar-Parisi-Zhang (KPZ) class undergo, in the course of time, a transition from the flat, growing regime to the stationary one. Simulations of the polynuclear growth model…

Statistical Mechanics · Physics 2013-06-03 Kazumasa A. Takeuchi

The dynamics of critical slope self-organized critical models is studied, using a previous mapping into a linear interface depinning model dragged at one end. The model is solved obtaining the complete set of scaling exponents. Some results…

Condensed Matter · Physics 2007-05-23 Alexei Vazquez , Oscar Sotolongo-Costa

We present an ``equation-free'' multiscale approach to the simulation of unsteady diffusion in a random medium. The diffusivity of the medium is modeled as a random field with short correlation length, and the governing equations are cast…

Numerical Analysis · Mathematics 2007-05-23 Dongbin Xiu , Ioannis Kevrekidis

Probabilistic integration of a continuous dynamical system is a way of systematically introducing model error, at scales no larger than errors introduced by standard numerical discretisation, in order to enable thorough exploration of…

Numerical Analysis · Mathematics 2019-10-29 H. C. Lie , A. M. Stuart , T. J. Sullivan

We propose a flexible Bayesian approach for estimating the joint density of a multivariate outcome of interest in the presence of categorical covariates. Leveraging a Gaussian copula framework, our method effectively captures the dependence…

Methodology · Statistics 2026-04-10 Giovanni Toto , Peter Müller , Abhra Sarkar