Quantum annealing for industry applications: introduction and review

By Sheir Yarkoni, Elena Raponi, Thomas Bäck, Sebastian Schmitt. Reports on progress in physics. Physical Society, 2021

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Quantum annealing (QA) is a heuristic quantum optimization algorithm that can be used to solve combinatorial optimization problems. In recent years, advances in quantum technologies have enabled the development of small- and intermediate-scale quantum processors that implement the QA algorithm for programmable use. Specifically, QA processors produced by D-Wave systems have been studied and tested extensively in both research and industrial settings across different disciplines. In this paper we provide a literature review of the theoretical motivations for QA as a heuristic quantum optimization algorithm, the software and hardware that is required to use such quantum processors, and the state-of-the-art applications and proofs-of-concepts that have been demonstrated using them. The goal of our review is to provide a centralized and condensed source regarding applications of QA technology. We identify the advantages, limitations, and potential of QA for both researchers and practitioners from various fields.

Subfields: Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/a2a893aad107c3c382a84454318247d72926f592