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Compare the Pair: Rotated vs. Unrotated Surface Codes at Equal Logical Error Rates

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arxiv 2409.14765 v2 pith:APJ66BGJ submitted 2024-09-23 quant-ph

classification quant-ph
keywords codeerrorlogicalratessurfacerotatedcodesnumber
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abstract

Practical quantum computers will require resource-efficient error-correcting codes. The rotated surface code uses approximately half the number of qubits as the unrotated surface code to create a logical qubit with the same error-correcting distance. However, instead of distance, a more useful qubit-saving metric would be based on logical error rates. In this work we find the well-below-threshold scaling of logical to physical error rates under circuit-level noise for both codes at high odd and even distances, then compare the number of qubits used by each code to achieve equal logical error rates. We perform Monte Carlo sampling of memory experiment circuits with all valid CNOT orders, using the stabiliser simulator Stim and the uncorrelated minimum-weight perfect-matching decoder PyMatching 2. We find that the rotated code uses $74 - 75\%$ the number of qubits used by the unrotated code, depending on the noise model, to achieve a logical error rate of $p_L = 10^{-12}$ at the operational physical error rate of $p=10^{-3}$. The ratio remains $\approx75\%$ for physical error rates within a factor of two of $p=10^{-3}$ for all useful logical error rates. Our work finds the low-$p_L$ scaling of the surface code and clarifies the qubit savings provided by the rotated surface code, providing numerical justification for its use in future implementations of the surface code.

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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. Degeneracy Cutting: A Local and Efficient Post-Processing for Belief Propagation Decoding of Quantum Low-Density Parity-Check Codes

    quant-ph 2025-10 conditional novelty 6.0 of 10

    A local O(n) post-processor called degeneracy cutting prunes one low-probability qubit per stabilizer and reruns belief propagation, matching or beating BP+OSD accuracy in several qLDPC settings.

  2. Leveraging biased noise for more efficient quantum error correction at the circuit-level with two-level qubits

    quant-ph 2025-05 conditional novelty 6.0 of 10

    Bias-preserving CZ gates plus small residual CNOT bias enable a 90% threshold improvement and up to 75% footprint reduction for the XZZX code in two-level qubits.

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