Senior Theses
Publication Date
5-2018
Document Type
Thesis (Open Access)
Degree Name
Bachelor of Science in Physics
Department
Physics
Faculty Advisor(s)
Joelle Murray (Thesis Advisor)
Jennifer Heath & Michael Crosser (Committee Members)
Subject Categories
Applied Mathematics | Biological and Chemical Physics | Dynamic Systems | Non-linear Dynamics | Physics
Abstract
A system is considered complex if it is composed of individual parts that abide by their own set of rules, while the system, as a whole, will produce non-deterministic properties. This prevents the behavior of such systems from being accurately predicted. The motivation for studying complexity spurs from the fact that it is a fundamental aspect of innumerable systems. Among complex systems, fly swarms are relatively simple, but even so they are still not well understood. In this research, several computational models were developed to assist with the understanding of fly swarms. These models were primarily analyzed by using the average distance from the center of mass, average distance between flies, and the inertia ratios. The inertia ratios indicated asymmetric fly systems, suggesting some accuracy in such models, as physical fly swarms exhibit asymmetry. A major goal of this research was to provide a mathematical definition for swarming. While an arbitrary definition was developed, future research is required to pinpoint a definite definition.
Recommended Citation
Bebee, Austin, "The Computational Study of Fly Swarms & Complexity" (2018). Senior Theses. 37.
https://digitalcommons.linfield.edu/physstud_theses/37
Included in
Biological and Chemical Physics Commons, Dynamic Systems Commons, Non-linear Dynamics Commons
