Application of the quantum approximate optimization algorithm to combinatorial optimization problems
Licentiate thesis, 2020
This licentiate thesis is an extended introduction to the accompanying papers, which encompass a study of the quantum approximate optimization algorithm (QAOA). It is a hybrid quantum-classical algorithm for solving combinatorial optimization problems and is a promising algorithm to run on near term quantum devices. In this thesis, we will introduce the workings of the QAOA, together with some applications of it on combinatorial optimization problems.
combinatorial optimization
quantum computing
Quantum approximate optimization algorithm
Author
Pontus Vikstål
Chalmers, Microtechnology and Nanoscience (MC2), Applied Quantum Physics
Improved Success Probability with Greater Circuit Depth for the Quantum Approximate Optimization Algorithm
Physical Review Applied,; Vol. 14(2020)
Journal article
Applying the Quantum Approximate Optimization Algorithm to the Tail-Assignment Problem
Physical Review Applied,; Vol. 14(2020)
Journal article
Subject Categories
Other Physics Topics
Technical report MC2 - Department of Microtechnology and Nanoscience, Chalmers University of Technology: 436
Publisher
Chalmers