Street map analysis with excitable chemical medium.

Area of Science:

• Chemical Systems Biology
• Computational Science
• Network Theory

Background:

• Belousov-Zhabotinsky (BZ) reactions, known for excitation wave propagation, are utilized in unconventional computing.
• BZ computing employs wave front interactions, governed by geometry and external stimuli like illumination, for information processing.
• Existing BZ computing prototypes include logical circuits, wet electronics, and neuromorphic systems.

Purpose of the Study:

• To apply Belousov-Zhabotinsky (BZ) computing principles to analyze the geometry of street networks.
• To investigate excitation wave propagation dynamics within a simulated street network under varying excitability conditions.
• To demonstrate and explain a pruning strategy observed in street network formation as excitability decreases.

Main Methods:

• Utilized the two-variable Oregonator equations, a validated model for Belousov-Zhabotinsky (BZ) reactions.
• Simulated excitation wave front propagation across a range of excitability parameters, transitioning from excitable to nonexcitable states.
• Analyzed the selection and pruning of network pathways based on wave propagation dynamics and geometrical constraints.

Main Results:

• Demonstrated a distinct pruning strategy in simulated street networks with decreasing medium excitability.
• Observed preferential selection of wider and more ballistically appropriate streets as excitability diminished.
• Elucidated the underlying mechanics of street selection and pruning driven by wave propagation dynamics.

Conclusions:

• The study successfully adapted Belousov-Zhabotinsky (BZ) reaction principles to model street network geometry.
• A novel pruning mechanism for street network formation was identified, linked to decreasing excitability.
• Findings provide a foundation for future research into urban dynamics and the characterization of street network structures.