期刊
PHYSICAL REVIEW LETTERS
卷 117, 期 24, 页码 -出版社
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevLett.117.248001
关键词
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资金
- CONICET
- Agence Nationale de la Recherche [ANR-15-CE30-0002-01]
- Agence Nationale de la Recherche (ANR) [ANR-15-CE30-0002] Funding Source: Agence Nationale de la Recherche (ANR)
We study a minimal cognitive flocking model, which assumes that the moving entities navigate using the available instantaneous visual information exclusively. The model consists of active particles, with no memory, that interact by a short-ranged, position-based, attractive force, which acts inside a vision cone (VC), and lack velocity-velocity alignment. We show that this active system can exhibit-due to the VC that breaks Newton's third law-various complex, large-scale, self-organized patterns. Depending on parameter values, we observe the emergence of aggregates or millinglike patterns, the formation of moving-locally polar-files with particles at the front of these structures acting as effective leaders, and the self-organization of particles into macroscopic nematic structures leading to long-ranged nematic order. Combining simulations and nonlinear field equations, we show that position-based active models, as the one analyzed here, represent a new class of active systems fundamentally different from other active systems, including velocity-alignment-based flocking systems. The reported results are of prime importance in the study, interpretation, and modeling of collective motion patterns in living and nonliving active systems.
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