Course Description
This graduate-level course provides a rigorous introduction to the principles and practice of quantum computing, bridging the gap between foundational quantum mechanics and contemporary algorithmic developments. Students will gain a deep understanding of the mathematical structures that underpin quantum computation, including complex vector spaces, tensor products, and unitary operations, as well as the physical realizations of qubits across various quantum hardware platforms.
Beginning with a review of Hilbert space theory and Dirac notation, the course will progressively introduce qubits, quantum gates, and circuit model formalism. The curriculum emphasizes both conceptual clarity and practical skill, offering hands-on experience with quantum programming frameworks such as Qiskit and Cirq. Throughout the semester, students will explore pivotal quantum algorithms—Deutsch-Jozsa, Simon, Shor, Grover, VQE, and QAOA—demonstrating their computational advantages over classical counterparts.
The course also addresses essential topics in quantum error correction and fault-tolerant computing, presenting the theoretical underpinnings of stabilizer codes and threshold theorems. Students will investigate the challenges of decoherence, leakage, and gate imperfections, and learn strategies for mitigating errors in near-term quantum devices.
By the end of the semester, participants will have designed and simulated a complete quantum algorithm tailored to a real-world problem, showcasing their ability to translate abstract theory into tangible quantum solutions. The final project will be presented to the class, fostering a collaborative learning environment and reinforcing the interdisciplinary nature of quantum technology.