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Coarse graining (CG) is an important task for efficient modeling and simulation of complex multi-scale systems, such as the conformational dynamics of biomolecules. This work presents a projection-based coarse-graining formalism for general…

Computational Physics · Physics 2026-05-28 Vahid Nateghi , Lara Neureither , Selma Moqvist , Carsten Hartmann , Simon Olsson , Feliks Nüske

The Kuramoto model of coupled phase oscillators on small-world (SW) graphs is analyzed in this work. When the number of oscillators in the network goes to infinity, the model acquires a family of steady state solutions of degree q, called…

Adaptation and Self-Organizing Systems · Physics 2015-06-16 Georgi S. Medvedev

A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships that govern essential biological processes. Here, we approach…

The Kuramoto model and its generalizations have been broadly employed to characterize and mechanistically understand various collective dynamical phenomena, especially the emergence of synchrony among coupled oscillators. Despite almost…

Adaptation and Self-Organizing Systems · Physics 2025-05-16 Seungjae Lee , Lucas Braun , Frieder Bönisch , Malte Schröder , Moritz Thümler , Marc Timme

The present paper introduces a linear reformulation of the Kuramoto model describing a self-synchronizing phase transition in a system of globally coupled oscillators that in general have different characteristic frequencies. The…

Pattern Formation and Solitons · Physics 2008-03-18 David C. Roberts

Synchronization in networks of coupled oscillators is classically studied via the Kuramoto model, whose intrinsic nonlinearity limits analytical tractability and complicates control design. Complex-valued extensions circumvent this by…

Systems and Control · Electrical Eng. & Systems 2026-04-09 Lorenzo Giordano , Josep M. Olm , Mario di Bernardo

Coarse graining enables the investigation of molecular dynamics for larger systems and at longer timescales than is possible at atomic resolution. However, a coarse graining model must be formulated such that the conclusions we draw from it…

Data-driven model discovery of complex dynamical systems is typically done using sparse optimization, but it has a fundamental limitation: sparsity in that the underlying governing equations of the system contain only a small number of…

Machine Learning · Computer Science 2024-09-24 Mohammadamin Moradi , Shirin Panahi , Erik M. Bollt , Ying-Cheng Lai

The Kuramoto model has become a paradigm to describe the dynamics of nonlinear oscillator under the influence of external perturbations, both deterministic and stochastic. It is based on the idea to describe the oscillator dynamics by a…

Adaptation and Self-Organizing Systems · Physics 2019-05-09 Michele Bonnin

Kuramoto model is one of the most prominent models for the synchronization of coupled oscillators. It has long been a research hotspot to understand how natural frequencies, the interaction between oscillators, and network topology…

Adaptation and Self-Organizing Systems · Physics 2020-04-08 Shuyang Ling

The dynamics of ensembles of phase oscillators are usually described considering their infinite-size limit. In practice, however, this limit is fully accessible only if the Ott-Antonsen theory can be applied, and the heterogeneity is…

Adaptation and Self-Organizing Systems · Physics 2022-10-11 Iván León , Diego Pazó

Given (small amounts of) time-series' data from a high-dimensional, fine-grained, multiscale dynamical system, we propose a generative framework for learning an effective, lower-dimensional, coarse-grained dynamical model that is predictive…

Machine Learning · Statistics 2021-01-18 Sebastian Kaltenbach , Phaedon-Stelios Koutsourelakis

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

The equivalence between the natural minimization of energy in a dynamical system and the minimization of an objective function characterizing a combinatorial optimization problem offers a promising approach to designing dynamical…

Optimization and Control · Mathematics 2022-06-14 Antik Mallick , Mohammad Khairul Bashar , Zongli Lin , Nikhil Shukla

Common models of synchronizable oscillatory systems consist of a collection of coupled oscillators governed by a collection of differential equations. The ubiquitous Kuramoto models rely on an {\em a priori} fixed connectivity pattern…

Populations and Evolution · Quantitative Biology 2020-05-01 Elizabeth A. Tripp , Feng Fu , Scott D. Pauls

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 study the dynamics of a generalized version of the famous Kuramoto-Sakaguchi coupled oscillator model. In the classic version of this system, all oscillators are governed by the same ODE, which depends on the order parameter of the…

Adaptation and Self-Organizing Systems · Physics 2019-02-20 Bolun Chen , Jan R. Engelbrecht , Renato Mirollo

The celebrated Ott-Antonsen ansatz for coupled oscillators provides a useful framework to work with deterministic systems in the thermodynamic limit, but remains just an approximation for stochastic models. In this paper, I construct a…

Statistical Mechanics · Physics 2024-07-03 Victor Buendía

We formulate a general Kuramoto model on weighted simplicial complexes where phases oscillators are supported on simplices of any order $k$. Crucially, we introduce linear and non-linear frustration terms that are independent of the…

Mathematical Physics · Physics 2022-05-23 Alexis Arnaudon , Robert L. Peach , Giovanni Petri , Paul Expert

In this paper, we propose an equation-based parametric Reduced Order Model (ROM), whose accuracy is improved with data-driven terms added into the reduced equations. These additions have the aim of reintroducing contributions that in…

Numerical Analysis · Mathematics 2025-05-26 Anna Ivagnes , Giovanni Stabile , Gianluigi Rozza