Perspectives of quantum annealing: methods and implementations

Year: 2020

Authors: Hauke P., Katzgraber H.G., Lechner W., Nishimori H., Oliver W.D.

Autors Affiliation: Univ Trento, INO CNR BEC Ctr, I-38123 Povo, TN, Italy;‎ Univ Trento, Dept Phys, I-38123 Povo, TN, Italy;‎ Heidelberg Univ, Kirchhoff Inst Phys, D-69120 Heidelberg, Germany:‎ Heidelberg Univ, Inst Theoret Phys, D-69120 Heidelberg, Germany;‎ Microsoft Corp, Microsoft Quantum, Redmond, WA 98052 USA; Univ Innsbruck, Inst Theoret Phys, A-6020 Innsbruck, Austria; Austrian Acad Sci, Inst Quantum Opt & Quantum Informat, A-6020 Innsbruck, Austria;‎ Tokyo Inst Technol, Inst Innovat Res, Midori Ku, Nagatsuta Cho, Yokohama, Kanagawa 2268503, Japan; Tohoku Univ, Grad Sch Informat Sci, Sendai, Miyagi 9808579, Japan; MIT, Elect Res Lab, Cambridge, MA 02139 USA; MIT, Lincoln Lab, 244 Wood St, Lexington, MA 02420 USA

Abstract: Quantum annealing is a computing paradigm that has the ambitious goal of efficiently solving large-scale combinatorial optimization problems of practical importance. However, many challenges have yet to be overcome before this goal can be reached. This perspectives article first gives a brief introduction to the concept of quantum annealing, and then highlights new pathways that may clear the way towards feasible and large scale quantum annealing. Moreover, since this field of research is to a strong degree driven by a synergy between experiment and theory, we discuss both in this work. An important focus in this article is on future perspectives, which complements other review articles, and which we hope will motivate further research.

Journal/Review: REPORTS ON PROGRESS IN PHYSICS

Volume: 83 (5)      Pages from: 054401  to: 054401

KeyWords: review; quantum annealing; adiabatic quantum optimization
DOI: 10.1088/1361-6633/ab85b8

ImpactFactor: 17.264
Citations: 237
data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2024-10-13
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