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Full synchronization of dynamical elements coupled via hypergraphs can be analyzed with the hypergraph projection onto dyadic matrices, but this is not sufficient for analyzing cluster synchronization. Here we develop the necessary…

Adaptation and Self-Organizing Systems · Physics 2022-03-21 Anastasiya Salova , Raissa M. D'Souza

Synchronization is an important and prevalent phenomenon in natural and engineered systems. In many dynamical networks, the coupling is balanced or adjusted in order to admit global synchronization, a condition called Laplacian coupling.…

In the study of dynamical systems on networks/graphs, a key theme is how the network topology influences stability for steady states or synchronized states. Ideally, one would like to derive conditions for stability or instability that…

Dynamical Systems · Mathematics 2020-07-01 Raffaella Mulas , Christian Kuehn , Jürgen Jost

We study the synchronization properties of a generic networked dynamical system, and show that, under a suitable approximation, the transition to synchronization can be predicted with the only help of eigenvalues and eigenvectors of the…

Coupled map lattices (CMLs) are prototypical dynamical systems on networks/graphs. They exhibit complex patterns generated via the interplay of diffusive/Laplacian coupling and nonlinear reactions modelled by a single iterated map at each…

Chaotic Dynamics · Physics 2021-09-24 Tobias Böhle , Christian Kuehn , Raffaella Mulas , Jürgen Jost

Hypergraphs extend traditional networks by capturing multi-way or group interactions. Given the complexity of hypergraph data and the wide range of methodology available for pairwise network analysis, hypergraph data is often projected onto…

Social and Information Networks · Computer Science 2025-06-23 Timothy LaRock , Renaud Lambiotte

Many networked systems are governed by non-pairwise interactions between nodes. The resulting higher-order interaction structure can then be encoded by means of a hypernetwork. In this paper we consider dynamical systems on hypernetworks by…

Dynamical Systems · Mathematics 2023-08-11 Sören von der Gracht , Eddie Nijholt , Bob Rink

Networks are a widely used and efficient paradigm to model real-world systems where basic units interact pairwise. Many body interactions are often at play, and cannot be modelled by resorting to binary exchanges. In this work, we consider…

Adaptation and Self-Organizing Systems · Physics 2020-06-03 Timoteo Carletti , Duccio Fanelli , Sara Nicoletti

Suppose we are given a system of coupled oscillators on an unknown graph along with the trajectory of the system during some period. Can we predict whether the system will eventually synchronize? Even with a known underlying graph…

Dynamical Systems · Mathematics 2022-08-25 Hardeep Bassi , Richard Yim , Rohith Kodukula , Joshua Vendrow , Cherlin Zhu , Hanbaek Lyu

Almost equitable partitions (AEPs) have been linked to cluster synchronization in oscillatory systems, highlighting the importance of structure in collective network dynamics. We provide a general spectral framework that formalizes this…

Social and Information Networks · Computer Science 2025-09-15 Tobias Timofeyev , Alice Patania

Synchronization over networks depends strongly on the structure of the coupling between the oscillators. When the coupling presents certain regularities, the dynamics can be coarse-grained into clusters by means of External Equitable…

A network of coupled dynamical systems is represented by a graph whose vertices represent individual cells and whose edges represent couplings between cells. Motivated by the impact of synchronization results of the Kuramoto networks, we…

Dynamical Systems · Mathematics 2023-10-10 Tiago Amorim , Miriam Manoel

A network can be analyzed at different topological scales, ranging from single nodes to motifs, communities, up to the complete structure. We propose a novel intermediate-level topological analysis that considers non-overlapping subgraphs…

Computational Physics · Physics 2009-11-13 Lucas Antiqueira , Luciano da Fontoura Costa

We present clustering methods for multivariate data exploiting the underlying geometry of the graphical structure between variables. As opposed to standard approaches that assume known graph structures, we first estimate the edge structure…

Methodology · Statistics 2015-09-28 Sayantan Banerjee , Rehan Akbani , Veerabhadran Baladandayuthapani

Clustering is the propensity of nodes that share a common neighbour to be connected. It is ubiquitous in many networks but poses many modelling challenges. Clustering typically manifests itself by a higher than expected frequency of…

Dynamical Systems · Mathematics 2016-01-07 Martin Ritchie , Luc Berthouze , Istvan Z. Kiss

Many complex systems involve direct interactions among more than two entities and can be represented by hypergraphs, in which hyperedges encode higher-order interactions among an arbitrary number of nodes. To analyze structures and dynamics…

Physics and Society · Physics 2023-05-23 Kazuki Nakajima , Kazuyuki Shudo , Naoki Masuda

Graph clustering is a fundamental problem in unsupervised learning, with numerous applications in computer science and in analysing real-world data. In many real-world applications, we find that the clusters have a significant high-level…

Data Structures and Algorithms · Computer Science 2023-01-02 Peter Macgregor

We introduce and study systems of randomly coupled maps (RCM) where the relevant parameter is the degree of connectivity in the system. Global (almost-) synchronized states are found (equivalent to the synchronization observed in globally…

Condensed Matter · Physics 2009-10-31 Susanna C. Manrubia , Alexander S. Mikhailov

Laplacian dynamics on a signless graph characterize a class of linear interactions, where pairwise cooperative interactions between all agents lead to the convergence to a common state. On a structurally balanced signed graph, the agents…

Systems and Control · Electrical Eng. & Systems 2025-02-13 Shaoxuan Cui , Chencheng Zhang , Bin Jiang , Hildeberto Jardón Kojakhmetov , Ming Cao

Observational data usually comes with a multimodal nature, which means that it can be naturally represented by a multi-layer graph whose layers share the same set of vertices (users) with different edges (pairwise relationships). In this…

Machine Learning · Computer Science 2015-08-31 Xiaowen Dong , Pascal Frossard , Pierre Vandergheynst , Nikolai Nefedov
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