TY - CHAP A1 - Krüger, Tom A1 - Mauerer, Wolfgang T1 - Quantum Annealing-Based Software Components T2 - Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops (ICSE'20): Seoul Republic of Korea 27.06.2020 - 19.07.2020 N2 - Quantum computers have the potential of solving problems more efficiently than classical computers. While first commercial prototypes have become available, the performance of such machines in practical application is still subject to exploration. Quantum computers will not entirely replace classical machines, but serve as accelerators for specific problems. This necessitates integrating quantum computational primitives into existing applications. In this paper, we perform a case study on how to augment existing software with quantum computational primitives for the Boolean satisfiability problem (SAT) implemented using a quantum annealer (QA). We discuss relevant quality measures for quantum components, and show that mathematically equivalent, but structurally different ways of transforming SAT to a QA can lead to substantial differences regarding these qualities. We argue that engineers need to be aware that (and which) details, although they may be less relevant in traditional software engineering, require considerable attention in quantum computing. KW - Boolean Satisfiability KW - Experimental Performance Analysis KW - Quantum Annealin KW - Quantum computing Y1 - 2020 SN - 9781450379632 U6 - https://doi.org/10.1145/3387940.3391472 SP - 445 EP - 450 PB - Association for Computing Machinery CY - New York, NY ER - TY - CHAP A1 - Sax, Irmi A1 - Feld, Sebastian A1 - Zielinski, Sebastian A1 - Gabor, Thomas A1 - Linnhoff-Popien, Claudia A1 - Mauerer, Wolfgang ED - Palesi, Maurizio T1 - Approximate approximation on a quantum annealer T2 - Proceedings of the 17th ACM International Conference on Computing Frontiers (CF '20): Catania Sicily Italy 11.05.2020 -13.05.2020 N2 - Many problems of industrial interest are NP-complete, and quickly exhaust resources of computational devices with increasing input sizes. Quantum annealers (QA) are physical devices that aim at this class of problems by exploiting quantum mechanical properties of nature. However, they compete with efficient heuristics and probabilistic or randomised algorithms on classical machines that allow for finding approximate solutions to large NP-complete problems. While first implementations of QA have become commercially available, their practical benefits are far from fully explored. To the best of our knowledge, approximation techniques have not yet received substantial attention. In this paper, we explore how problems' approximate versions of varying degree can be systematically constructed for quantum annealer programs, and how this influences result quality or the handling of larger problem instances on given set of qubits. We illustrate various approximation techniques on both, simulations and real QA hardware, on different seminal problems, and interpret the results to contribute towards a better understanding of the real-world power and limitations of current-state and future quantum computing. KW - approximation algorithms analysis KW - Approximation, NP-complete problems KW - Quantum Annealin KW - quantum computation KW - Simplifying Qubos Y1 - 2020 SN - 9781450379564 U6 - https://doi.org/10.1145/3387902.3392635 SP - 108 EP - 117 PB - Association for Computing Machinery CY - New York, NY, United States ER -