Advanced Topics in Quantum Computing
Optional Course, Master Studies
Course & Seminar/Lab Instructor:
- Conf. dr. Andreea Arusoaie [email: andreea.arusoaie@info.uaic.ro]
Topics:
- Introduction to Quantum Computing: Motivation & Context, Bit vs. Qubit, Implementation of Qubits, Superposition, Measurement;
- Quantum Circuit Model: Quantum Gates, Multi qubit systems, Entanglement;
- Quantum Algorithms: Quantum Parallelism, Grover's Algorithm, Factoring-Shor's Algorithm
- Quantum Error Correction
- Variational Algorithms
- Quantum Machine Learning
- Programming in Qiskit - IBM Quantum Computing
Some useful references:
- Nielsen & Chuang — Quantum Computation and Quantum Information (2010)
- C. Bernhardt — Quantum Computing for Everyone (2019)
- Thomas G. Wong — Introduction to Classical and Quantum Computing (2022).
- Robert S. Sutor — Dancing with Qubits, 2nd Ed., Packt (2024).
- J. Watrous - IBM Quantum Learning — Basics of Quantum Information & Fundamentals of Quantum Algorithms.
Course Structure by Week
Week 2 — Principles of Quantum Mechanics
Week 3 — Quantum Circuit Model I: Quantum Gates
Week 4 — Quantum Circuit Model II: Multi-qubit systems. Multi-qubit Gate. Measurement
Week 5 — Quantum Circuit Model III: Universal Quantum Computation. No-Cloning theorem. Entanglement.
Week 6 — Teleportation. Simple quantum algorithms: Quantum Parallelism, Deutsch
Week 7 — Quantum Algorithms: Deutsch-Jozsa, Simon, Grover’s Algorithm
Week 9 — QFT. Quantum Period Find. Factoring-Shor’s Algorithm
Week 10 — Transpilation. Quantum Error Correction. Fault tolerant QC
Week 11 — Quantum Machine Learning I: Quantum kernel methods, Quantum neural networks
Week 12 — Quantum Machine Learning II : QSVM, Quantum generative models. Variational algorithms for optimization QAOA
Week 13 — Applications and Use Cases of Quantum Computing
Some useful Materials/Books -
[here]