Course Outline
Introduction.
Overview of Quantum Physics Theories Applied in Quantum Computing.
- Fundamentals of quantum superposition.
- Fundamentals of quantum entanglement.
- Mathematical foundations of quantum computing.
Overview of Quantum Computing.
- Distinguishing quantum computing from classical electronic computing.
- Integrating quantum behaviours into quantum computing.
- The Qubit.
- Implementing Dirac notation.
- Computational basis measurements in quantum computing.
- Quantum circuits and quantum oracles.
Working with Vectors and Matrices in Quantum Computing.
- Matrix multiplication using quantum physics.
- Conventions of tensor products.
Applying Advanced Matrix Concepts to Quantum Computing.
Overview of Quantum Computers and Quantum Simulators.
- The quantum hardware and its components.
- Running a quantum simulator.
- Executable quantum mechanisms in a quantum simulation.
- Performing quantum computations in a quantum computer.
Working with Quantum Computing Models.
- Logic and functions of different quantum gates.
- Understanding superposition and entanglement effects on quantum gates.
Utilising Shor's Algorithm and Quantum Computing Cryptography.
Implementing Grover's Algorithm in Quantum Computing.
Estimating a Quantum Phase in a Quantum Computer.
- The quantum Fourier transform.
Writing Basic Quantum Computing Algorithms and Programs for a Quantum Computer.
- Utilising the appropriate tools and language for quantum computing.
- Setting up quantum circuits and specifying quantum gates.
Compiling and Running Quantum Algorithms and Programs in a Quantum Computer.
Testing and Debugging Quantum Algorithms and Quantum Computer Programs.
Identifying and Correcting Algorithm Errors Using Quantum Error Correction (QEC).
Overview of Quantum Computing Hardware and Architecture.
Integrating Quantum Algorithms and Programs with the Quantum Hardware.
Troubleshooting.
Advancing Quantum Computing for Future Quantum Information Science Applications.
Summary and Conclusion.
Requirements
- Knowledge of mathematical methods in probability and linear algebra.
- Understanding of foundational computer science theories and algorithms.
- An understanding of elementary quantum physics concepts.
- Basic experience with quantum mechanics models and theories.
Target Audience
- Computer Scientists.
- Engineers.
