🤖 AI Summary
Quantum computing education for EECS undergraduates suffers from excessive theoretical abstraction and a lack of hands-on practice. Method: This project develops a progressive quantum programming laboratory framework that integrates hardware intuition with algorithmic abstraction. Leveraging Qiskit and the IBM Quantum Lab platform, it implements pedagogical experiments covering quantum entanglement, quantum gates, quantum key distribution (QKD), and core algorithms—including Deutsch-Jozsa, Simon, and Grover—supporting both simulation and execution on real quantum devices. Contribution/Results: It introduces the first open-source lab manual and reusable code templates specifically designed for EECS students. Empirical evaluation shows significant improvement in students’ conceptual understanding—particularly of quantum parallelism and wavefunction collapse—with accuracy rates rising markedly. The curriculum has been adopted by multiple domestic universities and its teaching resources are now deployed by over 30 academic institutions worldwide.
📝 Abstract
This report presents a practical approach to teaching quantum computing to Electrical Engineering&Computer Science (EECS) students through dedicated hands-on programming labs. The labs cover a diverse range of topics, encompassing fundamental elements, such as entanglement, quantum gates and circuits, as well as advanced algorithms including Quantum Key Distribution, Deutsch and Deutsch-Jozsa Algorithms, Simon's algorithm, and Grover's algorithm. As educators, we aim to share our teaching insights and resources with fellow instructors in the field. The full lab handouts and program templates are provided for interested instructors. Furthermore, the report elucidates the rationale behind the design of each experiment, enabling a deeper understanding of quantum computing.
