Submission Title

Fly Swarms and Complexity

Location

Jereld R. Nicholson Library: Grand Avenue

Subject Area

Physics/Applied Physics

Description

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, exhibits unexpected properties. The motivation for studying complexity spurs from the fact that it is a fundamental aspect of many systems, including forest fires, earthquakes, stock markets, fish schools, plant root growth, and fly swarms. We are particularly interested in fly swarms and the possible complex properties that the swarm exhibits, arising from the individual fly interactions.

Fly swarms are a relatively simple complex system, but such systems are still not fully understood. In this research, various computational models were developed to assist with the understanding of fly swarms. These models were primarily described by analyzing 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.

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May 18th, 3:30 PM May 18th, 5:00 PM

Fly Swarms and Complexity

Jereld R. Nicholson Library: Grand Avenue

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, exhibits unexpected properties. The motivation for studying complexity spurs from the fact that it is a fundamental aspect of many systems, including forest fires, earthquakes, stock markets, fish schools, plant root growth, and fly swarms. We are particularly interested in fly swarms and the possible complex properties that the swarm exhibits, arising from the individual fly interactions.

Fly swarms are a relatively simple complex system, but such systems are still not fully understood. In this research, various computational models were developed to assist with the understanding of fly swarms. These models were primarily described by analyzing 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.

 

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