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

TL;DR

This study compares rotated and unrotated surface codes in quantum error correction, demonstrating that the rotated code achieves similar logical error rates with approximately 75% fewer qubits, supporting its practical efficiency.

Contribution

The paper provides a detailed numerical comparison of rotated and unrotated surface codes at low logical error rates, quantifying qubit savings and scaling behavior under circuit-level noise.

Findings

Rotated surface code uses about 75% of the qubits compared to unrotated code for the same logical error rate.

The qubit savings remain consistent across a range of physical error rates near 10^{-3}.

The work confirms the low-error-rate scaling behavior of surface codes under realistic noise models.

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.