Optimisation and Search via Quantum Walks

Samuel Marsh

Research output: ThesisDoctoral Thesis

224 Downloads (Pure)

Abstract

This thesis proposes a novel framework for finding high-quality solutions to combinatorial optimisation problems, via an alternating series of quantum walks and solution-quality-dependent phase shifts. We demonstrate how problem constraints can be encoded through choice of graph structure, and derive efficient quantum circuits to implement the framework. The scheme is shown to have improved performance for real-world problems such as financial portfolio optimisation. We also apply the framework to the spatial database search problem, demonstrating improved success probability and runtime compared to previous techniques. Finally, we explore the power of nonlinear quantum mechanics applied to solving combinatorial optimisation problems.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • The University of Western Australia
Supervisors/Advisors
  • Wang, Jingbo, Supervisor
  • Noakes, Lyle, Supervisor
Thesis sponsors
Award date30 Oct 2021
DOIs
Publication statusUnpublished - 2021

Fingerprint

Dive into the research topics of 'Optimisation and Search via Quantum Walks'. Together they form a unique fingerprint.

Cite this