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In this project we model the spread of a virus on networks as a probabilistic process. We assume the virus breaks out at one vertex on a network and then spreads to neighboring vertices in each time step with a certain probability. Our objective is to find probability distributions that describe the uncertain number of infected vertices at a given time step. The networks we consider are paths, cycles, star graphs, complete graphs, and broom graphs. Through the use of Markov chains and Jordan Normal Form we analyze the probability distribution of these graphs, characterizing the transition matrix for each graph as well as the Jordan Form matrices.
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DeCusatis, Teagan, "Analyzing the Probabilistic Spread of a Virus on Various Networks" (2018). Senior Projects Spring 2018. 286.