Bimodal Synchronization Performance: Why Noise and Sparse Connectivity Can Improve Collective Timing

2026-05-19 · Source: cs.MA updates on arXiv.org · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems · Depth: Expert, extended

Summary

This paper analyzes a discrete-time, discrete-phase firefly-inspired synchronization model, revealing that collective synchrony emerges only near a critical balance between the quorum threshold (θ) and pulse duration (f). Within this optimal parameter region, the system exhibits bimodal performance, either achieving near-perfect synchronization or becoming trapped in stable multi-cluster states due to "symmetry-induced subgroup locking." Counterintuitively, highly connected or noiseless systems are not necessarily optimal, as increased interaction density can stabilize these low-performance configurations. The study demonstrates that reducing network connectivity or introducing noise into clock updates can suppress these undesirable states by disrupting symmetric interactions, thereby improving global synchronization. This finding suggests that communication or decision-making imperfections can be beneficial, highlighting bimodal performance as a general feature of scalable distributed systems, driven by overly regular interaction structures.

Key takeaway

Decentralized pulse-coupled systems, like those in swarm robotics, exhibit bimodal synchronization where high connectivity and noiseless conditions often trap them in stable, low-performance multi-cluster states. This failure stems from symmetry-induced subgroup locking, preventing global synchrony even when the quorum threshold matches pulse duration. Introducing moderate noise (e.g., $\sigma=0.1-0.4$) or reducing network connectivity can break these symmetries, enabling robust global synchronization and improving system performance.

Topics

• Pulse-coupled Oscillators
• Firefly Synchronization
• Bimodal Performance
• Symmetry-induced Subgroup Locking
• Network Connectivity

Code references

• Tianfu-swarm/firefly_two-phase_performance

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Editorial summary, takeaway, and curation by AIssential. Original article published by cs.MA updates on arXiv.org.