A review on Quantum Approximate Optimization Algorithm and its variants

The Quantum Approximate Optimization Algorithm (QAOA) is a highly promising variational quantum algorithm that aims to solve combinatorial optimization problems that are classically intractable. This comprehensive review offers an overview of the current state of QAOA, encompassing its performance a...

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Veröffentlicht in:Physics reports Jg. 1068; S. 1 - 66
Hauptverfasser: Blekos, Kostas, Brand, Dean, Ceschini, Andrea, Chou, Chiao-Hui, Li, Rui-Hao, Pandya, Komal, Summer, Alessandro
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 02.06.2024
Schlagworte:
Combinatorial optimization problems
NISQ algorithms
Quantum Approximate Optimization Algorithm (QAOA)
Quantum optimization
Variational Quantum Algorithms (VQAs)
Quantum Approximate Optimization Algorithm (QAOA)
Variational Quantum Algorithms (VQAs)
Combinatorial optimization problems
Quantum optimization
NISQ algorithms
ISSN:0370-1573, 1873-6270
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Zusammenfassung:The Quantum Approximate Optimization Algorithm (QAOA) is a highly promising variational quantum algorithm that aims to solve combinatorial optimization problems that are classically intractable. This comprehensive review offers an overview of the current state of QAOA, encompassing its performance analysis in diverse scenarios, its applicability across various problem instances, and considerations of hardware-specific challenges such as error susceptibility and noise resilience. Additionally, we conduct a comparative study of selected QAOA extensions and variants, while exploring future prospects and directions for the algorithm. We aim to provide insights into key questions about the algorithm, such as whether it can outperform classical algorithms and under what circumstances it should be used. Towards this goal, we offer specific practical points in a form of a short guide.
ISSN:0370-1573
1873-6270
DOI:10.1016/j.physrep.2024.03.002