Benchmarking the Planar Honeycomb Code
1Google Quantum AI, Santa Barbara, California 93117, USA
2University of California, Santa Barbara, 93106, USA
Published: | 2022-09-21, volume 6, page 813 |
Eprint: | arXiv:2202.11845v3 |
Doi: | https://doi.org/10.22331/q-2022-09-21-813 |
Citation: | Quantum 6, 813 (2022). |
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Abstract
We improve the planar honeycomb code by describing boundaries that need no additional physical connectivity, and by optimizing the shape of the qubit patch. We then benchmark the code using Monte Carlo sampling to estimate logical error rates and derive metrics including thresholds, lambdas, and teraquop qubit counts. We determine that the planar honeycomb code can create a logical qubit with one-in-a-trillion logical error rates using 7000 physical qubits at a 0.1% gate-level error rate (or 900 physical qubits given native two-qubit parity measurements). Our results cement the honeycomb code as a promising candidate for two-dimensional qubit architectures with sparse connectivity.

Featured image: The cycle of measurements that defines the planar honeycomb code, and the locations of logical observables throughout this cycle. Uses XYZ=RGB color coding to map Pauli operators to colors.
Estimating overheads for quantum fault-tolerance in the honeycomb code (Talk by Mike Newman)
A short history of the honeycomb code (Talk by Craig Gidney)
Popular summary
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► References
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The above citations are from Crossref's cited-by service (last updated successfully 2023-10-01 02:50:28) and SAO/NASA ADS (last updated successfully 2023-10-01 02:50:28). The list may be incomplete as not all publishers provide suitable and complete citation data.
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