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| 001 | 902578 | ||
| 005 | 20220131120355.0 | ||
| 024 | 7 | _ | |a 10.1103/PhysRevResearch.2.042017 |2 doi |
| 024 | 7 | _ | |a 2128/29069 |2 Handle |
| 024 | 7 | _ | |a altmetric:93058550 |2 altmetric |
| 024 | 7 | _ | |a WOS:000605398900001 |2 WOS |
| 037 | _ | _ | |a FZJ-2021-04377 |
| 082 | _ | _ | |a 530 |
| 100 | 1 | _ | |a Xue, Tingting |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Swarming transitions in hierarchical societies |
| 260 | _ | _ | |a College Park, MD |c 2020 |b APS |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1637566761_16357 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Social hierarchy is central to decision-making in the coordinated movement of many swarming species. Here we propose a hierarchical swarm model in the spirit of the Vicsek model of self-propelled particles. We show that, as the hierarchy becomes important, the swarming transition changes from the weak first-order transition observed for egalitarian populations, to a stronger first-order transition for intermediately strong hierarchies, and finally the discontinuity reduces until vanish, where the order-disorder transition appears to be absent in the extremely despotic societies. Associated to this we observe that the spatial structure of the swarm, as measured by the correlation between the density and velocity fields, is strongly mediated by the hierarchy. A two-group model and vectorial noise are also studied for verification. Our results point out the particular relevance of the hierarchical structures to swarming transitions when doing specific case studies. |
| 536 | _ | _ | |a 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) |0 G:(DE-HGF)POF4-5111 |c POF4-511 |f POF IV |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de |
| 700 | 1 | _ | |a Li, Xu |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Grassberger, Peter |0 P:(DE-Juel1)136887 |b 2 |
| 700 | 1 | _ | |a Chen, Li |0 0000-0002-0335-466X |b 3 |
| 773 | _ | _ | |a 10.1103/PhysRevResearch.2.042017 |g Vol. 2, no. 4, p. 042017 |0 PERI:(DE-600)3004165-X |n 4 |p 042017 |t Physical review research |v 2 |y 2020 |x 2643-1564 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/902578/files/PhysRevResearch.2.042017.pdf |y OpenAccess |
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| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action |1 G:(DE-HGF)POF4-510 |0 G:(DE-HGF)POF4-511 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Enabling Computational- & Data-Intensive Science and Engineering |9 G:(DE-HGF)POF4-5111 |x 0 |
| 914 | 1 | _ | |y 2021 |
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| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2020-09-04 |
| 915 | _ | _ | |a Creative Commons Attribution CC BY 4.0 |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |
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