QAOA is a widely-studied and one of the most promising algorithms of the NISQ era. It was designed to solve combinatorial optimization problems. QAOA has numerous applications in such undustries like logistics, finance or pharmacy. Many international companies explore the possibilities of applying QAOA to their tasks and new applications are discovered regulary. This makes understanding QAOA highly important for people looking to explore the economic potential of quantum computing in their field. The goal of this lecture is to introduce the motivation and the basic concepts of QAOA to people with technical backgroud and basic knowledge in quantum computing, but not necessarily a deep background in quantum computing or a degree in physics. The lecture is meant to be presented by a teacher. It is provided with additional materials for self-learning and exercise. The lecture takes the approach of implementing the core components of QAOA in consequtive steps by using Qiskit and Python. In the end, Qiskit's implementation of QAOA will be introduced. In the exercise notebook students will answer conceptual questions and solve an instance of a MAXCUT problem using Qiskit's QAOA. Finally, more applications of QAOA in industy will be discussed.
Motivating the use of QAOA algorithm for optimization problems. Brief introduction to quantum computing.
Duration: 5 minutes
Form of Teaching: Presentation via powerpoint by teacher
Resource Used: Introduction_to_QAOA_Qiskit.pdf
Introduces Optimization goal, Cost function, Hamiltonian, Adiabatic theorem, QAOA algorithm, MaxCut Problem
Duration: 10 minutes
Form of Teaching: Presentation via Juyter notebook follow-along
Resource Used: QAOA_Lecture.ipynb
Background Information: This provides supplemental material on the QAOA theory with visualization and equations. QAOA_Theoretical_Background.ipynb
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Implementing QAOA from scratch using Qiskit tools.
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QAOA using Qiskits routine.
Duration: 35 minutes
Form of Teaching: Presentation via Juyter notebook follow-along
Resource used: QAOA_with_Qiskit.ipynb
Future outlook and homework description. Goal is to motivate usage of QAOA/Quantum Computing in other fields.
Duration: 5 minutes
Homework exercise: QAOA_Exercise.ipynb
Solutions to exercise: QAOA_Exercise_Solutions.ipynb
Extra reading material for students provided in the final section of Introduction_to_QAOA_Qiskit.pdf