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Top-down and bottom-up models of collective motion
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Devereux, Harvey L. (2022) Top-down and bottom-up models of collective motion. PhD thesis, University of Warwick.
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Official URL: http://webcat.warwick.ac.uk/record=b3912293
Abstract
Active matter is an expanding field of physics covering a diverse range of complex and beautiful phenomena. From examples we see in our everyday lives, such as the flight of birds and organisation of insects, to more esoteric bacteria and other micro-scale biological systems. What we can learn about the physical rules that pin these diverse systems together is important not just for our understanding of physics but our ability to utilise the natural world around us. The core of our understanding of Active matter spans between out-of-equilibrium analogues of wellknown thermodynamics to the realm of complex intelligent decision-making. From a top-down view point, we observe phenomena such as aggregation, ordered motion, dynamic pattern formation, leader-follower relationships, long range interactions, collisions avoidance, and coordinated motion to name a few, and model these directly within a mathematical formalism. From a bottom-up perspective we attempt to explain the generation of these phenomena from intrinsic process driving individual agents. In this thesis we consider a data-driven analysis of collective motion in an insect system, a top-down approach, as well as developing a model of individual decision making based upon future path entropy, a bottom-up approach. The latter results in the spontaneous emergence of some basic features of collective motion seen in real world examples, lending explanatory power.
Item Type: | Thesis (PhD) | ||||
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Subjects: | Q Science > QA Mathematics Q Science > QC Physics Q Science > QH Natural history > QH301 Biology |
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Library of Congress Subject Headings (LCSH): | Biology -- Mathematical models, Brownian motion processes, Insects -- Behavior, Collective behavior -- Mathematical models, Animal behavior -- Mathematical models, Gyrinidae, Mathematical physics, Entropy | ||||
Official Date: | October 2022 | ||||
Dates: |
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Institution: | University of Warwick | ||||
Theses Department: | Mathematics Institute | ||||
Thesis Type: | PhD | ||||
Publication Status: | Unpublished | ||||
Supervisor(s)/Advisor: | Turner, Matthew S. ; Thutupalli, Shashi | ||||
Format of File: | |||||
Extent: | xxi, 138 pages : illustrations (some colour), charts | ||||
Language: | eng |
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