Collective motion from local attraction.

Area of Science:

• Complex Systems
• Biophysics
• Collective Behavior

Background:

• Animal groups like fish schools and bird flocks display complex cohesive movement patterns.
• Existing self-propelled particle models often rely on neighbor alignment for collective motion.

Purpose of the Study:

• To propose and analyze a novel self-propelled particle model where social attraction is the sole interaction force.
• To investigate the emergence of different collective motion phases based on attraction and inertia.
• To explore pattern diversity under varying visual perception and noise levels.

Main Methods:

• Development of a self-propelled particle model with attraction as the only social force.
• Simulation analysis in the zero noise limit to study phase transitions based on attraction and inertia.
• Introduction of restricted vision fields and increased noise to observe pattern dynamics.

Main Results:

• The model successfully generates three distinct phases: swarms, undirected mills, and moving aligned groups.
• Phase transitions are shown to depend on the balance between attraction strength and individual inertia.
• Restricted vision and increased noise lead to directed mills and novel 'rotating chain' structures.

Conclusions:

• Social attraction alone is sufficient to generate a rich variety of collective animal behaviors.
• The model provides insights into the fundamental mechanisms driving flocking dynamics in nature.
• The findings highlight the role of perception and noise in shaping emergent group patterns.