Fly Swarms and Complexity

A system is complex if it contains many interacting components. The motivation to study the properties of such systems comes from their prevalence in nature. The dynamics, the organization, and the degree of interactions between the components of the system were considered. At the foundation of this research is Self-Organized Criticality (SOC), a phenomenon put forward by Per Bak and colleagues in 1987. SOC is exhibited by slowly driven, highly nonlinear dynamic systems that have a critical point as an attractor. It is a mechanism that has been proposed by which complexity arises in nature. In 2014, Attanasi et. al published \u22Finite-Size Scaling as a Way to Probe Near Criticality in Natural Swarms\u22 which suggested that swarms are at a critical point or near criticality. This paved the investigation of the mathematical properties associated with SOC. A computational model was created as a way to analyze fly swarms for evidence of SOC and measure the degree of interactions between the flies and organization by looking at the connected correlation of the particles and polarization respectively. The data analysis showed that the particles are highly correlated and disorganization evident from a low polymerization. The cluster analysis of the flies did not yield interesting results; however, running a Fast Fourier Transform (FFT) on the clusters sizes with the clusters sizes being the input signal resulted in frequency plots that are similar to those of 1/f noise associated with Self-Organized Criticality. This suggested a possible evidence of SOC in the computational model; however, further research is required to better understand what the plots mean