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Greedy optimization for growing spatially embedded oscillatory networks.

Damien Beecroft1, Juan G Restrepo2, David Angulo-Garcia3

  • 1Department of Applied Mathematics, University of Washington, Washington 98195, USA.

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Summary
This summary is machine-generated.

This study introduces a greedy algorithm for growing spatially embedded oscillator networks, optimizing stability and minimizing link length. The method enhances network synchronization and resilience with minimal cost.

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Area of Science:

  • Complex Systems
  • Network Science
  • Physics

Background:

  • Oscillator synchronization often depends on physical connections, making distance critical.
  • Growing spatially embedded networks requires strategies to balance connectivity and stability.

Purpose of the Study:

  • To propose and explore a greedy algorithm for constructing spatially embedded oscillator networks.
  • To optimize network stability and minimize the cost of added link lengths during network growth.

Main Methods:

  • Sequential node addition to minimize link length cost.
  • Optimization of linear stability during network growth.
  • Numerical analysis of network topological properties and stability metrics.

Main Results:

  • The algorithm significantly improves network stability with minimal added length cost.
  • Resulting networks exhibit approximate exponential degree distribution, independent of algorithm parameters.
  • Network resilience and efficiency are positively affected by the proposed growth algorithm.

Conclusions:

  • The greedy algorithm effectively balances stability and cost in growing oscillator networks.
  • Findings are extendable to heterogeneous network classes.
  • This work advances directed growth algorithms for stable and efficient oscillatory networks.