Large-scale dynamics of self-propelled particles moving through obstacles: model derivation and pattern formation
File(s)
Author(s)
Type
Journal Article
Abstract
We model and study the patterns created through the interaction
of collectively moving self-propelled particles (SPPs) and elastically tethered
obstacles. Simulations of an individual-based model reveal at least three distinct large-scale patterns: travelling bands, trails and moving clusters. This
motivates the derivation of a macroscopic partial differential equations model
for the interactions between the self-propelled particles and the obstacles, for
which we assume large tether stiffness. The result is a coupled system of non linear, non-local partial differential equations. Linear stability analysis shows
that patterning is expected if the interactions are strong enough and allows
for the predictions of pattern size from model parameters. The macroscopic
equations reveal that the obstacle interactions induce short-ranged SPP aggregation, irrespective of whether obstacles and SPPs are attractive or repulsive.
of collectively moving self-propelled particles (SPPs) and elastically tethered
obstacles. Simulations of an individual-based model reveal at least three distinct large-scale patterns: travelling bands, trails and moving clusters. This
motivates the derivation of a macroscopic partial differential equations model
for the interactions between the self-propelled particles and the obstacles, for
which we assume large tether stiffness. The result is a coupled system of non linear, non-local partial differential equations. Linear stability analysis shows
that patterning is expected if the interactions are strong enough and allows
for the predictions of pattern size from model parameters. The macroscopic
equations reveal that the obstacle interactions induce short-ranged SPP aggregation, irrespective of whether obstacles and SPPs are attractive or repulsive.
Date Issued
2020-09-25
Date Acceptance
2020-09-08
Citation
Bulletin of Mathematical Biology, 2020, 82 (129), pp.1-39
ISSN
0092-8240
Publisher
Springer
Start Page
1
End Page
39
Journal / Book Title
Bulletin of Mathematical Biology
Volume
82
Issue
129
Copyright Statement
© The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Sponsor
The Royal Society
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (EPSRC)
Identifier
https://link.springer.com/article/10.1007/s11538-020-00805-z
Grant Number
WM130048
EP/M006883/1
EP/P013651/1
Subjects
Science & Technology
Life Sciences & Biomedicine
Biology
Mathematical & Computational Biology
Life Sciences & Biomedicine - Other Topics
Self-propelled particles
Hydrodynamic limit
Pattern formation
Stability analysis
Gradient flow
Non-local interactions
EQUATIONS
DRIVEN
SIMULATIONS
EVOLUTION
SYSTEM
Gradient flow
Hydrodynamic limit
Non-local interactions
Pattern formation
Self-propelled particles
Stability analysis
Mathematical Concepts
Models, Theoretical
Molecular Dynamics Simulation
Particle Size
Particle Size
Models, Theoretical
Mathematical Concepts
Molecular Dynamics Simulation
math.AP
math.AP
cond-mat.soft
q-bio.CB
35Q70, 82C05, 82C22, 82C70, 92B25, 92C35, 76S05
01 Mathematical Sciences
06 Biological Sciences
Bioinformatics
Publication Status
Published
Date Publish Online
2020-09-25