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Faculty of Graduate Studies

Samantha Norrie

  • BSc (University of Victoria, 2023)
Notice of the Final Oral Examination for the Degree of Master of Science

Topic

Visual and Interactive Tools in Support of a Hands-on Introduction to Quantum Computing

Department of Computer Science

Date & location

  • Thursday, January 15, 2026
  • 1:00 P.M.
  • Engineering Computer Science Building, Room 468

Examining Committee

Supervisory Committee

  • Dr. Ulrike Stege, Department of Computer Science, University of Victoria (Co-Supervisor)
  • Dr. Anthony Estey, Department of Computer Science, UVic (Co-Supervisor)

External Examiner

  • Dr. Navneet Popli, Department of Electrical and Computer Engineering, University of Victoria

Chair of Oral Examination

  • Dr. Michael Eby, School of Earth and Ocean Sciences, UVic

Abstract

The rapid growth of quantum computing technology has created a need for educational tools that help foster intuitive understanding of quantum concepts. Although exploratory learning has demonstrated effectiveness in other science, technology, engineering, and mathematics domains, its role in quantum computing education remains underexplored. This thesis presents the design, implementation, and evaluation of two exploratory learning tools, QNotation and QGrover, which were developed to support introductory quantum computing instruction.

QNotation is a browser-based application that displays quantum circuits written using quantum software libraries (such as Qiskit, PennyLane, or Cirq) in circuit, Dirac, and matrix notation. To ensure reliability and conceptual accuracy, QNotation incorporates a comprehensive automated testing and verification framework, including integration tests executed through continuous integration workflows. We conducted an exploratory study to examine how students interact with QNotation. Preliminary survey data and usage observations provide initial insights into learner engagement patterns within exploratory quantum computing environments. QGrover, another browser-based application, complements QNotation by allowing users to interact with Grover’s algorithm through dynamic visualizations. Users can configure the number of qubits, marked states, and iterations (or select the optimal count) used by the algorithm. This enables them to observe how the circuit and state vectors evolve step-by-step. By supporting exploratory manipulation, QGrover helps learners develop intuition about the algorithm’s dependence on its problem parameters.

The contributions of this work is an overview of how the aforementioned tools have been designed according to software engineering best practices to align with modern industry needs. Additionally, we demonstrate that well-designed exploratory tools can meaningfully improve the teaching and learning of quantum computing. We also provide example material to enable these tools to be easily integrated into learning exercises and assessments.

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