Approximate approximation on a quantum annealer
- 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.
Author: | Irmi Sax, Sebastian Feld, Sebastian Zielinski, Thomas Gabor, Claudia Linnhoff-Popien, Wolfgang MauererORCiDGND |
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DOI: | https://doi.org/10.1145/3387902.3392635 |
ISBN: | 9781450379564 |
Parent Title (English): | Proceedings of the 17th ACM International Conference on Computing Frontiers (CF '20): Catania Sicily Italy 11.05.2020 -13.05.2020 |
Publisher: | Association for Computing Machinery |
Place of publication: | New York, NY, United States |
Editor: | Maurizio Palesi |
Document Type: | conference proceeding (article) |
Language: | English |
Year of first Publication: | 2020 |
Release Date: | 2022/04/11 |
Tag: | Approximation, NP-complete problems; Quantum Annealin; Simplifying Qubos; approximation algorithms analysis; quantum computation |
First Page: | 108 |
Last Page: | 117 |
Institutes: | Fakultät Informatik und Mathematik |
Fakultät Informatik und Mathematik / Labor für Digitalisierung (LFD) | |
Begutachtungsstatus: | peer-reviewed |
research focus: | Digitalisierung |
Licence (German): | Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG |