Eigenvectors Graph Theory Linear algebra Quantum Computing Quantum Walks
Let $A$ be the adjacency matrix of a graph. We will associate this graph with a continuous-time quantum walk by using a transition matrix $U(t) = e^{itA}$. This allows us to create another matrix $\hat{M}$ which is time-independent. $\hat{M}$ gives us some measure of average probability values and long-term behavior of a continuous time quantum walk and is called the average mixing matrix. This has been studied extensively on trees and other graphs with distinct eigenvalues.
Our work focuses on graphs which have repeated eigenvalues. We give our own proof for why Star graphs have full rank, and we present an entry-wise recursive way to express the eigenvectors of Path graphs. We utilize this result to prove that the rank of Dutch Windmills with 3 or more $P_m$ blades is $\left\lceil\frac{m}{2}\right\rceil b + 1$. We go on to prove that French Windmills (appending $K_m$ instead) have full rank and that Kulli Cycle Windmills (appending $C_m$ alternate between full rank when $m$ is odd and $\frac{m}{2}b+1$ when $m$ is even.
Lastly we present some experimental results for Kulli Path Windmills which appear to mirror the behavior of Dutch Windmills. Separately, we demonstrate that when adding blades of different lengths onto an initially regular Dutch Windmill, it does not always add the rank of the blade sub-matrix as might be expected.
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Title
Continuous-Time Quantum Walks on Windmill Graphs
Creators
Paula Rachael Kimmerling
Contributors
Judith McDonald (Advisor)
Michael Tsatsomeros (Committee Member)
Matthew Hudelson (Committee Member)
Sergey Lapin (Committee Member)
Awarding Institution
Washington State University
Academic Unit
Department of Mathematics and Statistics
Theses and Dissertations
Doctor of Philosophy (PhD), Washington State University