论文标题

通过视觉感知,主动布朗颗粒的紧急集体行为

Emergent collective behavior of active Brownian particles by visual perception

论文作者

Negi, Rajendra Singh, Winkler, Roland G., Gompper, Gerhard

论文摘要

通过模拟研究了由自我探测的活性布朗颗粒组成的系统,以最小的认知羊群模型。活性布朗颗粒的动力学通过定向响应扩展,其可操作性有限,对视觉锥体内邻居位置和截止半径的瞬时视觉输入。该系统表现出大规模的自组织结构,这些结构取决于选定的参数值,尤其是排除体积相互作用的存在。分析并构建了相图,并构建了相图,并构建了相图。对粒子均方位移的分析显示了稀释系统和蠕虫相的ABP样动力学。在密集堆积结构的极限下,活动扩散系数明显较小,取决于簇中的颗粒数量。我们对簇增长动力学的分析表明,在平衡中短距离胶体系统的过程中的过程明显差异。具体而言,特定大小的簇的生长和衰减的特征时间比各向同性有吸引力的胶体的特征时间更长,我们将其归因于有向视觉感知的非互惠性质。我们的模拟揭示了ABP特征的相互作用(例如排除和旋转扩散)与基于认知的相互作用和导航之间存在很强的相互作用。

Systems comprised of self-steering active Brownian particles are studied via simulations for a minimal cognitive flocking model. The dynamics of the active Brownian particles is extended by an orientational response with limited maneuverability to an instantaneous visual input of the positions of neighbors within a vision cone and a cut-off radius. The system exhibits large-scale self-organized structures, which depend on selected parameter values, and, in particular, the presence of excluded-volume interactions. The emergent structures in two dimensions, such as worms, worm-aggregate coexistence, and hexagonally close-packed structures, are analysed and phase diagrams are constructed. The analysis of the particle's mean-square displacement shows ABP-like dynamics for dilute systems and the worm phase. In the limit of densely packed structures, the active diffusion coefficient is significantly smaller and depends on the number of particles in the cluster. Our analysis of the cluster-growth dynamics shows distinct differences to processes in systems of short-range attractive colloids in equilibrium. Specifically, the characteristic time for the growth and decay of clusters of a particular size is longer than that of isotropically attractive colloids, which we attribute to the non-reciprocal nature of the directed visual perception. Our simulations reveal a strong interplay between ABP-characteristic interactions, such as volume exclusion and rotational diffusion, and cognitive-based interactions and navigation.

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