https://doi.org/10.1140/epja/s10050-024-01385-5
Review
Graph algorithms with neutral atom quantum processors
1
PASQAL, 7 rue Léonard de Vinci, 91300, Massy, France
2
Laboratoire Charles Fabry, Institut d’Optique Graduate School, Université Paris-Saclay, CNRS, 91127, Palaiseau, France
Received:
3
April
2024
Accepted:
24
July
2024
Published online:
6
September
2024
Neutral atom technology has steadily demonstrated significant theoretical and experimental advancements, positioning itself as a front-runner platform for running quantum algorithms. One unique advantage of this technology lies in the ability to reconfigure the geometry of the qubit register, from shot to shot. This unique feature makes possible the native embedding of graph-structured problems at the hardware level, with profound consequences for the resolution of complex optimization and machine learning tasks. By driving qubits, one can generate processed quantum states which retain graph complex properties. These states can then be leveraged to offer direct solutions to problems or as resources in hybrid quantum-classical schemes. In this paper, we review the advancements in quantum algorithms for graph problems running on neutral atom Quantum Processing Units (QPUs), and discuss recently introduced embedding and problem-solving techniques. In addition, we clarify ongoing advancements in hardware, with an emphasis on enhancing the scalability, controllability and computation repetition rate of neutral atom QPUs.
Constantin Dalyac and Lucas Leclerc contributed equally to this work.
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© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.