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We investigate algebraic and topological signatures of networks of coupled oscillators. Translating dynamics into a system of algebraic equations enables us to identify classes of network topologies that exhibit unexpected behaviors. Many…

Dynamical Systems · Mathematics 2025-01-07 Heather Harrington , Hal Schenck , Mike Stillman

The activity of collections of synchronizing neurons can be represented by weakly coupled nonlinear phase oscillators satisfying Kuramoto's equations. In this article, we build such neural-oscillator models, partly based on…

Neurons and Cognition · Quantitative Biology 2012-04-27 Patrick Suppes , Jose Acacio de Barros , Gary Oas

Analog Ising machines (IMs) occupy an increasingly prominent area of computer architecture research, offering high-quality and low latency/energy solutions to intractable computing tasks. However, IMs have a fixed capacity, with little to…

Emerging Technologies · Computer Science 2026-03-03 Matthew X. Burns , Michael C. Huang

Synchronization systems with effective inertia, such as power grid networks and coupled electromechanical oscillators, are commonly modeled by the second-order Kuramoto model. In the forward process, numerical simulations exhibit a…

Physics and Society · Physics 2026-04-01 Gug Young Kim , Mi Jin Lee , Seung-Woo Son

The growing challenges of scaling digital computing motivate new approaches, especially through the dynamical evolution of physical systems that mimic neural networks and combinatorial optimization problems. While light is a hyper efficient…

The use of combinatorial optimization algorithms has contributed substantially to the major progress that has occurred in recent years in the understanding of the physics of disordered systems, such as the random-field Ising model. While…

Disordered Systems and Neural Networks · Physics 2023-02-22 Manoj Kumar , Martin Weigel

Recurrent neural networks (RNNs) are machine learning models widely used for learning temporal relationships. Current state-of-the-art RNNs use integrating or spiking neurons -- two classes of computing units whose outputs depend directly…

Neural and Evolutionary Computing · Computer Science 2025-06-10 Peter DelMastro , Arjun Karuvally , Hananel Hazan , Hava Siegelmann , Edward Rietman

The Kuramoto model is a classical mathematical model in the field of non-linear dynamical systems that describes the evolution of coupled oscillators in a network that may reach a synchronous state. The relationship between the network's…

Probability · Mathematics 2024-02-16 Pedro Abdalla , Afonso S. Bandeira , Clara Invernizzi

We propose the idea of using Kuramoto models (including their higher-dimensional generalizations) for machine learning over non-Euclidean data sets. These models are systems of matrix ODE's describing collective motions (swarming dynamics)…

Machine Learning · Computer Science 2024-05-16 Vladimir Jacimovic

This paper deals with an optimal control problem associated to the Kuramoto model describing the dynamical behavior of a network of coupled oscillators. Our aim is to design a suitable control function allowing us to steer the system to a…

Adaptation and Self-Organizing Systems · Physics 2020-05-15 Umberto Biccari , Enrique Zuazua

The Kuramoto model describes synchronization behavior among coupled oscillators and enjoys successful application in a wide variety of fields. Many of these applications seek phase-coherent solutions, i.e., equilibria of the model.…

Optimization and Control · Mathematics 2017-10-30 Owen Coss , Jonathan D. Hauenstein , Hoon Hong , Daniel K. Molzahn

The vision of building computational hardware for problem optimization has spurred large efforts in the physics community. In particular, networks of Kerr parametric oscillators (KPOs) are envisioned as simulators for finding the ground…

A new technique is demonstrated for carrying out exact positive-P phase-space simulations of the coherent Ising machine quantum computer. By suitable design of the coupling matrix, general hard optimization problems can be solved. Here,…

Quantum Physics · Physics 2022-02-09 Simon Kiesewetter , Peter D Drummond

We investigate the computational power of the recently introduced class of isometric tensor network states (isoTNSs), which generalizes the isometric conditions of the canonical form of one-dimensional matrix-product states to tensor…

Strongly Correlated Electrons · Physics 2022-12-14 Sheng-Hsuan Lin , Michael Zaletel , Frank Pollmann

The coherent Ising machine (CIM) is a quantum-inspired computing platform that leverages optical parametric oscillation dynamics to solve combinatorial optimization problems by searching for the ground state of an Ising Hamiltonian.…

Quantum Physics · Physics 2025-09-18 Yan Chen Jiang , Lu Ma , Chuan Wang , Tie Jun Wang

The Kuramoto model has provided deep insights into synchronization phenomena and remains an important paradigm to study the dynamics of coupled oscillators. Yet, despite its success, the asynchronous regime in the Kuramoto model has…

Mathematical Physics · Physics 2024-03-26 Yagmur Kati , Jonas Ranft , Benjamin Lindner

Synchronization in the networks of coupled oscillators is a widely studied topic in different areas. It is well-known that synchronization occurs if the connectivity of the network dominates heterogeneity of the oscillators. Despite…

Optimization and Control · Mathematics 2018-09-20 Elizabeth Y. Huang , Saber Jafarpour , Francesco Bullo

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

Motivated by near term quantum computing hardware limitations, combinatorial optimization problems that can be addressed by current quantum algorithms and noisy hardware with little or no overhead are used to probe capabilities of quantum…

Optimization and Control · Mathematics 2026-05-15 Elijah Pelofske , Andreas Bärtschi , Stephan Eidenbenz

In this study, we present a novel analytical approach to solving large-scale Ising problems by reformulating the discrete Ising Hamiltonian into a continuous framework. This transformation enables us to derive exact solutions for a…

Computational Physics · Physics 2025-08-04 Amirhossein Rezaei , Mahmood Hasani , Alireza Rezaei , S. M. Hassan Halataei