English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Bursty switching dynamics promotes the collapse of network topologies

Zeng, Z., Feng, M., Perc, M., Kurths, J. (2025): Bursty switching dynamics promotes the collapse of network topologies. - Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 481, 2310, 20240936.
https://doi.org/10.1098/rspa.2024.0936

Item is

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Zeng, Ziyan1, Author
Feng, Minyu1, Author
Perc, Matjaž1, Author
Kurths, Jürgen2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

Content

show
hide
Free keywords: -
 Abstract: Time-varying connections are crucial in understanding the structures and dynamics of complex networks. In this paper, we propose a continuous-time switching topology model for temporal networks that are driven by bursty behaviour and study the effects on network structure and dynamic processes. Each edge can switch between an active and a dormant state, leading to intermittent activation patterns that are characterized by a renewal process. We analyse the stationarity of the network activation scale and emerging degree distributions by means of the Markov chain theory. We show that switching dynamics can promote the collapse of network topologies by reducing heterogeneities and forming isolated components in the underlying network. Our results indicate that switching topologies can significantly influence random walks in different networks and promote cooperation in donation games. Our research thus provides a simple quantitative framework to study network dynamics with temporal and intermittent interactions across social and technological networks.

Details

show
hide
Language(s): eng - English
 Dates: 2025-03-262025-03-26
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1098/rspa.2024.0936
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Proceedings of the Royal Society A : Mathematical, Physical and Engineering Sciences
Source Genre: Journal, SCI, Scopus, p3
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 481 (2310) Sequence Number: 20240936 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/201802091
Publisher: The Royal Society