Robustness of interdependent higher-order networks.

Area of Science:

• Complex systems
• Network science
• Statistical physics

Background:

• Real-world systems exhibit complex interactions beyond pairwise connections, necessitating models like simplicial complexes to capture higher-order structures.
• Interdependent networks are susceptible to cascading failures, a critical concern in complex system robustness.

Purpose of the Study:

• To investigate the robustness of interdependent simplicial complexes under random attacks, incorporating complementary effects from higher-order structures.
• To analyze how higher-order structures influence cascading failures and phase transitions in these complex systems.

Main Methods:

• Utilized the percolation method to derive the percolation threshold and giant component size under steady-state cascading failure.
• Developed analytical predictions and validated them through simulation results.

Main Results:

• Higher-order structures in simplicial complexes enhance robustness compared to traditional interdependent networks.
• The complementary effects of higher-order structures can alter the type of phase transition (first-order to second-order) and increase system resilience.
• Interlayer coupling strength influences the phase transition type, shifting it from second-order to first-order.

Conclusions:

• Simplicial complexes offer a more robust framework for modeling interdependent systems due to their inherent higher-order structures.
• Understanding higher-order interactions is crucial for designing resilient complex networks.
• The findings provide insights into the stability and failure dynamics of higher-order interdependent networks.