Solving Combinatorial Optimization Problems on a D-Wave Quantum Annealer and Development of Higher Level Hardware Abstraction Layers
Julian Hatzky · elib (German Aerospace Center) · 2021
The area of quantum computing is a relatively new and promising branch of computation that hopes to provide help especially in the field of non-deterministic polynomial hard problems. Due to the fact that quantum computers are a heuristically non-binary approach to computation, based on the effects of quantum mechanics, a bunch of advantages and disadvantages come with it. The following work focuses especially on so-called quantum annealers, a special architecture of quantum computers that one can see as an application-specific unit that is using certain quantum mechanical effects to target binary quadratic optimization problems of the class of non-deterministic polynomial-time problems and tries to solve them faster than classical computers can do. Because this is a whole new area, it lacks extensive software support which is addressed in this work. Hence the majority of the thesis aims to develop and extend software that enables users to solve problem instances on a quantum annealer fast and reliable. Furthermore, the necessary steps to solve combinatorial optimization problems are explained and the necessary background of quantum physics theory is given. In conclusion, the main question of this work can be described as follows: 'Is it possible to create an automated pipeline to solve problems on a D-Wave Systems n.d. quantum annealer?'.