Step-by-Step: Quantum Walk Implementations and Visualizations

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dc.contributor.authorJordon, Addie
dc.contributor.supervisorStege, Ulrike
dc.date.accessioned2023-12-20T22:59:19Z
dc.date.available2023-12-20T22:59:19Z
dc.date.copyright2023en_US
dc.date.issued2023-12-20
dc.degree.departmentDepartment of Computer Science
dc.degree.levelMaster of Applied Science M.A.Sc.en_US
dc.description.abstractQuantum walks (QWs) are the quantum analogue to classical random walks. I provide background and motivation for quantum walk algorithms and their applications. I present new visualizations for one-, two-, and three-dimensional quantum walks and explain how the visualizations can help teach quantum concepts such as superposition and interference. I contribute the Quantum Walk Visualization (QWalkVis) application for visualizing quantum walks. Users can select the dimensions, number of states, and number of steps in the walk, and generate probabilistic plots on-the-fly. Users are able to view the probabilities for each step of the walk one by one. QWalkVis aims to aid students in learning about quantum walks and foundational quantum concepts through interactive exploration. I present use cases of QWalkVis for both education and research purposes. I also propose a new application of quantum walks for creating noise distributions. Noise distributions are essential for noise sampling used in differential privacy, and help keep query data private.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/15743
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectquantum computingen_US
dc.subjectquantum walksen_US
dc.subjectquantum algorithmsen_US
dc.subjectquantumen_US
dc.subjectrandom walksen_US
dc.subjecteducationen_US
dc.titleStep-by-Step: Quantum Walk Implementations and Visualizationsen_US
dc.typeThesisen_US

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