Entropy by Neighbor Distance as a New Measure for Characterizing Spatiotemporal Orders in Microscopic Collective Systems
Collective systems self-organize to form globally ordered spatiotemporal patterns. Finding appropriate measures to characterize the order in these patterns will contribute to our understanding of the principles of self-organization in all collective systems. Here we examine a new measure based on th...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Micromachines |
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| Online Access: | https://www.mdpi.com/2072-666X/14/8/1503 |
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| author | Yulei Fu Zongyuan Wu Sirui Zhan Jiacheng Yang Gaurav Gardi Vimal Kishore Paolo Malgaretti Wendong Wang |
| author_facet | Yulei Fu Zongyuan Wu Sirui Zhan Jiacheng Yang Gaurav Gardi Vimal Kishore Paolo Malgaretti Wendong Wang |
| author_sort | Yulei Fu |
| collection | DOAJ |
| description | Collective systems self-organize to form globally ordered spatiotemporal patterns. Finding appropriate measures to characterize the order in these patterns will contribute to our understanding of the principles of self-organization in all collective systems. Here we examine a new measure based on the entropy of the neighbor distance distributions in the characterization of collective patterns. We study three types of systems: a simulated self-propelled boid system, two active colloidal systems, and one centimeter-scale robotic swarm system. In all these systems, the new measure proves sensitive in revealing active phase transitions and in distinguishing steady states. We envision that the entropy by neighbor distance could be useful for characterizing biological swarms such as bird flocks and for designing robotic swarms. |
| first_indexed | 2024-03-10T23:44:08Z |
| format | Article |
| id | doaj.art-ee8c6298c78a465c9509bb8bdefc9155 |
| institution | Directory Open Access Journal |
| issn | 2072-666X |
| language | English |
| last_indexed | 2024-03-10T23:44:08Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Micromachines |
| spelling | doaj.art-ee8c6298c78a465c9509bb8bdefc91552023-11-19T02:12:34ZengMDPI AGMicromachines2072-666X2023-07-01148150310.3390/mi14081503Entropy by Neighbor Distance as a New Measure for Characterizing Spatiotemporal Orders in Microscopic Collective SystemsYulei Fu0Zongyuan Wu1Sirui Zhan2Jiacheng Yang3Gaurav Gardi4Vimal Kishore5Paolo Malgaretti6Wendong Wang7University of Michigan—Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, ChinaUniversity of Michigan—Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, ChinaUniversity of Michigan—Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, ChinaThe Academy for Engineering and Technology, Fudan University, Shanghai 200433, ChinaPhysical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, GermanyDepartment of Physics, Banaras Hindu University, Varanasi 221005, IndiaHelmholtz Institute Erlangen-Nürnberg for Renewable Energy (IEK-11), Forschungszentrum Jülich, 52425 Jülich, GermanyUniversity of Michigan—Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, ChinaCollective systems self-organize to form globally ordered spatiotemporal patterns. Finding appropriate measures to characterize the order in these patterns will contribute to our understanding of the principles of self-organization in all collective systems. Here we examine a new measure based on the entropy of the neighbor distance distributions in the characterization of collective patterns. We study three types of systems: a simulated self-propelled boid system, two active colloidal systems, and one centimeter-scale robotic swarm system. In all these systems, the new measure proves sensitive in revealing active phase transitions and in distinguishing steady states. We envision that the entropy by neighbor distance could be useful for characterizing biological swarms such as bird flocks and for designing robotic swarms.https://www.mdpi.com/2072-666X/14/8/1503active mattercollective behaviorphase transitionorder parameter |
| spellingShingle | Yulei Fu Zongyuan Wu Sirui Zhan Jiacheng Yang Gaurav Gardi Vimal Kishore Paolo Malgaretti Wendong Wang Entropy by Neighbor Distance as a New Measure for Characterizing Spatiotemporal Orders in Microscopic Collective Systems Micromachines active matter collective behavior phase transition order parameter |
| title | Entropy by Neighbor Distance as a New Measure for Characterizing Spatiotemporal Orders in Microscopic Collective Systems |
| title_full | Entropy by Neighbor Distance as a New Measure for Characterizing Spatiotemporal Orders in Microscopic Collective Systems |
| title_fullStr | Entropy by Neighbor Distance as a New Measure for Characterizing Spatiotemporal Orders in Microscopic Collective Systems |
| title_full_unstemmed | Entropy by Neighbor Distance as a New Measure for Characterizing Spatiotemporal Orders in Microscopic Collective Systems |
| title_short | Entropy by Neighbor Distance as a New Measure for Characterizing Spatiotemporal Orders in Microscopic Collective Systems |
| title_sort | entropy by neighbor distance as a new measure for characterizing spatiotemporal orders in microscopic collective systems |
| topic | active matter collective behavior phase transition order parameter |
| url | https://www.mdpi.com/2072-666X/14/8/1503 |
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