How synchronized human networks escape local minima

Finding the global minimum in complex networks while avoiding local minima is challenging in many types of networks. In human networks and communities, adapting and finding new stable states amid changing conditions due to conflicts, climate changes, or disasters, is crucial. We studied the dynamics of complex networks of violin players and observed that such human networks have different methods to avoid local minima than other non-human networks. Humans can change the coupling strength between them or change their tempo. This leads to different dynamics than other networks and makes human networks more robust and better resilient against perturbations. We observed high-order vortex states, oscillation death, and amplitude death, due to the unique dynamics of the network. This research may have implications in politics, economics, pandemic control, decision-making, and predicting the dynamics of networks with artificial intelligence.

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Publication Details

Journal
Nature Communications
Published
2024-10-28
DOI
https://doi.org/10.1038/s41467-024-53540-7
Citations
11
Primary Topic
Nonlinear Dynamics and Pattern Formation
Type
article
Field-Weighted Citation Impact
3.84

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article

How synchronized human networks escape local minima

Hamootal Duadi, Nir Davidson, Moti Fridman, Elad Shniderman et al.
11 citations
Nature Communications
Nonlinear Dynamics and Pattern Formation
3.84
article

How synchronized human networks escape local minima

Hamootal Duadi, Nir Davidson, Moti Fridman, Elad Shniderman, Shir Shahal, Yahav Avraham
article en
11 citations

Abstract

Finding the global minimum in complex networks while avoiding local minima is challenging in many types of networks. In human networks and communities, adapting and finding new stable states amid changing conditions due to conflicts, climate changes, or disasters, is crucial. We studied the dynamics of complex networks of violin players and observed that such human networks have different methods to avoid local minima than other non-human networks. Humans can change the coupling strength between them or change their tempo. This leads to different dynamics than other networks and makes human networks more robust and better resilient against perturbations. We observed high-order vortex states, oscillation death, and amplitude death, due to the unique dynamics of the network. This research may have implications in politics, economics, pandemic control, decision-making, and predicting the dynamics of networks with artificial intelligence.

Nature CommunicationsVol. 15(1)
Bar-Ilan University (IL), Technion – Israel Institute of Technology (IL), Weizmann Institute of Science (IL)
Bar-Ilan University
Reduced inequalities
Openalex Percentile: Top 6%
Nonlinear Dynamics and Pattern Formation
3.84
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