Incorporating reputation into reinforcement learning can promote cooperation on hypergraphs DOI
Kuan Zou, Changwei Huang

Chaos Solitons & Fractals, Год журнала: 2024, Номер 186, С. 115203 - 115203

Опубликована: Июнь 29, 2024

Язык: Английский

The transition to synchronization of networked systems DOI Creative Commons
Atiyeh Bayani, Fahimeh Nazarimehr, Sajad Jafari

и другие.

Nature Communications, Год журнала: 2024, Номер 15(1)

Опубликована: Июнь 10, 2024

Язык: Английский

Процитировано

12

Self-organized bistability on globally coupled higher-order networks DOI
Md Sayeed Anwar, Nikita Frolov, Alexander E. Hramov

и другие.

Physical review. E, Год журнала: 2024, Номер 109(1)

Опубликована: Янв. 26, 2024

Self-organized bistability (SOB) stands as a critical behavior for the systems delicately adjusting themselves to brink of bistability, characterized by first-order transition. Its essence lies in inherent ability system undergo enduring shifts between coexisting states, achieved through self-regulation controlling parameter. Recently, SOB has been established scale-free network recurrent transition short-living state global synchronization. Here, we embark on theoretical exploration that extends boundaries concept higher-order (implicitly embedded microscopically within simplicial complex) while considering limitations imposed coupling constraints. By applying Ott-Antonsen dimensionality reduction thermodynamic limit network, derive requirements under limits are good agreement with numerical simulations finite size. We use continuous synchronization diagrams and statistical data from spontaneous synchronized events demonstrate crucial role plays initiating terminating temporary events. show weak-coupling consumption, these occurrences closely resemble traits epileptic brain functioning.

Язык: Английский

Процитировано

11

Dynamics of diseases spreading on networks in the forms of reaction-diffusion systems DOI

Gui-Quan Sun,

Runzi He,

Lifeng Hou

и другие.

EPL (Europhysics Letters), Год журнала: 2024, Номер 147(1), С. 12001 - 12001

Опубликована: Июль 1, 2024

Abstract In the face of persistent threats posed by infectious diseases, despite remarkable medical advancements, understanding and efficiently controlling their spatial spread through mathematical modeling remain imperative. Networked reaction-diffusion systems offer a promising avenue to effectively delineate population discrete distribution individual movement heterogeneity. However, dynamics diseases within these formulation optimal control strategies are currently undergoing vigorous development. this letter, we illustrate disease in networked lens control, considering various network complexities from pairwise networks higher-order networks. It then emphasizes applicability designing effective across diverse complexities. Finally, discuss existing challenges.

Язык: Английский

Процитировано

10

Patterns of neuronal synchrony in higher-order networks DOI
Soumen Majhi, Samali Ghosh, Palash Kumar Pal

и другие.

Physics of Life Reviews, Год журнала: 2024, Номер unknown

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

9

Topology shapes dynamics of higher-order networks DOI
Ana P. Millán, Hanlin Sun, Lorenzo Giambagli

и другие.

Nature Physics, Год журнала: 2025, Номер unknown

Опубликована: Фев. 19, 2025

Язык: Английский

Процитировано

2

Coupled diffusion dynamics of competitive information and green behaviors on multiplex networks under policy intervention DOI

Zhishuang Wang,

Yufeng Wan,

Qian Yin

и другие.

Applied Mathematics and Computation, Год журнала: 2025, Номер 495, С. 129328 - 129328

Опубликована: Фев. 4, 2025

Язык: Английский

Процитировано

1

The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives DOI Creative Commons
Timo Bröhl, Thorsten Rings, Jan Pukropski

и другие.

Frontiers in Network Physiology, Год журнала: 2024, Номер 3

Опубликована: Янв. 16, 2024

Epilepsy is now considered a network disease that affects the brain across multiple levels of spatial and temporal scales. The paradigm shift from an epileptic focus—a discrete cortical area which seizures originate—to widespread network—spanning lobes hemispheres—considerably advanced our understanding epilepsy continues to influence both research clinical treatment this multi-faceted high-impact neurological disorder. network, however, not static but evolves in time requires novel approaches for in-depth characterization. In review, we discuss conceptual basics theory critically examine state-of-the-art recording techniques analysis tools used assess characterize time-evolving human network. We give account on current shortcomings highlight potential developments towards improved management epilepsy.

Язык: Английский

Процитировано

9

Revealing Higher-Order Interactions in High-Dimensional Complex Systems: A Data-Driven Approach DOI Creative Commons
M. Reza Rahimi Tabar, Farnik Nikakhtar, Laya Parkavousi

и другие.

Physical Review X, Год журнала: 2024, Номер 14(1)

Опубликована: Март 18, 2024

Natural and manmade complex systems are comprised of different elementary units, being either system components or diverse subsystems as in the case networked systems. These units interact with each other a possibly nonlinear way, which results dynamics that is generally dissipative nonstationary. One challenges modeling such identification not only pairwise but, more importantly, higher-order interactions, together their directions strengths from measured multivariate time series. Here, we propose novel data-driven approach for characterizing interactions orders. Our based on solving set linear equations constructed Kramers-Moyal coefficients derived statistical moments N-dimensional We demonstrate substantial potential applications by reconstruction various multidimensional dynamical Published American Physical Society 2024

Язык: Английский

Процитировано

9

Robustness of interdependent hypergraphs: A bipartite network framework DOI Creative Commons
Xingyu Pan, Jie Zhou, Yinzuo Zhou

и другие.

Physical Review Research, Год журнала: 2024, Номер 6(1)

Опубликована: Янв. 12, 2024

In this paper, we develop a bipartite network framework to study the robustness of interdependent hypergraphs. From such perspective, nodes and hyperedges hypergraph are equivalent each other, property that largely simplifies their mathematical treatment. We general percolation theory based on representation apply it hypergraphs against random damage, which verify with numerical simulations. analyze variety interacting patterns, from heterogeneous correlated hyperstructures, full- partial-dependency couplings between an arbitrary number hypergraphs, characterize structural stability via phase diagrams. Given its generality, expect our will provide useful insights for development more realistic venues cascading failures in higher-order systems. Published by American Physical Society 2024

Язык: Английский

Процитировано

7

Simplices-based higher-order enhancement graph neural network for multi-behavior recommendation DOI
Qingbo Hao, Chundong Wang, Yingyuan Xiao

и другие.

Information Processing & Management, Год журнала: 2024, Номер 61(5), С. 103790 - 103790

Опубликована: Май 29, 2024

Язык: Английский

Процитировано

7