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ABSTRACT There are many instances of collective behaviors in the natural world. For example, eukaryotic cells coordinate their motion to heal wounds; bacteria swarm during colony expansion; defects in alignment in growing bacterial populations lead to biofilm growth; and birds move within dynamic flocks. Although the details of how these groups behave vary across animals and species, they share the same qualitative feature: they exhibit collective behaviors that are not simple extensions of details associated with the motion of an individual. To learn more about these biological systems, we propose studying these systems through the lens of the foundational Vicsek model. Here, we present the process of building this computational model from scratch in a tutorial format that focuses on building the appropriate skills of an undergraduate student. In doing so, an undergraduate student should be able to work alongside this article, the corresponding tutorial, and the original manuscript of the Vicsek model to build their own model. We conclude by summarizing some of the current work involving computational modeling of flocking with Vicsek-type models.
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Diverse behaviors in non-uniform chiral and non-chiral swarmalators
Abstract We study the emergent behaviors of a population of swarming coupled oscillators, dubbed swarmalators. Previous work considered the simplest, idealized case: identical swarmalators with global coupling. Here we expand this work by adding more realistic features: local coupling, non-identical natural frequencies, and chirality. This more realistic model generates a variety of new behaviors including lattices of vortices, beating clusters, and interacting phase waves. Similar behaviors are found across natural and artificial micro-scale collective systems, including social slime mold, spermatozoa vortex arrays, and Quincke rollers. Our results indicate a wide range of future use cases, both to aid characterization and understanding of natural swarms, and to design complex interactions in collective systems from soft and active matter to micro-robotics.
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- Award ID(s):
- 2042411
- PAR ID:
- 10397991
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Nature Communications
- Volume:
- 14
- Issue:
- 1
- ISSN:
- 2041-1723
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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