Mean-field theory for double-well systems on degree-heterogeneous networks

Author:

Kundu Prosenjit1ORCID,MacLaren Neil G.1ORCID,Kori Hiroshi2,Masuda Naoki134ORCID

Affiliation:

1. Department of Mathematics, State University of New York at Buffalo, Buffalo, NY 14260-2900, USA

2. Department of Complexity Science and Engineering, The University of Tokyo, Chiba 277-8561, Japan

3. Computational and Data-Enabled Science and Engineering Program, State University of New York at Buffalo, Buffalo, NY 14260-5030, USA

4. Faculty of Science and Engineering, Waseda University, Tokyo 169-8555, Japan

Abstract

Many complex dynamical systems in the real world, including ecological, climate, financial and power-grid systems, often show critical transitions, or tipping points, in which the system’s dynamics suddenly transit into a qualitatively different state. In mathematical models, tipping points happen as a control parameter gradually changes and crosses a certain threshold. Tipping elements in such systems may interact with each other as a network, and understanding the behaviour of interacting tipping elements is a challenge because of the high dimensionality originating from the network. Here, we develop a degree-based mean-field theory for a prototypical double-well system coupled on a network with the aim of understanding coupled tipping dynamics with a low-dimensional description. The method approximates both the onset of the tipping point and the position of equilibria with a reasonable accuracy. Based on the developed theory and numerical simulations, we also provide evidence for multistage tipping point transitions in networks of double-well systems.

Funder

JSPS KAKENHI

National Science Foundation

AFOSR European Office

Sumitomo Foundation

Publisher

The Royal Society

Subject

General Physics and Astronomy,General Engineering,General Mathematics

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Anticipating regime shifts by mixing early warning signals from different nodes;Nature Communications;2024-02-05

2. Dimensionality reduction in discrete-time dynamical systems;Communications in Nonlinear Science and Numerical Simulation;2023-08

3. Dimension reduction in higher-order contagious phenomena;Chaos: An Interdisciplinary Journal of Nonlinear Science;2023-05-01

4. Dimension reduction of dynamics on modular and heterogeneous directed networks;PNAS Nexus;2023-05

5. Correction to: ‘Mean-field theory for double-well systems on degree-heterogeneous networks’ (2023) by Kundu et al.;Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences;2023-04

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