Application of the quantum approximate optimization algorithm to combinatorial optimization problems
Licentiatavhandling, 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

Kollektorn (A423)
Opponent: Sevag Gharibian, Paderborn Universitet, Tyskland

Författare

Pontus Vikstål

Chalmers, Mikroteknologi och nanovetenskap (MC2), Tillämpad kvantfysik

Improved Success Probability with Greater Circuit Depth for the Quantum Approximate Optimization Algorithm

Physical Review Applied,; Vol. 14(2020)

Artikel i vetenskaplig tidskrift

Applying the Quantum Approximate Optimization Algorithm to the Tail-Assignment Problem

Physical Review Applied,; Vol. 14(2020)

Artikel i vetenskaplig tidskrift

Ämneskategorier

Annan fysik

Technical report MC2 - Department of Microtechnology and Nanoscience, Chalmers University of Technology: 436

Utgivare

Chalmers tekniska högskola

Kollektorn (A423)

Online

Opponent: Sevag Gharibian, Paderborn Universitet, Tyskland

Mer information

Senast uppdaterat

2020-12-15