2020
DOI: 10.1088/1361-6633/ab85b8
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Perspectives of quantum annealing: methods and implementations

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 dr… Show more

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Cited by 355 publications
(268 citation statements)
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“…Quantum simulations are emerging to be one of the important applications of quantum annealing [1][2][3][4], quite different, and arguably more natural, than the original intent of using such devices for optimization, the subject of many recent studies [5][6][7][8][9][10][11][12][13][14][15]. Prominent examples include the simulation of the Kosterlitz-Thouless topological phase transition [16,17] and three-dimensional spin glasses [18] using the D-Wave quantum annealing devices, that have successfully reproduced the behavior of various physical quantities and the structure of the phase diagram, as predicted by classical simulations.…”
Section: Introductionmentioning
confidence: 99%
“…Quantum simulations are emerging to be one of the important applications of quantum annealing [1][2][3][4], quite different, and arguably more natural, than the original intent of using such devices for optimization, the subject of many recent studies [5][6][7][8][9][10][11][12][13][14][15]. Prominent examples include the simulation of the Kosterlitz-Thouless topological phase transition [16,17] and three-dimensional spin glasses [18] using the D-Wave quantum annealing devices, that have successfully reproduced the behavior of various physical quantities and the structure of the phase diagram, as predicted by classical simulations.…”
Section: Introductionmentioning
confidence: 99%
“…A major category of optimization problems, particularly amenable to D-Wave's quantum annealing, are those that can be expressed as quadratic unconstrained binary optimization (QUBO) problems. QUBO refers to a pattern matching technique, that, among other applications, can be used in machine learning and optimization, and which involves minimizing a quadratic polynomial over binary variables [20,[23][24][25][26][27][28][29]. We emphasize that QUBO is NP-hard [29].…”
Section: Qpumentioning
confidence: 99%
“…A major category of optimization problems, particularly amenable to D-Wave's quantum annealing, are those that can be expressed as quadratic unconstrained binary optimization (QUBO) problems. QUBO refers to a pattern matching technique that, among other applications, can be used in machine learning and optimization, and which involves minimizing a quadratic polynomial over binary variables [21,[24][25][26][27][28][29][30]. We emphasize that QUBO is NP-hard [30].…”
Section: Introductionmentioning
confidence: 99%