QPLEX: Towards the Integration of Platform Agnostic Quantum Computation into Combinatorial Optimization Software
| dc.contributor.author | Giraldo Botello, Juan Fernando | |
| dc.contributor.supervisor | Müller, Hausi A. | |
| dc.contributor.supervisor | Villegas Machado, Norha Milena | |
| dc.date.accessioned | 2024-04-10T22:03:26Z | |
| dc.date.available | 2024-04-10T22:03:26Z | |
| dc.date.issued | 2024 | |
| dc.degree.department | Department of Computer Science | |
| dc.degree.level | Master of Science MSc | |
| dc.description.abstract | Quantum computing has the potential to surpass the capabilities of current classical computers when solving complex problems. Combinatorial optimization has emerged as a pivotal target area for quantum computers, as problems in this field are renowned for their complexity and resource-intensive nature. Moreover, these challenges play a critical role in various industrial sectors, including logistics, manufacturing, and finance. This thesis explores the integration of quantum computation into classical software tools as a means to potentially address combinatorial optimization problems more efficiently and effectively. This work introduces QPLEX, a Python software library that enables practitioners and researchers to implement the general mathematical formulation of a given combinatorial optimization problem once and execute it seamlessly on multiple quantum devices using various quantum algorithms. This software solution automatically adapts a general optimization model to the specific instructions utilized by the target quantum device’s SDK. It offers a versatile execution workflow capable of running gate-based hybrid quantum-classical algorithms for combinatorial optimization in a platform-agnostic manner. This approach reduces the programming overhead required for modeling and experimenting with combinatorial optimization solutions. Within this manuscript, we address and introduce the various aspects associated with the development of QPLEX in a clear and comprehensive manner. These aspects encompass the quantum algorithms and quantum hardware available in the library, along with QPLEX’s system design and implementation. Additionally, we provide a guide on how to use the library and conduct a thorough evaluation of the software solution within a specific use case as part of this thesis. | |
| dc.description.scholarlevel | Graduate | |
| dc.identifier.uri | https://hdl.handle.net/1828/16357 | |
| dc.language | English | eng |
| dc.language.iso | en | |
| dc.rights | Available to the World Wide Web | |
| dc.subject | Quantum Computing | |
| dc.subject | Software Engineering | |
| dc.subject | Combinatorial Optimization | |
| dc.subject | Quantum Software Engineering | |
| dc.title | QPLEX: Towards the Integration of Platform Agnostic Quantum Computation into Combinatorial Optimization Software | |
| dc.type | Thesis |