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Solving Gauss's Law on Digital Quantum Computers with Loop-String-Hadron Digitization

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arxiv 1812.07554 v3 pith:L7JJWR3H submitted 2018-12-18 hep-lat hep-thquant-ph

classification hep-lathep-thquant-ph
keywords gaugebasisdigitaldigitizationgaussloop-string-hadronquantumqubits
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

We show that using the loop-string-hadron (LSH) formulation of SU(2) lattice gauge theory (arXiv:1912.06133) as a basis for digital quantum computation easily solves an important problem of fundamental interest: implementing gauge invariance (or Gauss's law) exactly. We first discuss the structure of the LSH Hilbert space in $d$ spatial dimensions, its truncation, and its digitization with qubits. Error detection and mitigation in gauge theory simulations would benefit from physicality "oracles,'"so we decompose circuits that flag gauge invariant wavefunctions. We then analyze the logical qubit costs and entangling gate counts involved with the protocols. The LSH basis could save or cost more qubits than a Kogut-Susskind-type representation basis, depending on how the bases are digitized as well as the spatial dimension. The numerous other clear benefits encourage future studies into applying this framework.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Creation of Wave Packets for Quantum Chromodynamics on Quantum Computers

    quant-ph 2025-01 conditional novelty 7.0 of 10

    A quantum algorithm based on Haag-Ruelle theory and LCU proposes to prepare hadron wave packets from the vacuum in 3D lattice QCD, with a success probability that shrinks polynomially with lattice spacing, energy, and...

  2. Arbitrary-Distance Quantum Error Correction with Gauss's Law for $\mathbb Z_2$ Lattice Gauge Theory

    hep-lat 2026-07 accept novelty 6.0 of 10

    Gauss's law constraints in Z2 lattice gauge theory can be made into quantum error-correcting codes of arbitrary distance, with provably optimal encoding rate within the constructed family.

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