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Conference object . 2023
https://doi.org/10.22323/1.430...
Article . 2023 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2023
License: CC BY
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Review on Quantum Computing for Lattice Field Theory

Authors: Funcke, Lena; Hartung, Tobias; Jansen, Karl; Kühn, Stefan;

Review on Quantum Computing for Lattice Field Theory

Abstract

In these proceedings, we review recent advances in applying quantum computing to lattice field theory. Quantum computing offers the prospect to simulate lattice field theories in parameter regimes that are largely inaccessible with the conventional Monte Carlo approach, such as the sign-problem afflicted regimes of finite baryon density, topological terms, and out-of-equilibrium dynamics. First proof-of-concept quantum computations of lattice gauge theories in (1+1) dimensions have been accomplished, and first resource-efficient quantum algorithms for lattice gauge theories in (1+1) and (2+1) dimensions have been developed. The path towards quantum computations of (3+1)-dimensional lattice gauge theories, including Lattice QCD, requires many incremental steps of improving both quantum hardware and quantum algorithms. After reviewing these requirements and recent advances, we discuss the main challenges and future directions.

25 pages, 9 figures; Proceedings of the 39th International Symposium on Lattice Field Theory, 8th-13th August 2022, Rheinische Friedrich-Wilhelms-Universit\"at Bonn, Germany

Country
Germany
Keywords

Quantum Physics, High Energy Physics - Lattice (hep-lat), baryon: density, lattice field theory, FOS: Physical sciences, 530, computer: quantum, topological, High Energy Physics - Lattice, quantum algorithm, baryon, density, hardware, info:eu-repo/classification/ddc/530, numerical calculations, Quantum Physics (quant-ph), computer, quantum, Monte Carlo, lattice

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    Top 10%
    influence
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Average
Top 10%
Green