Non-reciprocal visual perception and polar alignment drive collective states in chiral active particles
Diganta Bhaskar, Abhishek Chaudhuri, Anil Kumar Dasanna

TL;DR
This study investigates how chirality, non-reciprocal perception, and alignment interactions in chiral active particles lead to diverse collective behaviors and phases, revealing new states driven by these combined effects.
Contribution
It introduces a model of chiral intelligent active Brownian particles with vision-based sensing, demonstrating novel collective states influenced by chirality and non-reciprocal interactions.
Findings
Identified multiple collective states including spinners, vortices, ripples, and swarms.
Chirality determines phase morphology, with high chirality leading to dilute phases.
Ripple loops emerge as a new state driven by outward torques.
Abstract
Self-propelled particles rarely move in straight lines; environmental interactions, shape asymmetry, and intrinsic torques generically induce curved or fluctuating trajectories. In biological and synthetic systems, this curvature often coexists with directional sensing and non-reciprocal interactions. Motivated by this, we explore the collective dynamics of chiral intelligent active Brownian particles (iABPs) that combine polar alignment with vision-based sensing. By varying the ratio of alignment to visual maneuverability, the vision angle, and the reduced chirality , we construct a phase diagram exhibiting diverse collective states: spinners, vortices, ripples, worm-like swarms, rotary clusters, and irregular aggregates. Chirality critically governs their morphology: high chirality yields dilute phases, while moderate to low chirality produces cohesive yet dynamic…
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Taxonomy
TopicsMicro and Nano Robotics · Modular Robots and Swarm Intelligence · Distributed Control Multi-Agent Systems
