Quantum Information Processing

, Volume 15, Issue 2, pp 609–636

Performance of two different quantum annealing correction codes


DOI: 10.1007/s11128-015-1201-z

Cite this article as:
Mishra, A., Albash, T. & Lidar, D.A. Quantum Inf Process (2016) 15: 609. doi:10.1007/s11128-015-1201-z


Quantum annealing is a promising approach for solving optimization problems, but like all other quantum information processing methods, it requires error correction to ensure scalability. In this work, we experimentally compare two quantum annealing correction (QAC) codes in the setting of antiferromagnetic chains, using two different quantum annealing processors. The lower-temperature processor gives rise to higher success probabilities. The two codes differ in a number of interesting and important ways, but both require four physical qubits per encoded qubit. We find significant performance differences, which we explain in terms of the effective energy boost provided by the respective redundantly encoded logical operators of the two codes. The code with the higher energy boost results in improved performance, at the expense of a lower-degree encoded graph. Therefore, we find that there exists an important trade-off between encoded connectivity and performance for quantum annealing correction codes.


Quantum computation Quantum error correction Quantum annealing Error correction Quantum optimization Superconducting flux qubits Transverse field Ising model Spin chains 

Funding information

Funder NameGrant NumberFunding Note
Army Research Office (US)
  • W911NF-12-1-0523
Multidisciplinary University Research Initiative
  • W911NF-11-1-0268
University of Southern California (US)
    National Science Foundation (US)
    • CCF-1551064
    Fermilab, Office of Science (US)
    • 622302

    Copyright information

    © Springer Science+Business Media New York 2015

    Authors and Affiliations

    1. 1.Department of Physics and AstronomyUniversity of Southern CaliforniaLos AngelesUSA
    2. 2.Center for Quantum Information Science and TechnologyUniversity of Southern CaliforniaLos AngelesUSA
    3. 3.Information Sciences InstituteUniversity of Southern CaliforniaMarina del ReyUSA
    4. 4.Department of Electrical EngineeringUniversity of Southern CaliforniaLos AngelesUSA
    5. 5.Department of ChemistryUniversity of Southern CaliforniaLos AngelesUSA

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