Monte Carlo graph search for quantum circuit optimization

verfasst von: Bodo Rosenhahn, Tobias J. Osborne
Abstract: The building blocks of quantum algorithms and software are quantum gates, with the appropriate combination of quantum gates leading to a desired quantum circuit. Deep expert knowledge is necessary to discover effective combinations of quantum gates to achieve a desired quantum algorithm for solving a specific task. This is especially challenging for quantum machine learning and signal processing. For example, it is not trivial to design a quantum Fourier transform from scratch. This work proposes a quantum architecture search algorithm which is based on a Monte Carlo graph search and measures of importance sampling. It is applicable to the optimization of gate order for both discrete gates and gates containing continuous variables. Several numerical experiments demonstrate the applicability of the proposed method for the automatic discovery of quantum circuits.
Organisationseinheit(en): QuantumFrontiers
Institut für Informationsverarbeitung
Forschungszentrum L3S
Institut für Theoretische Physik
Typ: Artikel
Journal: Physical Review A
Band: 108
Anzahl der Seiten: 10
ISSN: 2469-9926
Publikationsdatum: 19.12.2023
Publikationsstatus: Veröffentlicht
Peer-reviewed: Ja
ASJC Scopus Sachgebiete: Atom- und Molekularphysik sowie Optik
Elektronische Version(en): https://doi.org/10.48550/arXiv.2307.07353 (Zugang: Offen)
https://doi.org/10.1103/PhysRevA.108.062615 (Zugang: Geschlossen)

BibTeX

@article{4f7a65055d6b4d178aca43833cc25bf3,
title = "Monte Carlo graph search for quantum circuit optimization",
abstract = "The building blocks of quantum algorithms and software are quantum gates, with the appropriate combination of quantum gates leading to a desired quantum circuit. Deep expert knowledge is necessary to discover effective combinations of quantum gates to achieve a desired quantum algorithm for solving a specific task. This is especially challenging for quantum machine learning and signal processing. For example, it is not trivial to design a quantum Fourier transform from scratch. This work proposes a quantum architecture search algorithm which is based on a Monte Carlo graph search and measures of importance sampling. It is applicable to the optimization of gate order for both discrete gates and gates containing continuous variables. Several numerical experiments demonstrate the applicability of the proposed method for the automatic discovery of quantum circuits.",
author = "Bodo Rosenhahn and Osborne, {Tobias J.}",
note = "Funding Information: This work was supported, in part, by Quantum Valley Lower Saxony and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), Project No. 274200144, SFB1227, under Germany's Excellence Strategies EXC-2123 QuantumFrontiers and EXC-2122 PhoenixD. ",
year = "2023",
month = dec,
day = "19",
doi = "10.48550/arXiv.2307.07353",
language = "English",
volume = "108",
journal = "Physical Review A",
issn = "2469-9926",
publisher = "American Physical Society",
number = "6",
}